sd.html

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<title>Data Science Speed Dating Final Project</title>

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  content: "\e252";
}
.glyphicon-triangle-top:before {
  content: "\e253";
}
.glyphicon-console:before {
  content: "\e254";
}
.glyphicon-superscript:before {
  content: "\e255";
}
.glyphicon-subscript:before {
  content: "\e256";
}
.glyphicon-menu-left:before {
  content: "\e257";
}
.glyphicon-menu-right:before {
  content: "\e258";
}
.glyphicon-menu-down:before {
  content: "\e259";
}
.glyphicon-menu-up:before {
  content: "\e260";
}
* {
  -webkit-box-sizing: border-box;
  -moz-box-sizing: border-box;
  box-sizing: border-box;
}
*:before,
*:after {
  -webkit-box-sizing: border-box;
  -moz-box-sizing: border-box;
  box-sizing: border-box;
}
html {
  font-size: 10px;
  -webkit-tap-highlight-color: rgba(0, 0, 0, 0);
}
body {
  font-family: "Helvetica Neue", Helvetica, Arial, sans-serif;
  font-size: 13px;
  line-height: 1.42857143;
  color: #000;
  background-color: #fff;
}
input,
button,
select,
textarea {
  font-family: inherit;
  font-size: inherit;
  line-height: inherit;
}
a {
  color: #337ab7;
  text-decoration: none;
}
a:hover,
a:focus {
  color: #23527c;
  text-decoration: underline;
}
a:focus {
  outline: 5px auto -webkit-focus-ring-color;
  outline-offset: -2px;
}
figure {
  margin: 0;
}
img {
  vertical-align: middle;
}
.img-responsive,
.thumbnail > img,
.thumbnail a > img,
.carousel-inner > .item > img,
.carousel-inner > .item > a > img {
  display: block;
  max-width: 100%;
  height: auto;
}
.img-rounded {
  border-radius: 3px;
}
.img-thumbnail {
  padding: 4px;
  line-height: 1.42857143;
  background-color: #fff;
  border: 1px solid #ddd;
  border-radius: 2px;
  -webkit-transition: all 0.2s ease-in-out;
  -o-transition: all 0.2s ease-in-out;
  transition: all 0.2s ease-in-out;
  display: inline-block;
  max-width: 100%;
  height: auto;
}
.img-circle {
  border-radius: 50%;
}
hr {
  margin-top: 18px;
  margin-bottom: 18px;
  border: 0;
  border-top: 1px solid #eeeeee;
}
.sr-only {
  position: absolute;
  width: 1px;
  height: 1px;
  margin: -1px;
  padding: 0;
  overflow: hidden;
  clip: rect(0, 0, 0, 0);
  border: 0;
}
.sr-only-focusable:active,
.sr-only-focusable:focus {
  position: static;
  width: auto;
  height: auto;
  margin: 0;
  overflow: visible;
  clip: auto;
}
[role="button"] {
  cursor: pointer;
}
h1,
h2,
h3,
h4,
h5,
h6,
.h1,
.h2,
.h3,
.h4,
.h5,
.h6 {
  font-family: inherit;
  font-weight: 500;
  line-height: 1.1;
  color: inherit;
}
h1 small,
h2 small,
h3 small,
h4 small,
h5 small,
h6 small,
.h1 small,
.h2 small,
.h3 small,
.h4 small,
.h5 small,
.h6 small,
h1 .small,
h2 .small,
h3 .small,
h4 .small,
h5 .small,
h6 .small,
.h1 .small,
.h2 .small,
.h3 .small,
.h4 .small,
.h5 .small,
.h6 .small {
  font-weight: normal;
  line-height: 1;
  color: #777777;
}
h1,
.h1,
h2,
.h2,
h3,
.h3 {
  margin-top: 18px;
  margin-bottom: 9px;
}
h1 small,
.h1 small,
h2 small,
.h2 small,
h3 small,
.h3 small,
h1 .small,
.h1 .small,
h2 .small,
.h2 .small,
h3 .small,
.h3 .small {
  font-size: 65%;
}
h4,
.h4,
h5,
.h5,
h6,
.h6 {
  margin-top: 9px;
  margin-bottom: 9px;
}
h4 small,
.h4 small,
h5 small,
.h5 small,
h6 small,
.h6 small,
h4 .small,
.h4 .small,
h5 .small,
.h5 .small,
h6 .small,
.h6 .small {
  font-size: 75%;
}
h1,
.h1 {
  font-size: 33px;
}
h2,
.h2 {
  font-size: 27px;
}
h3,
.h3 {
  font-size: 23px;
}
h4,
.h4 {
  font-size: 17px;
}
h5,
.h5 {
  font-size: 13px;
}
h6,
.h6 {
  font-size: 12px;
}
p {
  margin: 0 0 9px;
}
.lead {
  margin-bottom: 18px;
  font-size: 14px;
  font-weight: 300;
  line-height: 1.4;
}
@media (min-width: 768px) {
  .lead {
    font-size: 19.5px;
  }
}
small,
.small {
  font-size: 92%;
}
mark,
.mark {
  background-color: #fcf8e3;
  padding: .2em;
}
.text-left {
  text-align: left;
}
.text-right {
  text-align: right;
}
.text-center {
  text-align: center;
}
.text-justify {
  text-align: justify;
}
.text-nowrap {
  white-space: nowrap;
}
.text-lowercase {
  text-transform: lowercase;
}
.text-uppercase {
  text-transform: uppercase;
}
.text-capitalize {
  text-transform: capitalize;
}
.text-muted {
  color: #777777;
}
.text-primary {
  color: #337ab7;
}
a.text-primary:hover,
a.text-primary:focus {
  color: #286090;
}
.text-success {
  color: #3c763d;
}
a.text-success:hover,
a.text-success:focus {
  color: #2b542c;
}
.text-info {
  color: #31708f;
}
a.text-info:hover,
a.text-info:focus {
  color: #245269;
}
.text-warning {
  color: #8a6d3b;
}
a.text-warning:hover,
a.text-warning:focus {
  color: #66512c;
}
.text-danger {
  color: #a94442;
}
a.text-danger:hover,
a.text-danger:focus {
  color: #843534;
}
.bg-primary {
  color: #fff;
  background-color: #337ab7;
}
a.bg-primary:hover,
a.bg-primary:focus {
  background-color: #286090;
}
.bg-success {
  background-color: #dff0d8;
}
a.bg-success:hover,
a.bg-success:focus {
  background-color: #c1e2b3;
}
.bg-info {
  background-color: #d9edf7;
}
a.bg-info:hover,
a.bg-info:focus {
  background-color: #afd9ee;
}
.bg-warning {
  background-color: #fcf8e3;
}
a.bg-warning:hover,
a.bg-warning:focus {
  background-color: #f7ecb5;
}
.bg-danger {
  background-color: #f2dede;
}
a.bg-danger:hover,
a.bg-danger:focus {
  background-color: #e4b9b9;
}
.page-header {
  padding-bottom: 8px;
  margin: 36px 0 18px;
  border-bottom: 1px solid #eeeeee;
}
ul,
ol {
  margin-top: 0;
  margin-bottom: 9px;
}
ul ul,
ol ul,
ul ol,
ol ol {
  margin-bottom: 0;
}
.list-unstyled {
  padding-left: 0;
  list-style: none;
}
.list-inline {
  padding-left: 0;
  list-style: none;
  margin-left: -5px;
}
.list-inline > li {
  display: inline-block;
  padding-left: 5px;
  padding-right: 5px;
}
dl {
  margin-top: 0;
  margin-bottom: 18px;
}
dt,
dd {
  line-height: 1.42857143;
}
dt {
  font-weight: bold;
}
dd {
  margin-left: 0;
}
@media (min-width: 541px) {
  .dl-horizontal dt {
    float: left;
    width: 160px;
    clear: left;
    text-align: right;
    overflow: hidden;
    text-overflow: ellipsis;
    white-space: nowrap;
  }
  .dl-horizontal dd {
    margin-left: 180px;
  }
}
abbr[title],
abbr[data-original-title] {
  cursor: help;
  border-bottom: 1px dotted #777777;
}
.initialism {
  font-size: 90%;
  text-transform: uppercase;
}
blockquote {
  padding: 9px 18px;
  margin: 0 0 18px;
  font-size: inherit;
  border-left: 5px solid #eeeeee;
}
blockquote p:last-child,
blockquote ul:last-child,
blockquote ol:last-child {
  margin-bottom: 0;
}
blockquote footer,
blockquote small,
blockquote .small {
  display: block;
  font-size: 80%;
  line-height: 1.42857143;
  color: #777777;
}
blockquote footer:before,
blockquote small:before,
blockquote .small:before {
  content: '\2014 \00A0';
}
.blockquote-reverse,
blockquote.pull-right {
  padding-right: 15px;
  padding-left: 0;
  border-right: 5px solid #eeeeee;
  border-left: 0;
  text-align: right;
}
.blockquote-reverse footer:before,
blockquote.pull-right footer:before,
.blockquote-reverse small:before,
blockquote.pull-right small:before,
.blockquote-reverse .small:before,
blockquote.pull-right .small:before {
  content: '';
}
.blockquote-reverse footer:after,
blockquote.pull-right footer:after,
.blockquote-reverse small:after,
blockquote.pull-right small:after,
.blockquote-reverse .small:after,
blockquote.pull-right .small:after {
  content: '\00A0 \2014';
}
address {
  margin-bottom: 18px;
  font-style: normal;
  line-height: 1.42857143;
}
code,
kbd,
pre,
samp {
  font-family: monospace;
}
code {
  padding: 2px 4px;
  font-size: 90%;
  color: #c7254e;
  background-color: #f9f2f4;
  border-radius: 2px;
}
kbd {
  padding: 2px 4px;
  font-size: 90%;
  color: #888;
  background-color: transparent;
  border-radius: 1px;
  box-shadow: inset 0 -1px 0 rgba(0, 0, 0, 0.25);
}
kbd kbd {
  padding: 0;
  font-size: 100%;
  font-weight: bold;
  box-shadow: none;
}
pre {
  display: block;
  padding: 8.5px;
  margin: 0 0 9px;
  font-size: 12px;
  line-height: 1.42857143;
  word-break: break-all;
  word-wrap: break-word;
  color: #333333;
  background-color: #f5f5f5;
  border: 1px solid #ccc;
  border-radius: 2px;
}
pre code {
  padding: 0;
  font-size: inherit;
  color: inherit;
  white-space: pre-wrap;
  background-color: transparent;
  border-radius: 0;
}
.pre-scrollable {
  max-height: 340px;
  overflow-y: scroll;
}
.container {
  margin-right: auto;
  margin-left: auto;
  padding-left: 0px;
  padding-right: 0px;
}
@media (min-width: 768px) {
  .container {
    width: 768px;
  }
}
@media (min-width: 992px) {
  .container {
    width: 940px;
  }
}
@media (min-width: 1200px) {
  .container {
    width: 1140px;
  }
}
.container-fluid {
  margin-right: auto;
  margin-left: auto;
  padding-left: 0px;
  padding-right: 0px;
}
.row {
  margin-left: 0px;
  margin-right: 0px;
}
.col-xs-1, .col-sm-1, .col-md-1, .col-lg-1, .col-xs-2, .col-sm-2, .col-md-2, .col-lg-2, .col-xs-3, .col-sm-3, .col-md-3, .col-lg-3, .col-xs-4, .col-sm-4, .col-md-4, .col-lg-4, .col-xs-5, .col-sm-5, .col-md-5, .col-lg-5, .col-xs-6, .col-sm-6, .col-md-6, .col-lg-6, .col-xs-7, .col-sm-7, .col-md-7, .col-lg-7, .col-xs-8, .col-sm-8, .col-md-8, .col-lg-8, .col-xs-9, .col-sm-9, .col-md-9, .col-lg-9, .col-xs-10, .col-sm-10, .col-md-10, .col-lg-10, .col-xs-11, .col-sm-11, .col-md-11, .col-lg-11, .col-xs-12, .col-sm-12, .col-md-12, .col-lg-12 {
  position: relative;
  min-height: 1px;
  padding-left: 0px;
  padding-right: 0px;
}
.col-xs-1, .col-xs-2, .col-xs-3, .col-xs-4, .col-xs-5, .col-xs-6, .col-xs-7, .col-xs-8, .col-xs-9, .col-xs-10, .col-xs-11, .col-xs-12 {
  float: left;
}
.col-xs-12 {
  width: 100%;
}
.col-xs-11 {
  width: 91.66666667%;
}
.col-xs-10 {
  width: 83.33333333%;
}
.col-xs-9 {
  width: 75%;
}
.col-xs-8 {
  width: 66.66666667%;
}
.col-xs-7 {
  width: 58.33333333%;
}
.col-xs-6 {
  width: 50%;
}
.col-xs-5 {
  width: 41.66666667%;
}
.col-xs-4 {
  width: 33.33333333%;
}
.col-xs-3 {
  width: 25%;
}
.col-xs-2 {
  width: 16.66666667%;
}
.col-xs-1 {
  width: 8.33333333%;
}
.col-xs-pull-12 {
  right: 100%;
}
.col-xs-pull-11 {
  right: 91.66666667%;
}
.col-xs-pull-10 {
  right: 83.33333333%;
}
.col-xs-pull-9 {
  right: 75%;
}
.col-xs-pull-8 {
  right: 66.66666667%;
}
.col-xs-pull-7 {
  right: 58.33333333%;
}
.col-xs-pull-6 {
  right: 50%;
}
.col-xs-pull-5 {
  right: 41.66666667%;
}
.col-xs-pull-4 {
  right: 33.33333333%;
}
.col-xs-pull-3 {
  right: 25%;
}
.col-xs-pull-2 {
  right: 16.66666667%;
}
.col-xs-pull-1 {
  right: 8.33333333%;
}
.col-xs-pull-0 {
  right: auto;
}
.col-xs-push-12 {
  left: 100%;
}
.col-xs-push-11 {
  left: 91.66666667%;
}
.col-xs-push-10 {
  left: 83.33333333%;
}
.col-xs-push-9 {
  left: 75%;
}
.col-xs-push-8 {
  left: 66.66666667%;
}
.col-xs-push-7 {
  left: 58.33333333%;
}
.col-xs-push-6 {
  left: 50%;
}
.col-xs-push-5 {
  left: 41.66666667%;
}
.col-xs-push-4 {
  left: 33.33333333%;
}
.col-xs-push-3 {
  left: 25%;
}
.col-xs-push-2 {
  left: 16.66666667%;
}
.col-xs-push-1 {
  left: 8.33333333%;
}
.col-xs-push-0 {
  left: auto;
}
.col-xs-offset-12 {
  margin-left: 100%;
}
.col-xs-offset-11 {
  margin-left: 91.66666667%;
}
.col-xs-offset-10 {
  margin-left: 83.33333333%;
}
.col-xs-offset-9 {
  margin-left: 75%;
}
.col-xs-offset-8 {
  margin-left: 66.66666667%;
}
.col-xs-offset-7 {
  margin-left: 58.33333333%;
}
.col-xs-offset-6 {
  margin-left: 50%;
}
.col-xs-offset-5 {
  margin-left: 41.66666667%;
}
.col-xs-offset-4 {
  margin-left: 33.33333333%;
}
.col-xs-offset-3 {
  margin-left: 25%;
}
.col-xs-offset-2 {
  margin-left: 16.66666667%;
}
.col-xs-offset-1 {
  margin-left: 8.33333333%;
}
.col-xs-offset-0 {
  margin-left: 0%;
}
@media (min-width: 768px) {
  .col-sm-1, .col-sm-2, .col-sm-3, .col-sm-4, .col-sm-5, .col-sm-6, .col-sm-7, .col-sm-8, .col-sm-9, .col-sm-10, .col-sm-11, .col-sm-12 {
    float: left;
  }
  .col-sm-12 {
    width: 100%;
  }
  .col-sm-11 {
    width: 91.66666667%;
  }
  .col-sm-10 {
    width: 83.33333333%;
  }
  .col-sm-9 {
    width: 75%;
  }
  .col-sm-8 {
    width: 66.66666667%;
  }
  .col-sm-7 {
    width: 58.33333333%;
  }
  .col-sm-6 {
    width: 50%;
  }
  .col-sm-5 {
    width: 41.66666667%;
  }
  .col-sm-4 {
    width: 33.33333333%;
  }
  .col-sm-3 {
    width: 25%;
  }
  .col-sm-2 {
    width: 16.66666667%;
  }
  .col-sm-1 {
    width: 8.33333333%;
  }
  .col-sm-pull-12 {
    right: 100%;
  }
  .col-sm-pull-11 {
    right: 91.66666667%;
  }
  .col-sm-pull-10 {
    right: 83.33333333%;
  }
  .col-sm-pull-9 {
    right: 75%;
  }
  .col-sm-pull-8 {
    right: 66.66666667%;
  }
  .col-sm-pull-7 {
    right: 58.33333333%;
  }
  .col-sm-pull-6 {
    right: 50%;
  }
  .col-sm-pull-5 {
    right: 41.66666667%;
  }
  .col-sm-pull-4 {
    right: 33.33333333%;
  }
  .col-sm-pull-3 {
    right: 25%;
  }
  .col-sm-pull-2 {
    right: 16.66666667%;
  }
  .col-sm-pull-1 {
    right: 8.33333333%;
  }
  .col-sm-pull-0 {
    right: auto;
  }
  .col-sm-push-12 {
    left: 100%;
  }
  .col-sm-push-11 {
    left: 91.66666667%;
  }
  .col-sm-push-10 {
    left: 83.33333333%;
  }
  .col-sm-push-9 {
    left: 75%;
  }
  .col-sm-push-8 {
    left: 66.66666667%;
  }
  .col-sm-push-7 {
    left: 58.33333333%;
  }
  .col-sm-push-6 {
    left: 50%;
  }
  .col-sm-push-5 {
    left: 41.66666667%;
  }
  .col-sm-push-4 {
    left: 33.33333333%;
  }
  .col-sm-push-3 {
    left: 25%;
  }
  .col-sm-push-2 {
    left: 16.66666667%;
  }
  .col-sm-push-1 {
    left: 8.33333333%;
  }
  .col-sm-push-0 {
    left: auto;
  }
  .col-sm-offset-12 {
    margin-left: 100%;
  }
  .col-sm-offset-11 {
    margin-left: 91.66666667%;
  }
  .col-sm-offset-10 {
    margin-left: 83.33333333%;
  }
  .col-sm-offset-9 {
    margin-left: 75%;
  }
  .col-sm-offset-8 {
    margin-left: 66.66666667%;
  }
  .col-sm-offset-7 {
    margin-left: 58.33333333%;
  }
  .col-sm-offset-6 {
    margin-left: 50%;
  }
  .col-sm-offset-5 {
    margin-left: 41.66666667%;
  }
  .col-sm-offset-4 {
    margin-left: 33.33333333%;
  }
  .col-sm-offset-3 {
    margin-left: 25%;
  }
  .col-sm-offset-2 {
    margin-left: 16.66666667%;
  }
  .col-sm-offset-1 {
    margin-left: 8.33333333%;
  }
  .col-sm-offset-0 {
    margin-left: 0%;
  }
}
@media (min-width: 992px) {
  .col-md-1, .col-md-2, .col-md-3, .col-md-4, .col-md-5, .col-md-6, .col-md-7, .col-md-8, .col-md-9, .col-md-10, .col-md-11, .col-md-12 {
    float: left;
  }
  .col-md-12 {
    width: 100%;
  }
  .col-md-11 {
    width: 91.66666667%;
  }
  .col-md-10 {
    width: 83.33333333%;
  }
  .col-md-9 {
    width: 75%;
  }
  .col-md-8 {
    width: 66.66666667%;
  }
  .col-md-7 {
    width: 58.33333333%;
  }
  .col-md-6 {
    width: 50%;
  }
  .col-md-5 {
    width: 41.66666667%;
  }
  .col-md-4 {
    width: 33.33333333%;
  }
  .col-md-3 {
    width: 25%;
  }
  .col-md-2 {
    width: 16.66666667%;
  }
  .col-md-1 {
    width: 8.33333333%;
  }
  .col-md-pull-12 {
    right: 100%;
  }
  .col-md-pull-11 {
    right: 91.66666667%;
  }
  .col-md-pull-10 {
    right: 83.33333333%;
  }
  .col-md-pull-9 {
    right: 75%;
  }
  .col-md-pull-8 {
    right: 66.66666667%;
  }
  .col-md-pull-7 {
    right: 58.33333333%;
  }
  .col-md-pull-6 {
    right: 50%;
  }
  .col-md-pull-5 {
    right: 41.66666667%;
  }
  .col-md-pull-4 {
    right: 33.33333333%;
  }
  .col-md-pull-3 {
    right: 25%;
  }
  .col-md-pull-2 {
    right: 16.66666667%;
  }
  .col-md-pull-1 {
    right: 8.33333333%;
  }
  .col-md-pull-0 {
    right: auto;
  }
  .col-md-push-12 {
    left: 100%;
  }
  .col-md-push-11 {
    left: 91.66666667%;
  }
  .col-md-push-10 {
    left: 83.33333333%;
  }
  .col-md-push-9 {
    left: 75%;
  }
  .col-md-push-8 {
    left: 66.66666667%;
  }
  .col-md-push-7 {
    left: 58.33333333%;
  }
  .col-md-push-6 {
    left: 50%;
  }
  .col-md-push-5 {
    left: 41.66666667%;
  }
  .col-md-push-4 {
    left: 33.33333333%;
  }
  .col-md-push-3 {
    left: 25%;
  }
  .col-md-push-2 {
    left: 16.66666667%;
  }
  .col-md-push-1 {
    left: 8.33333333%;
  }
  .col-md-push-0 {
    left: auto;
  }
  .col-md-offset-12 {
    margin-left: 100%;
  }
  .col-md-offset-11 {
    margin-left: 91.66666667%;
  }
  .col-md-offset-10 {
    margin-left: 83.33333333%;
  }
  .col-md-offset-9 {
    margin-left: 75%;
  }
  .col-md-offset-8 {
    margin-left: 66.66666667%;
  }
  .col-md-offset-7 {
    margin-left: 58.33333333%;
  }
  .col-md-offset-6 {
    margin-left: 50%;
  }
  .col-md-offset-5 {
    margin-left: 41.66666667%;
  }
  .col-md-offset-4 {
    margin-left: 33.33333333%;
  }
  .col-md-offset-3 {
    margin-left: 25%;
  }
  .col-md-offset-2 {
    margin-left: 16.66666667%;
  }
  .col-md-offset-1 {
    margin-left: 8.33333333%;
  }
  .col-md-offset-0 {
    margin-left: 0%;
  }
}
@media (min-width: 1200px) {
  .col-lg-1, .col-lg-2, .col-lg-3, .col-lg-4, .col-lg-5, .col-lg-6, .col-lg-7, .col-lg-8, .col-lg-9, .col-lg-10, .col-lg-11, .col-lg-12 {
    float: left;
  }
  .col-lg-12 {
    width: 100%;
  }
  .col-lg-11 {
    width: 91.66666667%;
  }
  .col-lg-10 {
    width: 83.33333333%;
  }
  .col-lg-9 {
    width: 75%;
  }
  .col-lg-8 {
    width: 66.66666667%;
  }
  .col-lg-7 {
    width: 58.33333333%;
  }
  .col-lg-6 {
    width: 50%;
  }
  .col-lg-5 {
    width: 41.66666667%;
  }
  .col-lg-4 {
    width: 33.33333333%;
  }
  .col-lg-3 {
    width: 25%;
  }
  .col-lg-2 {
    width: 16.66666667%;
  }
  .col-lg-1 {
    width: 8.33333333%;
  }
  .col-lg-pull-12 {
    right: 100%;
  }
  .col-lg-pull-11 {
    right: 91.66666667%;
  }
  .col-lg-pull-10 {
    right: 83.33333333%;
  }
  .col-lg-pull-9 {
    right: 75%;
  }
  .col-lg-pull-8 {
    right: 66.66666667%;
  }
  .col-lg-pull-7 {
    right: 58.33333333%;
  }
  .col-lg-pull-6 {
    right: 50%;
  }
  .col-lg-pull-5 {
    right: 41.66666667%;
  }
  .col-lg-pull-4 {
    right: 33.33333333%;
  }
  .col-lg-pull-3 {
    right: 25%;
  }
  .col-lg-pull-2 {
    right: 16.66666667%;
  }
  .col-lg-pull-1 {
    right: 8.33333333%;
  }
  .col-lg-pull-0 {
    right: auto;
  }
  .col-lg-push-12 {
    left: 100%;
  }
  .col-lg-push-11 {
    left: 91.66666667%;
  }
  .col-lg-push-10 {
    left: 83.33333333%;
  }
  .col-lg-push-9 {
    left: 75%;
  }
  .col-lg-push-8 {
    left: 66.66666667%;
  }
  .col-lg-push-7 {
    left: 58.33333333%;
  }
  .col-lg-push-6 {
    left: 50%;
  }
  .col-lg-push-5 {
    left: 41.66666667%;
  }
  .col-lg-push-4 {
    left: 33.33333333%;
  }
  .col-lg-push-3 {
    left: 25%;
  }
  .col-lg-push-2 {
    left: 16.66666667%;
  }
  .col-lg-push-1 {
    left: 8.33333333%;
  }
  .col-lg-push-0 {
    left: auto;
  }
  .col-lg-offset-12 {
    margin-left: 100%;
  }
  .col-lg-offset-11 {
    margin-left: 91.66666667%;
  }
  .col-lg-offset-10 {
    margin-left: 83.33333333%;
  }
  .col-lg-offset-9 {
    margin-left: 75%;
  }
  .col-lg-offset-8 {
    margin-left: 66.66666667%;
  }
  .col-lg-offset-7 {
    margin-left: 58.33333333%;
  }
  .col-lg-offset-6 {
    margin-left: 50%;
  }
  .col-lg-offset-5 {
    margin-left: 41.66666667%;
  }
  .col-lg-offset-4 {
    margin-left: 33.33333333%;
  }
  .col-lg-offset-3 {
    margin-left: 25%;
  }
  .col-lg-offset-2 {
    margin-left: 16.66666667%;
  }
  .col-lg-offset-1 {
    margin-left: 8.33333333%;
  }
  .col-lg-offset-0 {
    margin-left: 0%;
  }
}
table {
  background-color: transparent;
}
caption {
  padding-top: 8px;
  padding-bottom: 8px;
  color: #777777;
  text-align: left;
}
th {
  text-align: left;
}
.table {
  width: 100%;
  max-width: 100%;
  margin-bottom: 18px;
}
.table > thead > tr > th,
.table > tbody > tr > th,
.table > tfoot > tr > th,
.table > thead > tr > td,
.table > tbody > tr > td,
.table > tfoot > tr > td {
  padding: 8px;
  line-height: 1.42857143;
  vertical-align: top;
  border-top: 1px solid #ddd;
}
.table > thead > tr > th {
  vertical-align: bottom;
  border-bottom: 2px solid #ddd;
}
.table > caption + thead > tr:first-child > th,
.table > colgroup + thead > tr:first-child > th,
.table > thead:first-child > tr:first-child > th,
.table > caption + thead > tr:first-child > td,
.table > colgroup + thead > tr:first-child > td,
.table > thead:first-child > tr:first-child > td {
  border-top: 0;
}
.table > tbody + tbody {
  border-top: 2px solid #ddd;
}
.table .table {
  background-color: #fff;
}
.table-condensed > thead > tr > th,
.table-condensed > tbody > tr > th,
.table-condensed > tfoot > tr > th,
.table-condensed > thead > tr > td,
.table-condensed > tbody > tr > td,
.table-condensed > tfoot > tr > td {
  padding: 5px;
}
.table-bordered {
  border: 1px solid #ddd;
}
.table-bordered > thead > tr > th,
.table-bordered > tbody > tr > th,
.table-bordered > tfoot > tr > th,
.table-bordered > thead > tr > td,
.table-bordered > tbody > tr > td,
.table-bordered > tfoot > tr > td {
  border: 1px solid #ddd;
}
.table-bordered > thead > tr > th,
.table-bordered > thead > tr > td {
  border-bottom-width: 2px;
}
.table-striped > tbody > tr:nth-of-type(odd) {
  background-color: #f9f9f9;
}
.table-hover > tbody > tr:hover {
  background-color: #f5f5f5;
}
table col[class*="col-"] {
  position: static;
  float: none;
  display: table-column;
}
table td[class*="col-"],
table th[class*="col-"] {
  position: static;
  float: none;
  display: table-cell;
}
.table > thead > tr > td.active,
.table > tbody > tr > td.active,
.table > tfoot > tr > td.active,
.table > thead > tr > th.active,
.table > tbody > tr > th.active,
.table > tfoot > tr > th.active,
.table > thead > tr.active > td,
.table > tbody > tr.active > td,
.table > tfoot > tr.active > td,
.table > thead > tr.active > th,
.table > tbody > tr.active > th,
.table > tfoot > tr.active > th {
  background-color: #f5f5f5;
}
.table-hover > tbody > tr > td.active:hover,
.table-hover > tbody > tr > th.active:hover,
.table-hover > tbody > tr.active:hover > td,
.table-hover > tbody > tr:hover > .active,
.table-hover > tbody > tr.active:hover > th {
  background-color: #e8e8e8;
}
.table > thead > tr > td.success,
.table > tbody > tr > td.success,
.table > tfoot > tr > td.success,
.table > thead > tr > th.success,
.table > tbody > tr > th.success,
.table > tfoot > tr > th.success,
.table > thead > tr.success > td,
.table > tbody > tr.success > td,
.table > tfoot > tr.success > td,
.table > thead > tr.success > th,
.table > tbody > tr.success > th,
.table > tfoot > tr.success > th {
  background-color: #dff0d8;
}
.table-hover > tbody > tr > td.success:hover,
.table-hover > tbody > tr > th.success:hover,
.table-hover > tbody > tr.success:hover > td,
.table-hover > tbody > tr:hover > .success,
.table-hover > tbody > tr.success:hover > th {
  background-color: #d0e9c6;
}
.table > thead > tr > td.info,
.table > tbody > tr > td.info,
.table > tfoot > tr > td.info,
.table > thead > tr > th.info,
.table > tbody > tr > th.info,
.table > tfoot > tr > th.info,
.table > thead > tr.info > td,
.table > tbody > tr.info > td,
.table > tfoot > tr.info > td,
.table > thead > tr.info > th,
.table > tbody > tr.info > th,
.table > tfoot > tr.info > th {
  background-color: #d9edf7;
}
.table-hover > tbody > tr > td.info:hover,
.table-hover > tbody > tr > th.info:hover,
.table-hover > tbody > tr.info:hover > td,
.table-hover > tbody > tr:hover > .info,
.table-hover > tbody > tr.info:hover > th {
  background-color: #c4e3f3;
}
.table > thead > tr > td.warning,
.table > tbody > tr > td.warning,
.table > tfoot > tr > td.warning,
.table > thead > tr > th.warning,
.table > tbody > tr > th.warning,
.table > tfoot > tr > th.warning,
.table > thead > tr.warning > td,
.table > tbody > tr.warning > td,
.table > tfoot > tr.warning > td,
.table > thead > tr.warning > th,
.table > tbody > tr.warning > th,
.table > tfoot > tr.warning > th {
  background-color: #fcf8e3;
}
.table-hover > tbody > tr > td.warning:hover,
.table-hover > tbody > tr > th.warning:hover,
.table-hover > tbody > tr.warning:hover > td,
.table-hover > tbody > tr:hover > .warning,
.table-hover > tbody > tr.warning:hover > th {
  background-color: #faf2cc;
}
.table > thead > tr > td.danger,
.table > tbody > tr > td.danger,
.table > tfoot > tr > td.danger,
.table > thead > tr > th.danger,
.table > tbody > tr > th.danger,
.table > tfoot > tr > th.danger,
.table > thead > tr.danger > td,
.table > tbody > tr.danger > td,
.table > tfoot > tr.danger > td,
.table > thead > tr.danger > th,
.table > tbody > tr.danger > th,
.table > tfoot > tr.danger > th {
  background-color: #f2dede;
}
.table-hover > tbody > tr > td.danger:hover,
.table-hover > tbody > tr > th.danger:hover,
.table-hover > tbody > tr.danger:hover > td,
.table-hover > tbody > tr:hover > .danger,
.table-hover > tbody > tr.danger:hover > th {
  background-color: #ebcccc;
}
.table-responsive {
  overflow-x: auto;
  min-height: 0.01%;
}
@media screen and (max-width: 767px) {
  .table-responsive {
    width: 100%;
    margin-bottom: 13.5px;
    overflow-y: hidden;
    -ms-overflow-style: -ms-autohiding-scrollbar;
    border: 1px solid #ddd;
  }
  .table-responsive > .table {
    margin-bottom: 0;
  }
  .table-responsive > .table > thead > tr > th,
  .table-responsive > .table > tbody > tr > th,
  .table-responsive > .table > tfoot > tr > th,
  .table-responsive > .table > thead > tr > td,
  .table-responsive > .table > tbody > tr > td,
  .table-responsive > .table > tfoot > tr > td {
    white-space: nowrap;
  }
  .table-responsive > .table-bordered {
    border: 0;
  }
  .table-responsive > .table-bordered > thead > tr > th:first-child,
  .table-responsive > .table-bordered > tbody > tr > th:first-child,
  .table-responsive > .table-bordered > tfoot > tr > th:first-child,
  .table-responsive > .table-bordered > thead > tr > td:first-child,
  .table-responsive > .table-bordered > tbody > tr > td:first-child,
  .table-responsive > .table-bordered > tfoot > tr > td:first-child {
    border-left: 0;
  }
  .table-responsive > .table-bordered > thead > tr > th:last-child,
  .table-responsive > .table-bordered > tbody > tr > th:last-child,
  .table-responsive > .table-bordered > tfoot > tr > th:last-child,
  .table-responsive > .table-bordered > thead > tr > td:last-child,
  .table-responsive > .table-bordered > tbody > tr > td:last-child,
  .table-responsive > .table-bordered > tfoot > tr > td:last-child {
    border-right: 0;
  }
  .table-responsive > .table-bordered > tbody > tr:last-child > th,
  .table-responsive > .table-bordered > tfoot > tr:last-child > th,
  .table-responsive > .table-bordered > tbody > tr:last-child > td,
  .table-responsive > .table-bordered > tfoot > tr:last-child > td {
    border-bottom: 0;
  }
}
fieldset {
  padding: 0;
  margin: 0;
  border: 0;
  min-width: 0;
}
legend {
  display: block;
  width: 100%;
  padding: 0;
  margin-bottom: 18px;
  font-size: 19.5px;
  line-height: inherit;
  color: #333333;
  border: 0;
  border-bottom: 1px solid #e5e5e5;
}
label {
  display: inline-block;
  max-width: 100%;
  margin-bottom: 5px;
  font-weight: bold;
}
input[type="search"] {
  -webkit-box-sizing: border-box;
  -moz-box-sizing: border-box;
  box-sizing: border-box;
}
input[type="radio"],
input[type="checkbox"] {
  margin: 4px 0 0;
  margin-top: 1px \9;
  line-height: normal;
}
input[type="file"] {
  display: block;
}
input[type="range"] {
  display: block;
  width: 100%;
}
select[multiple],
select[size] {
  height: auto;
}
input[type="file"]:focus,
input[type="radio"]:focus,
input[type="checkbox"]:focus {
  outline: 5px auto -webkit-focus-ring-color;
  outline-offset: -2px;
}
output {
  display: block;
  padding-top: 7px;
  font-size: 13px;
  line-height: 1.42857143;
  color: #555555;
}
.form-control {
  display: block;
  width: 100%;
  height: 32px;
  padding: 6px 12px;
  font-size: 13px;
  line-height: 1.42857143;
  color: #555555;
  background-color: #fff;
  background-image: none;
  border: 1px solid #ccc;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  -webkit-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  -o-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
}
.form-control:focus {
  border-color: #66afe9;
  outline: 0;
  -webkit-box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
  box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
}
.form-control::-moz-placeholder {
  color: #999;
  opacity: 1;
}
.form-control:-ms-input-placeholder {
  color: #999;
}
.form-control::-webkit-input-placeholder {
  color: #999;
}
.form-control::-ms-expand {
  border: 0;
  background-color: transparent;
}
.form-control[disabled],
.form-control[readonly],
fieldset[disabled] .form-control {
  background-color: #eeeeee;
  opacity: 1;
}
.form-control[disabled],
fieldset[disabled] .form-control {
  cursor: not-allowed;
}
textarea.form-control {
  height: auto;
}
input[type="search"] {
  -webkit-appearance: none;
}
@media screen and (-webkit-min-device-pixel-ratio: 0) {
  input[type="date"].form-control,
  input[type="time"].form-control,
  input[type="datetime-local"].form-control,
  input[type="month"].form-control {
    line-height: 32px;
  }
  input[type="date"].input-sm,
  input[type="time"].input-sm,
  input[type="datetime-local"].input-sm,
  input[type="month"].input-sm,
  .input-group-sm input[type="date"],
  .input-group-sm input[type="time"],
  .input-group-sm input[type="datetime-local"],
  .input-group-sm input[type="month"] {
    line-height: 30px;
  }
  input[type="date"].input-lg,
  input[type="time"].input-lg,
  input[type="datetime-local"].input-lg,
  input[type="month"].input-lg,
  .input-group-lg input[type="date"],
  .input-group-lg input[type="time"],
  .input-group-lg input[type="datetime-local"],
  .input-group-lg input[type="month"] {
    line-height: 45px;
  }
}
.form-group {
  margin-bottom: 15px;
}
.radio,
.checkbox {
  position: relative;
  display: block;
  margin-top: 10px;
  margin-bottom: 10px;
}
.radio label,
.checkbox label {
  min-height: 18px;
  padding-left: 20px;
  margin-bottom: 0;
  font-weight: normal;
  cursor: pointer;
}
.radio input[type="radio"],
.radio-inline input[type="radio"],
.checkbox input[type="checkbox"],
.checkbox-inline input[type="checkbox"] {
  position: absolute;
  margin-left: -20px;
  margin-top: 4px \9;
}
.radio + .radio,
.checkbox + .checkbox {
  margin-top: -5px;
}
.radio-inline,
.checkbox-inline {
  position: relative;
  display: inline-block;
  padding-left: 20px;
  margin-bottom: 0;
  vertical-align: middle;
  font-weight: normal;
  cursor: pointer;
}
.radio-inline + .radio-inline,
.checkbox-inline + .checkbox-inline {
  margin-top: 0;
  margin-left: 10px;
}
input[type="radio"][disabled],
input[type="checkbox"][disabled],
input[type="radio"].disabled,
input[type="checkbox"].disabled,
fieldset[disabled] input[type="radio"],
fieldset[disabled] input[type="checkbox"] {
  cursor: not-allowed;
}
.radio-inline.disabled,
.checkbox-inline.disabled,
fieldset[disabled] .radio-inline,
fieldset[disabled] .checkbox-inline {
  cursor: not-allowed;
}
.radio.disabled label,
.checkbox.disabled label,
fieldset[disabled] .radio label,
fieldset[disabled] .checkbox label {
  cursor: not-allowed;
}
.form-control-static {
  padding-top: 7px;
  padding-bottom: 7px;
  margin-bottom: 0;
  min-height: 31px;
}
.form-control-static.input-lg,
.form-control-static.input-sm {
  padding-left: 0;
  padding-right: 0;
}
.input-sm {
  height: 30px;
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
}
select.input-sm {
  height: 30px;
  line-height: 30px;
}
textarea.input-sm,
select[multiple].input-sm {
  height: auto;
}
.form-group-sm .form-control {
  height: 30px;
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
}
.form-group-sm select.form-control {
  height: 30px;
  line-height: 30px;
}
.form-group-sm textarea.form-control,
.form-group-sm select[multiple].form-control {
  height: auto;
}
.form-group-sm .form-control-static {
  height: 30px;
  min-height: 30px;
  padding: 6px 10px;
  font-size: 12px;
  line-height: 1.5;
}
.input-lg {
  height: 45px;
  padding: 10px 16px;
  font-size: 17px;
  line-height: 1.3333333;
  border-radius: 3px;
}
select.input-lg {
  height: 45px;
  line-height: 45px;
}
textarea.input-lg,
select[multiple].input-lg {
  height: auto;
}
.form-group-lg .form-control {
  height: 45px;
  padding: 10px 16px;
  font-size: 17px;
  line-height: 1.3333333;
  border-radius: 3px;
}
.form-group-lg select.form-control {
  height: 45px;
  line-height: 45px;
}
.form-group-lg textarea.form-control,
.form-group-lg select[multiple].form-control {
  height: auto;
}
.form-group-lg .form-control-static {
  height: 45px;
  min-height: 35px;
  padding: 11px 16px;
  font-size: 17px;
  line-height: 1.3333333;
}
.has-feedback {
  position: relative;
}
.has-feedback .form-control {
  padding-right: 40px;
}
.form-control-feedback {
  position: absolute;
  top: 0;
  right: 0;
  z-index: 2;
  display: block;
  width: 32px;
  height: 32px;
  line-height: 32px;
  text-align: center;
  pointer-events: none;
}
.input-lg + .form-control-feedback,
.input-group-lg + .form-control-feedback,
.form-group-lg .form-control + .form-control-feedback {
  width: 45px;
  height: 45px;
  line-height: 45px;
}
.input-sm + .form-control-feedback,
.input-group-sm + .form-control-feedback,
.form-group-sm .form-control + .form-control-feedback {
  width: 30px;
  height: 30px;
  line-height: 30px;
}
.has-success .help-block,
.has-success .control-label,
.has-success .radio,
.has-success .checkbox,
.has-success .radio-inline,
.has-success .checkbox-inline,
.has-success.radio label,
.has-success.checkbox label,
.has-success.radio-inline label,
.has-success.checkbox-inline label {
  color: #3c763d;
}
.has-success .form-control {
  border-color: #3c763d;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
}
.has-success .form-control:focus {
  border-color: #2b542c;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #67b168;
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #67b168;
}
.has-success .input-group-addon {
  color: #3c763d;
  border-color: #3c763d;
  background-color: #dff0d8;
}
.has-success .form-control-feedback {
  color: #3c763d;
}
.has-warning .help-block,
.has-warning .control-label,
.has-warning .radio,
.has-warning .checkbox,
.has-warning .radio-inline,
.has-warning .checkbox-inline,
.has-warning.radio label,
.has-warning.checkbox label,
.has-warning.radio-inline label,
.has-warning.checkbox-inline label {
  color: #8a6d3b;
}
.has-warning .form-control {
  border-color: #8a6d3b;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
}
.has-warning .form-control:focus {
  border-color: #66512c;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #c0a16b;
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #c0a16b;
}
.has-warning .input-group-addon {
  color: #8a6d3b;
  border-color: #8a6d3b;
  background-color: #fcf8e3;
}
.has-warning .form-control-feedback {
  color: #8a6d3b;
}
.has-error .help-block,
.has-error .control-label,
.has-error .radio,
.has-error .checkbox,
.has-error .radio-inline,
.has-error .checkbox-inline,
.has-error.radio label,
.has-error.checkbox label,
.has-error.radio-inline label,
.has-error.checkbox-inline label {
  color: #a94442;
}
.has-error .form-control {
  border-color: #a94442;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
}
.has-error .form-control:focus {
  border-color: #843534;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #ce8483;
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #ce8483;
}
.has-error .input-group-addon {
  color: #a94442;
  border-color: #a94442;
  background-color: #f2dede;
}
.has-error .form-control-feedback {
  color: #a94442;
}
.has-feedback label ~ .form-control-feedback {
  top: 23px;
}
.has-feedback label.sr-only ~ .form-control-feedback {
  top: 0;
}
.help-block {
  display: block;
  margin-top: 5px;
  margin-bottom: 10px;
  color: #404040;
}
@media (min-width: 768px) {
  .form-inline .form-group {
    display: inline-block;
    margin-bottom: 0;
    vertical-align: middle;
  }
  .form-inline .form-control {
    display: inline-block;
    width: auto;
    vertical-align: middle;
  }
  .form-inline .form-control-static {
    display: inline-block;
  }
  .form-inline .input-group {
    display: inline-table;
    vertical-align: middle;
  }
  .form-inline .input-group .input-group-addon,
  .form-inline .input-group .input-group-btn,
  .form-inline .input-group .form-control {
    width: auto;
  }
  .form-inline .input-group > .form-control {
    width: 100%;
  }
  .form-inline .control-label {
    margin-bottom: 0;
    vertical-align: middle;
  }
  .form-inline .radio,
  .form-inline .checkbox {
    display: inline-block;
    margin-top: 0;
    margin-bottom: 0;
    vertical-align: middle;
  }
  .form-inline .radio label,
  .form-inline .checkbox label {
    padding-left: 0;
  }
  .form-inline .radio input[type="radio"],
  .form-inline .checkbox input[type="checkbox"] {
    position: relative;
    margin-left: 0;
  }
  .form-inline .has-feedback .form-control-feedback {
    top: 0;
  }
}
.form-horizontal .radio,
.form-horizontal .checkbox,
.form-horizontal .radio-inline,
.form-horizontal .checkbox-inline {
  margin-top: 0;
  margin-bottom: 0;
  padding-top: 7px;
}
.form-horizontal .radio,
.form-horizontal .checkbox {
  min-height: 25px;
}
.form-horizontal .form-group {
  margin-left: 0px;
  margin-right: 0px;
}
@media (min-width: 768px) {
  .form-horizontal .control-label {
    text-align: right;
    margin-bottom: 0;
    padding-top: 7px;
  }
}
.form-horizontal .has-feedback .form-control-feedback {
  right: 0px;
}
@media (min-width: 768px) {
  .form-horizontal .form-group-lg .control-label {
    padding-top: 11px;
    font-size: 17px;
  }
}
@media (min-width: 768px) {
  .form-horizontal .form-group-sm .control-label {
    padding-top: 6px;
    font-size: 12px;
  }
}
.btn {
  display: inline-block;
  margin-bottom: 0;
  font-weight: normal;
  text-align: center;
  vertical-align: middle;
  touch-action: manipulation;
  cursor: pointer;
  background-image: none;
  border: 1px solid transparent;
  white-space: nowrap;
  padding: 6px 12px;
  font-size: 13px;
  line-height: 1.42857143;
  border-radius: 2px;
  -webkit-user-select: none;
  -moz-user-select: none;
  -ms-user-select: none;
  user-select: none;
}
.btn:focus,
.btn:active:focus,
.btn.active:focus,
.btn.focus,
.btn:active.focus,
.btn.active.focus {
  outline: 5px auto -webkit-focus-ring-color;
  outline-offset: -2px;
}
.btn:hover,
.btn:focus,
.btn.focus {
  color: #333;
  text-decoration: none;
}
.btn:active,
.btn.active {
  outline: 0;
  background-image: none;
  -webkit-box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);
  box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);
}
.btn.disabled,
.btn[disabled],
fieldset[disabled] .btn {
  cursor: not-allowed;
  opacity: 0.65;
  filter: alpha(opacity=65);
  -webkit-box-shadow: none;
  box-shadow: none;
}
a.btn.disabled,
fieldset[disabled] a.btn {
  pointer-events: none;
}
.btn-default {
  color: #333;
  background-color: #fff;
  border-color: #ccc;
}
.btn-default:focus,
.btn-default.focus {
  color: #333;
  background-color: #e6e6e6;
  border-color: #8c8c8c;
}
.btn-default:hover {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
.btn-default:active,
.btn-default.active,
.open > .dropdown-toggle.btn-default {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
.btn-default:active:hover,
.btn-default.active:hover,
.open > .dropdown-toggle.btn-default:hover,
.btn-default:active:focus,
.btn-default.active:focus,
.open > .dropdown-toggle.btn-default:focus,
.btn-default:active.focus,
.btn-default.active.focus,
.open > .dropdown-toggle.btn-default.focus {
  color: #333;
  background-color: #d4d4d4;
  border-color: #8c8c8c;
}
.btn-default:active,
.btn-default.active,
.open > .dropdown-toggle.btn-default {
  background-image: none;
}
.btn-default.disabled:hover,
.btn-default[disabled]:hover,
fieldset[disabled] .btn-default:hover,
.btn-default.disabled:focus,
.btn-default[disabled]:focus,
fieldset[disabled] .btn-default:focus,
.btn-default.disabled.focus,
.btn-default[disabled].focus,
fieldset[disabled] .btn-default.focus {
  background-color: #fff;
  border-color: #ccc;
}
.btn-default .badge {
  color: #fff;
  background-color: #333;
}
.btn-primary {
  color: #fff;
  background-color: #337ab7;
  border-color: #2e6da4;
}
.btn-primary:focus,
.btn-primary.focus {
  color: #fff;
  background-color: #286090;
  border-color: #122b40;
}
.btn-primary:hover {
  color: #fff;
  background-color: #286090;
  border-color: #204d74;
}
.btn-primary:active,
.btn-primary.active,
.open > .dropdown-toggle.btn-primary {
  color: #fff;
  background-color: #286090;
  border-color: #204d74;
}
.btn-primary:active:hover,
.btn-primary.active:hover,
.open > .dropdown-toggle.btn-primary:hover,
.btn-primary:active:focus,
.btn-primary.active:focus,
.open > .dropdown-toggle.btn-primary:focus,
.btn-primary:active.focus,
.btn-primary.active.focus,
.open > .dropdown-toggle.btn-primary.focus {
  color: #fff;
  background-color: #204d74;
  border-color: #122b40;
}
.btn-primary:active,
.btn-primary.active,
.open > .dropdown-toggle.btn-primary {
  background-image: none;
}
.btn-primary.disabled:hover,
.btn-primary[disabled]:hover,
fieldset[disabled] .btn-primary:hover,
.btn-primary.disabled:focus,
.btn-primary[disabled]:focus,
fieldset[disabled] .btn-primary:focus,
.btn-primary.disabled.focus,
.btn-primary[disabled].focus,
fieldset[disabled] .btn-primary.focus {
  background-color: #337ab7;
  border-color: #2e6da4;
}
.btn-primary .badge {
  color: #337ab7;
  background-color: #fff;
}
.btn-success {
  color: #fff;
  background-color: #5cb85c;
  border-color: #4cae4c;
}
.btn-success:focus,
.btn-success.focus {
  color: #fff;
  background-color: #449d44;
  border-color: #255625;
}
.btn-success:hover {
  color: #fff;
  background-color: #449d44;
  border-color: #398439;
}
.btn-success:active,
.btn-success.active,
.open > .dropdown-toggle.btn-success {
  color: #fff;
  background-color: #449d44;
  border-color: #398439;
}
.btn-success:active:hover,
.btn-success.active:hover,
.open > .dropdown-toggle.btn-success:hover,
.btn-success:active:focus,
.btn-success.active:focus,
.open > .dropdown-toggle.btn-success:focus,
.btn-success:active.focus,
.btn-success.active.focus,
.open > .dropdown-toggle.btn-success.focus {
  color: #fff;
  background-color: #398439;
  border-color: #255625;
}
.btn-success:active,
.btn-success.active,
.open > .dropdown-toggle.btn-success {
  background-image: none;
}
.btn-success.disabled:hover,
.btn-success[disabled]:hover,
fieldset[disabled] .btn-success:hover,
.btn-success.disabled:focus,
.btn-success[disabled]:focus,
fieldset[disabled] .btn-success:focus,
.btn-success.disabled.focus,
.btn-success[disabled].focus,
fieldset[disabled] .btn-success.focus {
  background-color: #5cb85c;
  border-color: #4cae4c;
}
.btn-success .badge {
  color: #5cb85c;
  background-color: #fff;
}
.btn-info {
  color: #fff;
  background-color: #5bc0de;
  border-color: #46b8da;
}
.btn-info:focus,
.btn-info.focus {
  color: #fff;
  background-color: #31b0d5;
  border-color: #1b6d85;
}
.btn-info:hover {
  color: #fff;
  background-color: #31b0d5;
  border-color: #269abc;
}
.btn-info:active,
.btn-info.active,
.open > .dropdown-toggle.btn-info {
  color: #fff;
  background-color: #31b0d5;
  border-color: #269abc;
}
.btn-info:active:hover,
.btn-info.active:hover,
.open > .dropdown-toggle.btn-info:hover,
.btn-info:active:focus,
.btn-info.active:focus,
.open > .dropdown-toggle.btn-info:focus,
.btn-info:active.focus,
.btn-info.active.focus,
.open > .dropdown-toggle.btn-info.focus {
  color: #fff;
  background-color: #269abc;
  border-color: #1b6d85;
}
.btn-info:active,
.btn-info.active,
.open > .dropdown-toggle.btn-info {
  background-image: none;
}
.btn-info.disabled:hover,
.btn-info[disabled]:hover,
fieldset[disabled] .btn-info:hover,
.btn-info.disabled:focus,
.btn-info[disabled]:focus,
fieldset[disabled] .btn-info:focus,
.btn-info.disabled.focus,
.btn-info[disabled].focus,
fieldset[disabled] .btn-info.focus {
  background-color: #5bc0de;
  border-color: #46b8da;
}
.btn-info .badge {
  color: #5bc0de;
  background-color: #fff;
}
.btn-warning {
  color: #fff;
  background-color: #f0ad4e;
  border-color: #eea236;
}
.btn-warning:focus,
.btn-warning.focus {
  color: #fff;
  background-color: #ec971f;
  border-color: #985f0d;
}
.btn-warning:hover {
  color: #fff;
  background-color: #ec971f;
  border-color: #d58512;
}
.btn-warning:active,
.btn-warning.active,
.open > .dropdown-toggle.btn-warning {
  color: #fff;
  background-color: #ec971f;
  border-color: #d58512;
}
.btn-warning:active:hover,
.btn-warning.active:hover,
.open > .dropdown-toggle.btn-warning:hover,
.btn-warning:active:focus,
.btn-warning.active:focus,
.open > .dropdown-toggle.btn-warning:focus,
.btn-warning:active.focus,
.btn-warning.active.focus,
.open > .dropdown-toggle.btn-warning.focus {
  color: #fff;
  background-color: #d58512;
  border-color: #985f0d;
}
.btn-warning:active,
.btn-warning.active,
.open > .dropdown-toggle.btn-warning {
  background-image: none;
}
.btn-warning.disabled:hover,
.btn-warning[disabled]:hover,
fieldset[disabled] .btn-warning:hover,
.btn-warning.disabled:focus,
.btn-warning[disabled]:focus,
fieldset[disabled] .btn-warning:focus,
.btn-warning.disabled.focus,
.btn-warning[disabled].focus,
fieldset[disabled] .btn-warning.focus {
  background-color: #f0ad4e;
  border-color: #eea236;
}
.btn-warning .badge {
  color: #f0ad4e;
  background-color: #fff;
}
.btn-danger {
  color: #fff;
  background-color: #d9534f;
  border-color: #d43f3a;
}
.btn-danger:focus,
.btn-danger.focus {
  color: #fff;
  background-color: #c9302c;
  border-color: #761c19;
}
.btn-danger:hover {
  color: #fff;
  background-color: #c9302c;
  border-color: #ac2925;
}
.btn-danger:active,
.btn-danger.active,
.open > .dropdown-toggle.btn-danger {
  color: #fff;
  background-color: #c9302c;
  border-color: #ac2925;
}
.btn-danger:active:hover,
.btn-danger.active:hover,
.open > .dropdown-toggle.btn-danger:hover,
.btn-danger:active:focus,
.btn-danger.active:focus,
.open > .dropdown-toggle.btn-danger:focus,
.btn-danger:active.focus,
.btn-danger.active.focus,
.open > .dropdown-toggle.btn-danger.focus {
  color: #fff;
  background-color: #ac2925;
  border-color: #761c19;
}
.btn-danger:active,
.btn-danger.active,
.open > .dropdown-toggle.btn-danger {
  background-image: none;
}
.btn-danger.disabled:hover,
.btn-danger[disabled]:hover,
fieldset[disabled] .btn-danger:hover,
.btn-danger.disabled:focus,
.btn-danger[disabled]:focus,
fieldset[disabled] .btn-danger:focus,
.btn-danger.disabled.focus,
.btn-danger[disabled].focus,
fieldset[disabled] .btn-danger.focus {
  background-color: #d9534f;
  border-color: #d43f3a;
}
.btn-danger .badge {
  color: #d9534f;
  background-color: #fff;
}
.btn-link {
  color: #337ab7;
  font-weight: normal;
  border-radius: 0;
}
.btn-link,
.btn-link:active,
.btn-link.active,
.btn-link[disabled],
fieldset[disabled] .btn-link {
  background-color: transparent;
  -webkit-box-shadow: none;
  box-shadow: none;
}
.btn-link,
.btn-link:hover,
.btn-link:focus,
.btn-link:active {
  border-color: transparent;
}
.btn-link:hover,
.btn-link:focus {
  color: #23527c;
  text-decoration: underline;
  background-color: transparent;
}
.btn-link[disabled]:hover,
fieldset[disabled] .btn-link:hover,
.btn-link[disabled]:focus,
fieldset[disabled] .btn-link:focus {
  color: #777777;
  text-decoration: none;
}
.btn-lg,
.btn-group-lg > .btn {
  padding: 10px 16px;
  font-size: 17px;
  line-height: 1.3333333;
  border-radius: 3px;
}
.btn-sm,
.btn-group-sm > .btn {
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
}
.btn-xs,
.btn-group-xs > .btn {
  padding: 1px 5px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
}
.btn-block {
  display: block;
  width: 100%;
}
.btn-block + .btn-block {
  margin-top: 5px;
}
input[type="submit"].btn-block,
input[type="reset"].btn-block,
input[type="button"].btn-block {
  width: 100%;
}
.fade {
  opacity: 0;
  -webkit-transition: opacity 0.15s linear;
  -o-transition: opacity 0.15s linear;
  transition: opacity 0.15s linear;
}
.fade.in {
  opacity: 1;
}
.collapse {
  display: none;
}
.collapse.in {
  display: block;
}
tr.collapse.in {
  display: table-row;
}
tbody.collapse.in {
  display: table-row-group;
}
.collapsing {
  position: relative;
  height: 0;
  overflow: hidden;
  -webkit-transition-property: height, visibility;
  transition-property: height, visibility;
  -webkit-transition-duration: 0.35s;
  transition-duration: 0.35s;
  -webkit-transition-timing-function: ease;
  transition-timing-function: ease;
}
.caret {
  display: inline-block;
  width: 0;
  height: 0;
  margin-left: 2px;
  vertical-align: middle;
  border-top: 4px dashed;
  border-top: 4px solid \9;
  border-right: 4px solid transparent;
  border-left: 4px solid transparent;
}
.dropup,
.dropdown {
  position: relative;
}
.dropdown-toggle:focus {
  outline: 0;
}
.dropdown-menu {
  position: absolute;
  top: 100%;
  left: 0;
  z-index: 1000;
  display: none;
  float: left;
  min-width: 160px;
  padding: 5px 0;
  margin: 2px 0 0;
  list-style: none;
  font-size: 13px;
  text-align: left;
  background-color: #fff;
  border: 1px solid #ccc;
  border: 1px solid rgba(0, 0, 0, 0.15);
  border-radius: 2px;
  -webkit-box-shadow: 0 6px 12px rgba(0, 0, 0, 0.175);
  box-shadow: 0 6px 12px rgba(0, 0, 0, 0.175);
  background-clip: padding-box;
}
.dropdown-menu.pull-right {
  right: 0;
  left: auto;
}
.dropdown-menu .divider {
  height: 1px;
  margin: 8px 0;
  overflow: hidden;
  background-color: #e5e5e5;
}
.dropdown-menu > li > a {
  display: block;
  padding: 3px 20px;
  clear: both;
  font-weight: normal;
  line-height: 1.42857143;
  color: #333333;
  white-space: nowrap;
}
.dropdown-menu > li > a:hover,
.dropdown-menu > li > a:focus {
  text-decoration: none;
  color: #262626;
  background-color: #f5f5f5;
}
.dropdown-menu > .active > a,
.dropdown-menu > .active > a:hover,
.dropdown-menu > .active > a:focus {
  color: #fff;
  text-decoration: none;
  outline: 0;
  background-color: #337ab7;
}
.dropdown-menu > .disabled > a,
.dropdown-menu > .disabled > a:hover,
.dropdown-menu > .disabled > a:focus {
  color: #777777;
}
.dropdown-menu > .disabled > a:hover,
.dropdown-menu > .disabled > a:focus {
  text-decoration: none;
  background-color: transparent;
  background-image: none;
  filter: progid:DXImageTransform.Microsoft.gradient(enabled = false);
  cursor: not-allowed;
}
.open > .dropdown-menu {
  display: block;
}
.open > a {
  outline: 0;
}
.dropdown-menu-right {
  left: auto;
  right: 0;
}
.dropdown-menu-left {
  left: 0;
  right: auto;
}
.dropdown-header {
  display: block;
  padding: 3px 20px;
  font-size: 12px;
  line-height: 1.42857143;
  color: #777777;
  white-space: nowrap;
}
.dropdown-backdrop {
  position: fixed;
  left: 0;
  right: 0;
  bottom: 0;
  top: 0;
  z-index: 990;
}
.pull-right > .dropdown-menu {
  right: 0;
  left: auto;
}
.dropup .caret,
.navbar-fixed-bottom .dropdown .caret {
  border-top: 0;
  border-bottom: 4px dashed;
  border-bottom: 4px solid \9;
  content: "";
}
.dropup .dropdown-menu,
.navbar-fixed-bottom .dropdown .dropdown-menu {
  top: auto;
  bottom: 100%;
  margin-bottom: 2px;
}
@media (min-width: 541px) {
  .navbar-right .dropdown-menu {
    left: auto;
    right: 0;
  }
  .navbar-right .dropdown-menu-left {
    left: 0;
    right: auto;
  }
}
.btn-group,
.btn-group-vertical {
  position: relative;
  display: inline-block;
  vertical-align: middle;
}
.btn-group > .btn,
.btn-group-vertical > .btn {
  position: relative;
  float: left;
}
.btn-group > .btn:hover,
.btn-group-vertical > .btn:hover,
.btn-group > .btn:focus,
.btn-group-vertical > .btn:focus,
.btn-group > .btn:active,
.btn-group-vertical > .btn:active,
.btn-group > .btn.active,
.btn-group-vertical > .btn.active {
  z-index: 2;
}
.btn-group .btn + .btn,
.btn-group .btn + .btn-group,
.btn-group .btn-group + .btn,
.btn-group .btn-group + .btn-group {
  margin-left: -1px;
}
.btn-toolbar {
  margin-left: -5px;
}
.btn-toolbar .btn,
.btn-toolbar .btn-group,
.btn-toolbar .input-group {
  float: left;
}
.btn-toolbar > .btn,
.btn-toolbar > .btn-group,
.btn-toolbar > .input-group {
  margin-left: 5px;
}
.btn-group > .btn:not(:first-child):not(:last-child):not(.dropdown-toggle) {
  border-radius: 0;
}
.btn-group > .btn:first-child {
  margin-left: 0;
}
.btn-group > .btn:first-child:not(:last-child):not(.dropdown-toggle) {
  border-bottom-right-radius: 0;
  border-top-right-radius: 0;
}
.btn-group > .btn:last-child:not(:first-child),
.btn-group > .dropdown-toggle:not(:first-child) {
  border-bottom-left-radius: 0;
  border-top-left-radius: 0;
}
.btn-group > .btn-group {
  float: left;
}
.btn-group > .btn-group:not(:first-child):not(:last-child) > .btn {
  border-radius: 0;
}
.btn-group > .btn-group:first-child:not(:last-child) > .btn:last-child,
.btn-group > .btn-group:first-child:not(:last-child) > .dropdown-toggle {
  border-bottom-right-radius: 0;
  border-top-right-radius: 0;
}
.btn-group > .btn-group:last-child:not(:first-child) > .btn:first-child {
  border-bottom-left-radius: 0;
  border-top-left-radius: 0;
}
.btn-group .dropdown-toggle:active,
.btn-group.open .dropdown-toggle {
  outline: 0;
}
.btn-group > .btn + .dropdown-toggle {
  padding-left: 8px;
  padding-right: 8px;
}
.btn-group > .btn-lg + .dropdown-toggle {
  padding-left: 12px;
  padding-right: 12px;
}
.btn-group.open .dropdown-toggle {
  -webkit-box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);
  box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);
}
.btn-group.open .dropdown-toggle.btn-link {
  -webkit-box-shadow: none;
  box-shadow: none;
}
.btn .caret {
  margin-left: 0;
}
.btn-lg .caret {
  border-width: 5px 5px 0;
  border-bottom-width: 0;
}
.dropup .btn-lg .caret {
  border-width: 0 5px 5px;
}
.btn-group-vertical > .btn,
.btn-group-vertical > .btn-group,
.btn-group-vertical > .btn-group > .btn {
  display: block;
  float: none;
  width: 100%;
  max-width: 100%;
}
.btn-group-vertical > .btn-group > .btn {
  float: none;
}
.btn-group-vertical > .btn + .btn,
.btn-group-vertical > .btn + .btn-group,
.btn-group-vertical > .btn-group + .btn,
.btn-group-vertical > .btn-group + .btn-group {
  margin-top: -1px;
  margin-left: 0;
}
.btn-group-vertical > .btn:not(:first-child):not(:last-child) {
  border-radius: 0;
}
.btn-group-vertical > .btn:first-child:not(:last-child) {
  border-top-right-radius: 2px;
  border-top-left-radius: 2px;
  border-bottom-right-radius: 0;
  border-bottom-left-radius: 0;
}
.btn-group-vertical > .btn:last-child:not(:first-child) {
  border-top-right-radius: 0;
  border-top-left-radius: 0;
  border-bottom-right-radius: 2px;
  border-bottom-left-radius: 2px;
}
.btn-group-vertical > .btn-group:not(:first-child):not(:last-child) > .btn {
  border-radius: 0;
}
.btn-group-vertical > .btn-group:first-child:not(:last-child) > .btn:last-child,
.btn-group-vertical > .btn-group:first-child:not(:last-child) > .dropdown-toggle {
  border-bottom-right-radius: 0;
  border-bottom-left-radius: 0;
}
.btn-group-vertical > .btn-group:last-child:not(:first-child) > .btn:first-child {
  border-top-right-radius: 0;
  border-top-left-radius: 0;
}
.btn-group-justified {
  display: table;
  width: 100%;
  table-layout: fixed;
  border-collapse: separate;
}
.btn-group-justified > .btn,
.btn-group-justified > .btn-group {
  float: none;
  display: table-cell;
  width: 1%;
}
.btn-group-justified > .btn-group .btn {
  width: 100%;
}
.btn-group-justified > .btn-group .dropdown-menu {
  left: auto;
}
[data-toggle="buttons"] > .btn input[type="radio"],
[data-toggle="buttons"] > .btn-group > .btn input[type="radio"],
[data-toggle="buttons"] > .btn input[type="checkbox"],
[data-toggle="buttons"] > .btn-group > .btn input[type="checkbox"] {
  position: absolute;
  clip: rect(0, 0, 0, 0);
  pointer-events: none;
}
.input-group {
  position: relative;
  display: table;
  border-collapse: separate;
}
.input-group[class*="col-"] {
  float: none;
  padding-left: 0;
  padding-right: 0;
}
.input-group .form-control {
  position: relative;
  z-index: 2;
  float: left;
  width: 100%;
  margin-bottom: 0;
}
.input-group .form-control:focus {
  z-index: 3;
}
.input-group-lg > .form-control,
.input-group-lg > .input-group-addon,
.input-group-lg > .input-group-btn > .btn {
  height: 45px;
  padding: 10px 16px;
  font-size: 17px;
  line-height: 1.3333333;
  border-radius: 3px;
}
select.input-group-lg > .form-control,
select.input-group-lg > .input-group-addon,
select.input-group-lg > .input-group-btn > .btn {
  height: 45px;
  line-height: 45px;
}
textarea.input-group-lg > .form-control,
textarea.input-group-lg > .input-group-addon,
textarea.input-group-lg > .input-group-btn > .btn,
select[multiple].input-group-lg > .form-control,
select[multiple].input-group-lg > .input-group-addon,
select[multiple].input-group-lg > .input-group-btn > .btn {
  height: auto;
}
.input-group-sm > .form-control,
.input-group-sm > .input-group-addon,
.input-group-sm > .input-group-btn > .btn {
  height: 30px;
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
}
select.input-group-sm > .form-control,
select.input-group-sm > .input-group-addon,
select.input-group-sm > .input-group-btn > .btn {
  height: 30px;
  line-height: 30px;
}
textarea.input-group-sm > .form-control,
textarea.input-group-sm > .input-group-addon,
textarea.input-group-sm > .input-group-btn > .btn,
select[multiple].input-group-sm > .form-control,
select[multiple].input-group-sm > .input-group-addon,
select[multiple].input-group-sm > .input-group-btn > .btn {
  height: auto;
}
.input-group-addon,
.input-group-btn,
.input-group .form-control {
  display: table-cell;
}
.input-group-addon:not(:first-child):not(:last-child),
.input-group-btn:not(:first-child):not(:last-child),
.input-group .form-control:not(:first-child):not(:last-child) {
  border-radius: 0;
}
.input-group-addon,
.input-group-btn {
  width: 1%;
  white-space: nowrap;
  vertical-align: middle;
}
.input-group-addon {
  padding: 6px 12px;
  font-size: 13px;
  font-weight: normal;
  line-height: 1;
  color: #555555;
  text-align: center;
  background-color: #eeeeee;
  border: 1px solid #ccc;
  border-radius: 2px;
}
.input-group-addon.input-sm {
  padding: 5px 10px;
  font-size: 12px;
  border-radius: 1px;
}
.input-group-addon.input-lg {
  padding: 10px 16px;
  font-size: 17px;
  border-radius: 3px;
}
.input-group-addon input[type="radio"],
.input-group-addon input[type="checkbox"] {
  margin-top: 0;
}
.input-group .form-control:first-child,
.input-group-addon:first-child,
.input-group-btn:first-child > .btn,
.input-group-btn:first-child > .btn-group > .btn,
.input-group-btn:first-child > .dropdown-toggle,
.input-group-btn:last-child > .btn:not(:last-child):not(.dropdown-toggle),
.input-group-btn:last-child > .btn-group:not(:last-child) > .btn {
  border-bottom-right-radius: 0;
  border-top-right-radius: 0;
}
.input-group-addon:first-child {
  border-right: 0;
}
.input-group .form-control:last-child,
.input-group-addon:last-child,
.input-group-btn:last-child > .btn,
.input-group-btn:last-child > .btn-group > .btn,
.input-group-btn:last-child > .dropdown-toggle,
.input-group-btn:first-child > .btn:not(:first-child),
.input-group-btn:first-child > .btn-group:not(:first-child) > .btn {
  border-bottom-left-radius: 0;
  border-top-left-radius: 0;
}
.input-group-addon:last-child {
  border-left: 0;
}
.input-group-btn {
  position: relative;
  font-size: 0;
  white-space: nowrap;
}
.input-group-btn > .btn {
  position: relative;
}
.input-group-btn > .btn + .btn {
  margin-left: -1px;
}
.input-group-btn > .btn:hover,
.input-group-btn > .btn:focus,
.input-group-btn > .btn:active {
  z-index: 2;
}
.input-group-btn:first-child > .btn,
.input-group-btn:first-child > .btn-group {
  margin-right: -1px;
}
.input-group-btn:last-child > .btn,
.input-group-btn:last-child > .btn-group {
  z-index: 2;
  margin-left: -1px;
}
.nav {
  margin-bottom: 0;
  padding-left: 0;
  list-style: none;
}
.nav > li {
  position: relative;
  display: block;
}
.nav > li > a {
  position: relative;
  display: block;
  padding: 10px 15px;
}
.nav > li > a:hover,
.nav > li > a:focus {
  text-decoration: none;
  background-color: #eeeeee;
}
.nav > li.disabled > a {
  color: #777777;
}
.nav > li.disabled > a:hover,
.nav > li.disabled > a:focus {
  color: #777777;
  text-decoration: none;
  background-color: transparent;
  cursor: not-allowed;
}
.nav .open > a,
.nav .open > a:hover,
.nav .open > a:focus {
  background-color: #eeeeee;
  border-color: #337ab7;
}
.nav .nav-divider {
  height: 1px;
  margin: 8px 0;
  overflow: hidden;
  background-color: #e5e5e5;
}
.nav > li > a > img {
  max-width: none;
}
.nav-tabs {
  border-bottom: 1px solid #ddd;
}
.nav-tabs > li {
  float: left;
  margin-bottom: -1px;
}
.nav-tabs > li > a {
  margin-right: 2px;
  line-height: 1.42857143;
  border: 1px solid transparent;
  border-radius: 2px 2px 0 0;
}
.nav-tabs > li > a:hover {
  border-color: #eeeeee #eeeeee #ddd;
}
.nav-tabs > li.active > a,
.nav-tabs > li.active > a:hover,
.nav-tabs > li.active > a:focus {
  color: #555555;
  background-color: #fff;
  border: 1px solid #ddd;
  border-bottom-color: transparent;
  cursor: default;
}
.nav-tabs.nav-justified {
  width: 100%;
  border-bottom: 0;
}
.nav-tabs.nav-justified > li {
  float: none;
}
.nav-tabs.nav-justified > li > a {
  text-align: center;
  margin-bottom: 5px;
}
.nav-tabs.nav-justified > .dropdown .dropdown-menu {
  top: auto;
  left: auto;
}
@media (min-width: 768px) {
  .nav-tabs.nav-justified > li {
    display: table-cell;
    width: 1%;
  }
  .nav-tabs.nav-justified > li > a {
    margin-bottom: 0;
  }
}
.nav-tabs.nav-justified > li > a {
  margin-right: 0;
  border-radius: 2px;
}
.nav-tabs.nav-justified > .active > a,
.nav-tabs.nav-justified > .active > a:hover,
.nav-tabs.nav-justified > .active > a:focus {
  border: 1px solid #ddd;
}
@media (min-width: 768px) {
  .nav-tabs.nav-justified > li > a {
    border-bottom: 1px solid #ddd;
    border-radius: 2px 2px 0 0;
  }
  .nav-tabs.nav-justified > .active > a,
  .nav-tabs.nav-justified > .active > a:hover,
  .nav-tabs.nav-justified > .active > a:focus {
    border-bottom-color: #fff;
  }
}
.nav-pills > li {
  float: left;
}
.nav-pills > li > a {
  border-radius: 2px;
}
.nav-pills > li + li {
  margin-left: 2px;
}
.nav-pills > li.active > a,
.nav-pills > li.active > a:hover,
.nav-pills > li.active > a:focus {
  color: #fff;
  background-color: #337ab7;
}
.nav-stacked > li {
  float: none;
}
.nav-stacked > li + li {
  margin-top: 2px;
  margin-left: 0;
}
.nav-justified {
  width: 100%;
}
.nav-justified > li {
  float: none;
}
.nav-justified > li > a {
  text-align: center;
  margin-bottom: 5px;
}
.nav-justified > .dropdown .dropdown-menu {
  top: auto;
  left: auto;
}
@media (min-width: 768px) {
  .nav-justified > li {
    display: table-cell;
    width: 1%;
  }
  .nav-justified > li > a {
    margin-bottom: 0;
  }
}
.nav-tabs-justified {
  border-bottom: 0;
}
.nav-tabs-justified > li > a {
  margin-right: 0;
  border-radius: 2px;
}
.nav-tabs-justified > .active > a,
.nav-tabs-justified > .active > a:hover,
.nav-tabs-justified > .active > a:focus {
  border: 1px solid #ddd;
}
@media (min-width: 768px) {
  .nav-tabs-justified > li > a {
    border-bottom: 1px solid #ddd;
    border-radius: 2px 2px 0 0;
  }
  .nav-tabs-justified > .active > a,
  .nav-tabs-justified > .active > a:hover,
  .nav-tabs-justified > .active > a:focus {
    border-bottom-color: #fff;
  }
}
.tab-content > .tab-pane {
  display: none;
}
.tab-content > .active {
  display: block;
}
.nav-tabs .dropdown-menu {
  margin-top: -1px;
  border-top-right-radius: 0;
  border-top-left-radius: 0;
}
.navbar {
  position: relative;
  min-height: 30px;
  margin-bottom: 18px;
  border: 1px solid transparent;
}
@media (min-width: 541px) {
  .navbar {
    border-radius: 2px;
  }
}
@media (min-width: 541px) {
  .navbar-header {
    float: left;
  }
}
.navbar-collapse {
  overflow-x: visible;
  padding-right: 0px;
  padding-left: 0px;
  border-top: 1px solid transparent;
  box-shadow: inset 0 1px 0 rgba(255, 255, 255, 0.1);
  -webkit-overflow-scrolling: touch;
}
.navbar-collapse.in {
  overflow-y: auto;
}
@media (min-width: 541px) {
  .navbar-collapse {
    width: auto;
    border-top: 0;
    box-shadow: none;
  }
  .navbar-collapse.collapse {
    display: block !important;
    height: auto !important;
    padding-bottom: 0;
    overflow: visible !important;
  }
  .navbar-collapse.in {
    overflow-y: visible;
  }
  .navbar-fixed-top .navbar-collapse,
  .navbar-static-top .navbar-collapse,
  .navbar-fixed-bottom .navbar-collapse {
    padding-left: 0;
    padding-right: 0;
  }
}
.navbar-fixed-top .navbar-collapse,
.navbar-fixed-bottom .navbar-collapse {
  max-height: 340px;
}
@media (max-device-width: 540px) and (orientation: landscape) {
  .navbar-fixed-top .navbar-collapse,
  .navbar-fixed-bottom .navbar-collapse {
    max-height: 200px;
  }
}
.container > .navbar-header,
.container-fluid > .navbar-header,
.container > .navbar-collapse,
.container-fluid > .navbar-collapse {
  margin-right: 0px;
  margin-left: 0px;
}
@media (min-width: 541px) {
  .container > .navbar-header,
  .container-fluid > .navbar-header,
  .container > .navbar-collapse,
  .container-fluid > .navbar-collapse {
    margin-right: 0;
    margin-left: 0;
  }
}
.navbar-static-top {
  z-index: 1000;
  border-width: 0 0 1px;
}
@media (min-width: 541px) {
  .navbar-static-top {
    border-radius: 0;
  }
}
.navbar-fixed-top,
.navbar-fixed-bottom {
  position: fixed;
  right: 0;
  left: 0;
  z-index: 1030;
}
@media (min-width: 541px) {
  .navbar-fixed-top,
  .navbar-fixed-bottom {
    border-radius: 0;
  }
}
.navbar-fixed-top {
  top: 0;
  border-width: 0 0 1px;
}
.navbar-fixed-bottom {
  bottom: 0;
  margin-bottom: 0;
  border-width: 1px 0 0;
}
.navbar-brand {
  float: left;
  padding: 6px 0px;
  font-size: 17px;
  line-height: 18px;
  height: 30px;
}
.navbar-brand:hover,
.navbar-brand:focus {
  text-decoration: none;
}
.navbar-brand > img {
  display: block;
}
@media (min-width: 541px) {
  .navbar > .container .navbar-brand,
  .navbar > .container-fluid .navbar-brand {
    margin-left: 0px;
  }
}
.navbar-toggle {
  position: relative;
  float: right;
  margin-right: 0px;
  padding: 9px 10px;
  margin-top: -2px;
  margin-bottom: -2px;
  background-color: transparent;
  background-image: none;
  border: 1px solid transparent;
  border-radius: 2px;
}
.navbar-toggle:focus {
  outline: 0;
}
.navbar-toggle .icon-bar {
  display: block;
  width: 22px;
  height: 2px;
  border-radius: 1px;
}
.navbar-toggle .icon-bar + .icon-bar {
  margin-top: 4px;
}
@media (min-width: 541px) {
  .navbar-toggle {
    display: none;
  }
}
.navbar-nav {
  margin: 3px 0px;
}
.navbar-nav > li > a {
  padding-top: 10px;
  padding-bottom: 10px;
  line-height: 18px;
}
@media (max-width: 540px) {
  .navbar-nav .open .dropdown-menu {
    position: static;
    float: none;
    width: auto;
    margin-top: 0;
    background-color: transparent;
    border: 0;
    box-shadow: none;
  }
  .navbar-nav .open .dropdown-menu > li > a,
  .navbar-nav .open .dropdown-menu .dropdown-header {
    padding: 5px 15px 5px 25px;
  }
  .navbar-nav .open .dropdown-menu > li > a {
    line-height: 18px;
  }
  .navbar-nav .open .dropdown-menu > li > a:hover,
  .navbar-nav .open .dropdown-menu > li > a:focus {
    background-image: none;
  }
}
@media (min-width: 541px) {
  .navbar-nav {
    float: left;
    margin: 0;
  }
  .navbar-nav > li {
    float: left;
  }
  .navbar-nav > li > a {
    padding-top: 6px;
    padding-bottom: 6px;
  }
}
.navbar-form {
  margin-left: 0px;
  margin-right: 0px;
  padding: 10px 0px;
  border-top: 1px solid transparent;
  border-bottom: 1px solid transparent;
  -webkit-box-shadow: inset 0 1px 0 rgba(255, 255, 255, 0.1), 0 1px 0 rgba(255, 255, 255, 0.1);
  box-shadow: inset 0 1px 0 rgba(255, 255, 255, 0.1), 0 1px 0 rgba(255, 255, 255, 0.1);
  margin-top: -1px;
  margin-bottom: -1px;
}
@media (min-width: 768px) {
  .navbar-form .form-group {
    display: inline-block;
    margin-bottom: 0;
    vertical-align: middle;
  }
  .navbar-form .form-control {
    display: inline-block;
    width: auto;
    vertical-align: middle;
  }
  .navbar-form .form-control-static {
    display: inline-block;
  }
  .navbar-form .input-group {
    display: inline-table;
    vertical-align: middle;
  }
  .navbar-form .input-group .input-group-addon,
  .navbar-form .input-group .input-group-btn,
  .navbar-form .input-group .form-control {
    width: auto;
  }
  .navbar-form .input-group > .form-control {
    width: 100%;
  }
  .navbar-form .control-label {
    margin-bottom: 0;
    vertical-align: middle;
  }
  .navbar-form .radio,
  .navbar-form .checkbox {
    display: inline-block;
    margin-top: 0;
    margin-bottom: 0;
    vertical-align: middle;
  }
  .navbar-form .radio label,
  .navbar-form .checkbox label {
    padding-left: 0;
  }
  .navbar-form .radio input[type="radio"],
  .navbar-form .checkbox input[type="checkbox"] {
    position: relative;
    margin-left: 0;
  }
  .navbar-form .has-feedback .form-control-feedback {
    top: 0;
  }
}
@media (max-width: 540px) {
  .navbar-form .form-group {
    margin-bottom: 5px;
  }
  .navbar-form .form-group:last-child {
    margin-bottom: 0;
  }
}
@media (min-width: 541px) {
  .navbar-form {
    width: auto;
    border: 0;
    margin-left: 0;
    margin-right: 0;
    padding-top: 0;
    padding-bottom: 0;
    -webkit-box-shadow: none;
    box-shadow: none;
  }
}
.navbar-nav > li > .dropdown-menu {
  margin-top: 0;
  border-top-right-radius: 0;
  border-top-left-radius: 0;
}
.navbar-fixed-bottom .navbar-nav > li > .dropdown-menu {
  margin-bottom: 0;
  border-top-right-radius: 2px;
  border-top-left-radius: 2px;
  border-bottom-right-radius: 0;
  border-bottom-left-radius: 0;
}
.navbar-btn {
  margin-top: -1px;
  margin-bottom: -1px;
}
.navbar-btn.btn-sm {
  margin-top: 0px;
  margin-bottom: 0px;
}
.navbar-btn.btn-xs {
  margin-top: 4px;
  margin-bottom: 4px;
}
.navbar-text {
  margin-top: 6px;
  margin-bottom: 6px;
}
@media (min-width: 541px) {
  .navbar-text {
    float: left;
    margin-left: 0px;
    margin-right: 0px;
  }
}
@media (min-width: 541px) {
  .navbar-left {
    float: left !important;
    float: left;
  }
  .navbar-right {
    float: right !important;
    float: right;
    margin-right: 0px;
  }
  .navbar-right ~ .navbar-right {
    margin-right: 0;
  }
}
.navbar-default {
  background-color: #f8f8f8;
  border-color: #e7e7e7;
}
.navbar-default .navbar-brand {
  color: #777;
}
.navbar-default .navbar-brand:hover,
.navbar-default .navbar-brand:focus {
  color: #5e5e5e;
  background-color: transparent;
}
.navbar-default .navbar-text {
  color: #777;
}
.navbar-default .navbar-nav > li > a {
  color: #777;
}
.navbar-default .navbar-nav > li > a:hover,
.navbar-default .navbar-nav > li > a:focus {
  color: #333;
  background-color: transparent;
}
.navbar-default .navbar-nav > .active > a,
.navbar-default .navbar-nav > .active > a:hover,
.navbar-default .navbar-nav > .active > a:focus {
  color: #555;
  background-color: #e7e7e7;
}
.navbar-default .navbar-nav > .disabled > a,
.navbar-default .navbar-nav > .disabled > a:hover,
.navbar-default .navbar-nav > .disabled > a:focus {
  color: #ccc;
  background-color: transparent;
}
.navbar-default .navbar-toggle {
  border-color: #ddd;
}
.navbar-default .navbar-toggle:hover,
.navbar-default .navbar-toggle:focus {
  background-color: #ddd;
}
.navbar-default .navbar-toggle .icon-bar {
  background-color: #888;
}
.navbar-default .navbar-collapse,
.navbar-default .navbar-form {
  border-color: #e7e7e7;
}
.navbar-default .navbar-nav > .open > a,
.navbar-default .navbar-nav > .open > a:hover,
.navbar-default .navbar-nav > .open > a:focus {
  background-color: #e7e7e7;
  color: #555;
}
@media (max-width: 540px) {
  .navbar-default .navbar-nav .open .dropdown-menu > li > a {
    color: #777;
  }
  .navbar-default .navbar-nav .open .dropdown-menu > li > a:hover,
  .navbar-default .navbar-nav .open .dropdown-menu > li > a:focus {
    color: #333;
    background-color: transparent;
  }
  .navbar-default .navbar-nav .open .dropdown-menu > .active > a,
  .navbar-default .navbar-nav .open .dropdown-menu > .active > a:hover,
  .navbar-default .navbar-nav .open .dropdown-menu > .active > a:focus {
    color: #555;
    background-color: #e7e7e7;
  }
  .navbar-default .navbar-nav .open .dropdown-menu > .disabled > a,
  .navbar-default .navbar-nav .open .dropdown-menu > .disabled > a:hover,
  .navbar-default .navbar-nav .open .dropdown-menu > .disabled > a:focus {
    color: #ccc;
    background-color: transparent;
  }
}
.navbar-default .navbar-link {
  color: #777;
}
.navbar-default .navbar-link:hover {
  color: #333;
}
.navbar-default .btn-link {
  color: #777;
}
.navbar-default .btn-link:hover,
.navbar-default .btn-link:focus {
  color: #333;
}
.navbar-default .btn-link[disabled]:hover,
fieldset[disabled] .navbar-default .btn-link:hover,
.navbar-default .btn-link[disabled]:focus,
fieldset[disabled] .navbar-default .btn-link:focus {
  color: #ccc;
}
.navbar-inverse {
  background-color: #222;
  border-color: #080808;
}
.navbar-inverse .navbar-brand {
  color: #9d9d9d;
}
.navbar-inverse .navbar-brand:hover,
.navbar-inverse .navbar-brand:focus {
  color: #fff;
  background-color: transparent;
}
.navbar-inverse .navbar-text {
  color: #9d9d9d;
}
.navbar-inverse .navbar-nav > li > a {
  color: #9d9d9d;
}
.navbar-inverse .navbar-nav > li > a:hover,
.navbar-inverse .navbar-nav > li > a:focus {
  color: #fff;
  background-color: transparent;
}
.navbar-inverse .navbar-nav > .active > a,
.navbar-inverse .navbar-nav > .active > a:hover,
.navbar-inverse .navbar-nav > .active > a:focus {
  color: #fff;
  background-color: #080808;
}
.navbar-inverse .navbar-nav > .disabled > a,
.navbar-inverse .navbar-nav > .disabled > a:hover,
.navbar-inverse .navbar-nav > .disabled > a:focus {
  color: #444;
  background-color: transparent;
}
.navbar-inverse .navbar-toggle {
  border-color: #333;
}
.navbar-inverse .navbar-toggle:hover,
.navbar-inverse .navbar-toggle:focus {
  background-color: #333;
}
.navbar-inverse .navbar-toggle .icon-bar {
  background-color: #fff;
}
.navbar-inverse .navbar-collapse,
.navbar-inverse .navbar-form {
  border-color: #101010;
}
.navbar-inverse .navbar-nav > .open > a,
.navbar-inverse .navbar-nav > .open > a:hover,
.navbar-inverse .navbar-nav > .open > a:focus {
  background-color: #080808;
  color: #fff;
}
@media (max-width: 540px) {
  .navbar-inverse .navbar-nav .open .dropdown-menu > .dropdown-header {
    border-color: #080808;
  }
  .navbar-inverse .navbar-nav .open .dropdown-menu .divider {
    background-color: #080808;
  }
  .navbar-inverse .navbar-nav .open .dropdown-menu > li > a {
    color: #9d9d9d;
  }
  .navbar-inverse .navbar-nav .open .dropdown-menu > li > a:hover,
  .navbar-inverse .navbar-nav .open .dropdown-menu > li > a:focus {
    color: #fff;
    background-color: transparent;
  }
  .navbar-inverse .navbar-nav .open .dropdown-menu > .active > a,
  .navbar-inverse .navbar-nav .open .dropdown-menu > .active > a:hover,
  .navbar-inverse .navbar-nav .open .dropdown-menu > .active > a:focus {
    color: #fff;
    background-color: #080808;
  }
  .navbar-inverse .navbar-nav .open .dropdown-menu > .disabled > a,
  .navbar-inverse .navbar-nav .open .dropdown-menu > .disabled > a:hover,
  .navbar-inverse .navbar-nav .open .dropdown-menu > .disabled > a:focus {
    color: #444;
    background-color: transparent;
  }
}
.navbar-inverse .navbar-link {
  color: #9d9d9d;
}
.navbar-inverse .navbar-link:hover {
  color: #fff;
}
.navbar-inverse .btn-link {
  color: #9d9d9d;
}
.navbar-inverse .btn-link:hover,
.navbar-inverse .btn-link:focus {
  color: #fff;
}
.navbar-inverse .btn-link[disabled]:hover,
fieldset[disabled] .navbar-inverse .btn-link:hover,
.navbar-inverse .btn-link[disabled]:focus,
fieldset[disabled] .navbar-inverse .btn-link:focus {
  color: #444;
}
.breadcrumb {
  padding: 8px 15px;
  margin-bottom: 18px;
  list-style: none;
  background-color: #f5f5f5;
  border-radius: 2px;
}
.breadcrumb > li {
  display: inline-block;
}
.breadcrumb > li + li:before {
  content: "/\00a0";
  padding: 0 5px;
  color: #5e5e5e;
}
.breadcrumb > .active {
  color: #777777;
}
.pagination {
  display: inline-block;
  padding-left: 0;
  margin: 18px 0;
  border-radius: 2px;
}
.pagination > li {
  display: inline;
}
.pagination > li > a,
.pagination > li > span {
  position: relative;
  float: left;
  padding: 6px 12px;
  line-height: 1.42857143;
  text-decoration: none;
  color: #337ab7;
  background-color: #fff;
  border: 1px solid #ddd;
  margin-left: -1px;
}
.pagination > li:first-child > a,
.pagination > li:first-child > span {
  margin-left: 0;
  border-bottom-left-radius: 2px;
  border-top-left-radius: 2px;
}
.pagination > li:last-child > a,
.pagination > li:last-child > span {
  border-bottom-right-radius: 2px;
  border-top-right-radius: 2px;
}
.pagination > li > a:hover,
.pagination > li > span:hover,
.pagination > li > a:focus,
.pagination > li > span:focus {
  z-index: 2;
  color: #23527c;
  background-color: #eeeeee;
  border-color: #ddd;
}
.pagination > .active > a,
.pagination > .active > span,
.pagination > .active > a:hover,
.pagination > .active > span:hover,
.pagination > .active > a:focus,
.pagination > .active > span:focus {
  z-index: 3;
  color: #fff;
  background-color: #337ab7;
  border-color: #337ab7;
  cursor: default;
}
.pagination > .disabled > span,
.pagination > .disabled > span:hover,
.pagination > .disabled > span:focus,
.pagination > .disabled > a,
.pagination > .disabled > a:hover,
.pagination > .disabled > a:focus {
  color: #777777;
  background-color: #fff;
  border-color: #ddd;
  cursor: not-allowed;
}
.pagination-lg > li > a,
.pagination-lg > li > span {
  padding: 10px 16px;
  font-size: 17px;
  line-height: 1.3333333;
}
.pagination-lg > li:first-child > a,
.pagination-lg > li:first-child > span {
  border-bottom-left-radius: 3px;
  border-top-left-radius: 3px;
}
.pagination-lg > li:last-child > a,
.pagination-lg > li:last-child > span {
  border-bottom-right-radius: 3px;
  border-top-right-radius: 3px;
}
.pagination-sm > li > a,
.pagination-sm > li > span {
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
}
.pagination-sm > li:first-child > a,
.pagination-sm > li:first-child > span {
  border-bottom-left-radius: 1px;
  border-top-left-radius: 1px;
}
.pagination-sm > li:last-child > a,
.pagination-sm > li:last-child > span {
  border-bottom-right-radius: 1px;
  border-top-right-radius: 1px;
}
.pager {
  padding-left: 0;
  margin: 18px 0;
  list-style: none;
  text-align: center;
}
.pager li {
  display: inline;
}
.pager li > a,
.pager li > span {
  display: inline-block;
  padding: 5px 14px;
  background-color: #fff;
  border: 1px solid #ddd;
  border-radius: 15px;
}
.pager li > a:hover,
.pager li > a:focus {
  text-decoration: none;
  background-color: #eeeeee;
}
.pager .next > a,
.pager .next > span {
  float: right;
}
.pager .previous > a,
.pager .previous > span {
  float: left;
}
.pager .disabled > a,
.pager .disabled > a:hover,
.pager .disabled > a:focus,
.pager .disabled > span {
  color: #777777;
  background-color: #fff;
  cursor: not-allowed;
}
.label {
  display: inline;
  padding: .2em .6em .3em;
  font-size: 75%;
  font-weight: bold;
  line-height: 1;
  color: #fff;
  text-align: center;
  white-space: nowrap;
  vertical-align: baseline;
  border-radius: .25em;
}
a.label:hover,
a.label:focus {
  color: #fff;
  text-decoration: none;
  cursor: pointer;
}
.label:empty {
  display: none;
}
.btn .label {
  position: relative;
  top: -1px;
}
.label-default {
  background-color: #777777;
}
.label-default[href]:hover,
.label-default[href]:focus {
  background-color: #5e5e5e;
}
.label-primary {
  background-color: #337ab7;
}
.label-primary[href]:hover,
.label-primary[href]:focus {
  background-color: #286090;
}
.label-success {
  background-color: #5cb85c;
}
.label-success[href]:hover,
.label-success[href]:focus {
  background-color: #449d44;
}
.label-info {
  background-color: #5bc0de;
}
.label-info[href]:hover,
.label-info[href]:focus {
  background-color: #31b0d5;
}
.label-warning {
  background-color: #f0ad4e;
}
.label-warning[href]:hover,
.label-warning[href]:focus {
  background-color: #ec971f;
}
.label-danger {
  background-color: #d9534f;
}
.label-danger[href]:hover,
.label-danger[href]:focus {
  background-color: #c9302c;
}
.badge {
  display: inline-block;
  min-width: 10px;
  padding: 3px 7px;
  font-size: 12px;
  font-weight: bold;
  color: #fff;
  line-height: 1;
  vertical-align: middle;
  white-space: nowrap;
  text-align: center;
  background-color: #777777;
  border-radius: 10px;
}
.badge:empty {
  display: none;
}
.btn .badge {
  position: relative;
  top: -1px;
}
.btn-xs .badge,
.btn-group-xs > .btn .badge {
  top: 0;
  padding: 1px 5px;
}
a.badge:hover,
a.badge:focus {
  color: #fff;
  text-decoration: none;
  cursor: pointer;
}
.list-group-item.active > .badge,
.nav-pills > .active > a > .badge {
  color: #337ab7;
  background-color: #fff;
}
.list-group-item > .badge {
  float: right;
}
.list-group-item > .badge + .badge {
  margin-right: 5px;
}
.nav-pills > li > a > .badge {
  margin-left: 3px;
}
.jumbotron {
  padding-top: 30px;
  padding-bottom: 30px;
  margin-bottom: 30px;
  color: inherit;
  background-color: #eeeeee;
}
.jumbotron h1,
.jumbotron .h1 {
  color: inherit;
}
.jumbotron p {
  margin-bottom: 15px;
  font-size: 20px;
  font-weight: 200;
}
.jumbotron > hr {
  border-top-color: #d5d5d5;
}
.container .jumbotron,
.container-fluid .jumbotron {
  border-radius: 3px;
  padding-left: 0px;
  padding-right: 0px;
}
.jumbotron .container {
  max-width: 100%;
}
@media screen and (min-width: 768px) {
  .jumbotron {
    padding-top: 48px;
    padding-bottom: 48px;
  }
  .container .jumbotron,
  .container-fluid .jumbotron {
    padding-left: 60px;
    padding-right: 60px;
  }
  .jumbotron h1,
  .jumbotron .h1 {
    font-size: 59px;
  }
}
.thumbnail {
  display: block;
  padding: 4px;
  margin-bottom: 18px;
  line-height: 1.42857143;
  background-color: #fff;
  border: 1px solid #ddd;
  border-radius: 2px;
  -webkit-transition: border 0.2s ease-in-out;
  -o-transition: border 0.2s ease-in-out;
  transition: border 0.2s ease-in-out;
}
.thumbnail > img,
.thumbnail a > img {
  margin-left: auto;
  margin-right: auto;
}
a.thumbnail:hover,
a.thumbnail:focus,
a.thumbnail.active {
  border-color: #337ab7;
}
.thumbnail .caption {
  padding: 9px;
  color: #000;
}
.alert {
  padding: 15px;
  margin-bottom: 18px;
  border: 1px solid transparent;
  border-radius: 2px;
}
.alert h4 {
  margin-top: 0;
  color: inherit;
}
.alert .alert-link {
  font-weight: bold;
}
.alert > p,
.alert > ul {
  margin-bottom: 0;
}
.alert > p + p {
  margin-top: 5px;
}
.alert-dismissable,
.alert-dismissible {
  padding-right: 35px;
}
.alert-dismissable .close,
.alert-dismissible .close {
  position: relative;
  top: -2px;
  right: -21px;
  color: inherit;
}
.alert-success {
  background-color: #dff0d8;
  border-color: #d6e9c6;
  color: #3c763d;
}
.alert-success hr {
  border-top-color: #c9e2b3;
}
.alert-success .alert-link {
  color: #2b542c;
}
.alert-info {
  background-color: #d9edf7;
  border-color: #bce8f1;
  color: #31708f;
}
.alert-info hr {
  border-top-color: #a6e1ec;
}
.alert-info .alert-link {
  color: #245269;
}
.alert-warning {
  background-color: #fcf8e3;
  border-color: #faebcc;
  color: #8a6d3b;
}
.alert-warning hr {
  border-top-color: #f7e1b5;
}
.alert-warning .alert-link {
  color: #66512c;
}
.alert-danger {
  background-color: #f2dede;
  border-color: #ebccd1;
  color: #a94442;
}
.alert-danger hr {
  border-top-color: #e4b9c0;
}
.alert-danger .alert-link {
  color: #843534;
}
@-webkit-keyframes progress-bar-stripes {
  from {
    background-position: 40px 0;
  }
  to {
    background-position: 0 0;
  }
}
@keyframes progress-bar-stripes {
  from {
    background-position: 40px 0;
  }
  to {
    background-position: 0 0;
  }
}
.progress {
  overflow: hidden;
  height: 18px;
  margin-bottom: 18px;
  background-color: #f5f5f5;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 1px 2px rgba(0, 0, 0, 0.1);
  box-shadow: inset 0 1px 2px rgba(0, 0, 0, 0.1);
}
.progress-bar {
  float: left;
  width: 0%;
  height: 100%;
  font-size: 12px;
  line-height: 18px;
  color: #fff;
  text-align: center;
  background-color: #337ab7;
  -webkit-box-shadow: inset 0 -1px 0 rgba(0, 0, 0, 0.15);
  box-shadow: inset 0 -1px 0 rgba(0, 0, 0, 0.15);
  -webkit-transition: width 0.6s ease;
  -o-transition: width 0.6s ease;
  transition: width 0.6s ease;
}
.progress-striped .progress-bar,
.progress-bar-striped {
  background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-size: 40px 40px;
}
.progress.active .progress-bar,
.progress-bar.active {
  -webkit-animation: progress-bar-stripes 2s linear infinite;
  -o-animation: progress-bar-stripes 2s linear infinite;
  animation: progress-bar-stripes 2s linear infinite;
}
.progress-bar-success {
  background-color: #5cb85c;
}
.progress-striped .progress-bar-success {
  background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
}
.progress-bar-info {
  background-color: #5bc0de;
}
.progress-striped .progress-bar-info {
  background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
}
.progress-bar-warning {
  background-color: #f0ad4e;
}
.progress-striped .progress-bar-warning {
  background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
}
.progress-bar-danger {
  background-color: #d9534f;
}
.progress-striped .progress-bar-danger {
  background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
}
.media {
  margin-top: 15px;
}
.media:first-child {
  margin-top: 0;
}
.media,
.media-body {
  zoom: 1;
  overflow: hidden;
}
.media-body {
  width: 10000px;
}
.media-object {
  display: block;
}
.media-object.img-thumbnail {
  max-width: none;
}
.media-right,
.media > .pull-right {
  padding-left: 10px;
}
.media-left,
.media > .pull-left {
  padding-right: 10px;
}
.media-left,
.media-right,
.media-body {
  display: table-cell;
  vertical-align: top;
}
.media-middle {
  vertical-align: middle;
}
.media-bottom {
  vertical-align: bottom;
}
.media-heading {
  margin-top: 0;
  margin-bottom: 5px;
}
.media-list {
  padding-left: 0;
  list-style: none;
}
.list-group {
  margin-bottom: 20px;
  padding-left: 0;
}
.list-group-item {
  position: relative;
  display: block;
  padding: 10px 15px;
  margin-bottom: -1px;
  background-color: #fff;
  border: 1px solid #ddd;
}
.list-group-item:first-child {
  border-top-right-radius: 2px;
  border-top-left-radius: 2px;
}
.list-group-item:last-child {
  margin-bottom: 0;
  border-bottom-right-radius: 2px;
  border-bottom-left-radius: 2px;
}
a.list-group-item,
button.list-group-item {
  color: #555;
}
a.list-group-item .list-group-item-heading,
button.list-group-item .list-group-item-heading {
  color: #333;
}
a.list-group-item:hover,
button.list-group-item:hover,
a.list-group-item:focus,
button.list-group-item:focus {
  text-decoration: none;
  color: #555;
  background-color: #f5f5f5;
}
button.list-group-item {
  width: 100%;
  text-align: left;
}
.list-group-item.disabled,
.list-group-item.disabled:hover,
.list-group-item.disabled:focus {
  background-color: #eeeeee;
  color: #777777;
  cursor: not-allowed;
}
.list-group-item.disabled .list-group-item-heading,
.list-group-item.disabled:hover .list-group-item-heading,
.list-group-item.disabled:focus .list-group-item-heading {
  color: inherit;
}
.list-group-item.disabled .list-group-item-text,
.list-group-item.disabled:hover .list-group-item-text,
.list-group-item.disabled:focus .list-group-item-text {
  color: #777777;
}
.list-group-item.active,
.list-group-item.active:hover,
.list-group-item.active:focus {
  z-index: 2;
  color: #fff;
  background-color: #337ab7;
  border-color: #337ab7;
}
.list-group-item.active .list-group-item-heading,
.list-group-item.active:hover .list-group-item-heading,
.list-group-item.active:focus .list-group-item-heading,
.list-group-item.active .list-group-item-heading > small,
.list-group-item.active:hover .list-group-item-heading > small,
.list-group-item.active:focus .list-group-item-heading > small,
.list-group-item.active .list-group-item-heading > .small,
.list-group-item.active:hover .list-group-item-heading > .small,
.list-group-item.active:focus .list-group-item-heading > .small {
  color: inherit;
}
.list-group-item.active .list-group-item-text,
.list-group-item.active:hover .list-group-item-text,
.list-group-item.active:focus .list-group-item-text {
  color: #c7ddef;
}
.list-group-item-success {
  color: #3c763d;
  background-color: #dff0d8;
}
a.list-group-item-success,
button.list-group-item-success {
  color: #3c763d;
}
a.list-group-item-success .list-group-item-heading,
button.list-group-item-success .list-group-item-heading {
  color: inherit;
}
a.list-group-item-success:hover,
button.list-group-item-success:hover,
a.list-group-item-success:focus,
button.list-group-item-success:focus {
  color: #3c763d;
  background-color: #d0e9c6;
}
a.list-group-item-success.active,
button.list-group-item-success.active,
a.list-group-item-success.active:hover,
button.list-group-item-success.active:hover,
a.list-group-item-success.active:focus,
button.list-group-item-success.active:focus {
  color: #fff;
  background-color: #3c763d;
  border-color: #3c763d;
}
.list-group-item-info {
  color: #31708f;
  background-color: #d9edf7;
}
a.list-group-item-info,
button.list-group-item-info {
  color: #31708f;
}
a.list-group-item-info .list-group-item-heading,
button.list-group-item-info .list-group-item-heading {
  color: inherit;
}
a.list-group-item-info:hover,
button.list-group-item-info:hover,
a.list-group-item-info:focus,
button.list-group-item-info:focus {
  color: #31708f;
  background-color: #c4e3f3;
}
a.list-group-item-info.active,
button.list-group-item-info.active,
a.list-group-item-info.active:hover,
button.list-group-item-info.active:hover,
a.list-group-item-info.active:focus,
button.list-group-item-info.active:focus {
  color: #fff;
  background-color: #31708f;
  border-color: #31708f;
}
.list-group-item-warning {
  color: #8a6d3b;
  background-color: #fcf8e3;
}
a.list-group-item-warning,
button.list-group-item-warning {
  color: #8a6d3b;
}
a.list-group-item-warning .list-group-item-heading,
button.list-group-item-warning .list-group-item-heading {
  color: inherit;
}
a.list-group-item-warning:hover,
button.list-group-item-warning:hover,
a.list-group-item-warning:focus,
button.list-group-item-warning:focus {
  color: #8a6d3b;
  background-color: #faf2cc;
}
a.list-group-item-warning.active,
button.list-group-item-warning.active,
a.list-group-item-warning.active:hover,
button.list-group-item-warning.active:hover,
a.list-group-item-warning.active:focus,
button.list-group-item-warning.active:focus {
  color: #fff;
  background-color: #8a6d3b;
  border-color: #8a6d3b;
}
.list-group-item-danger {
  color: #a94442;
  background-color: #f2dede;
}
a.list-group-item-danger,
button.list-group-item-danger {
  color: #a94442;
}
a.list-group-item-danger .list-group-item-heading,
button.list-group-item-danger .list-group-item-heading {
  color: inherit;
}
a.list-group-item-danger:hover,
button.list-group-item-danger:hover,
a.list-group-item-danger:focus,
button.list-group-item-danger:focus {
  color: #a94442;
  background-color: #ebcccc;
}
a.list-group-item-danger.active,
button.list-group-item-danger.active,
a.list-group-item-danger.active:hover,
button.list-group-item-danger.active:hover,
a.list-group-item-danger.active:focus,
button.list-group-item-danger.active:focus {
  color: #fff;
  background-color: #a94442;
  border-color: #a94442;
}
.list-group-item-heading {
  margin-top: 0;
  margin-bottom: 5px;
}
.list-group-item-text {
  margin-bottom: 0;
  line-height: 1.3;
}
.panel {
  margin-bottom: 18px;
  background-color: #fff;
  border: 1px solid transparent;
  border-radius: 2px;
  -webkit-box-shadow: 0 1px 1px rgba(0, 0, 0, 0.05);
  box-shadow: 0 1px 1px rgba(0, 0, 0, 0.05);
}
.panel-body {
  padding: 15px;
}
.panel-heading {
  padding: 10px 15px;
  border-bottom: 1px solid transparent;
  border-top-right-radius: 1px;
  border-top-left-radius: 1px;
}
.panel-heading > .dropdown .dropdown-toggle {
  color: inherit;
}
.panel-title {
  margin-top: 0;
  margin-bottom: 0;
  font-size: 15px;
  color: inherit;
}
.panel-title > a,
.panel-title > small,
.panel-title > .small,
.panel-title > small > a,
.panel-title > .small > a {
  color: inherit;
}
.panel-footer {
  padding: 10px 15px;
  background-color: #f5f5f5;
  border-top: 1px solid #ddd;
  border-bottom-right-radius: 1px;
  border-bottom-left-radius: 1px;
}
.panel > .list-group,
.panel > .panel-collapse > .list-group {
  margin-bottom: 0;
}
.panel > .list-group .list-group-item,
.panel > .panel-collapse > .list-group .list-group-item {
  border-width: 1px 0;
  border-radius: 0;
}
.panel > .list-group:first-child .list-group-item:first-child,
.panel > .panel-collapse > .list-group:first-child .list-group-item:first-child {
  border-top: 0;
  border-top-right-radius: 1px;
  border-top-left-radius: 1px;
}
.panel > .list-group:last-child .list-group-item:last-child,
.panel > .panel-collapse > .list-group:last-child .list-group-item:last-child {
  border-bottom: 0;
  border-bottom-right-radius: 1px;
  border-bottom-left-radius: 1px;
}
.panel > .panel-heading + .panel-collapse > .list-group .list-group-item:first-child {
  border-top-right-radius: 0;
  border-top-left-radius: 0;
}
.panel-heading + .list-group .list-group-item:first-child {
  border-top-width: 0;
}
.list-group + .panel-footer {
  border-top-width: 0;
}
.panel > .table,
.panel > .table-responsive > .table,
.panel > .panel-collapse > .table {
  margin-bottom: 0;
}
.panel > .table caption,
.panel > .table-responsive > .table caption,
.panel > .panel-collapse > .table caption {
  padding-left: 15px;
  padding-right: 15px;
}
.panel > .table:first-child,
.panel > .table-responsive:first-child > .table:first-child {
  border-top-right-radius: 1px;
  border-top-left-radius: 1px;
}
.panel > .table:first-child > thead:first-child > tr:first-child,
.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child,
.panel > .table:first-child > tbody:first-child > tr:first-child,
.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child {
  border-top-left-radius: 1px;
  border-top-right-radius: 1px;
}
.panel > .table:first-child > thead:first-child > tr:first-child td:first-child,
.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child td:first-child,
.panel > .table:first-child > tbody:first-child > tr:first-child td:first-child,
.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child td:first-child,
.panel > .table:first-child > thead:first-child > tr:first-child th:first-child,
.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child th:first-child,
.panel > .table:first-child > tbody:first-child > tr:first-child th:first-child,
.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child th:first-child {
  border-top-left-radius: 1px;
}
.panel > .table:first-child > thead:first-child > tr:first-child td:last-child,
.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child td:last-child,
.panel > .table:first-child > tbody:first-child > tr:first-child td:last-child,
.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child td:last-child,
.panel > .table:first-child > thead:first-child > tr:first-child th:last-child,
.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child th:last-child,
.panel > .table:first-child > tbody:first-child > tr:first-child th:last-child,
.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child th:last-child {
  border-top-right-radius: 1px;
}
.panel > .table:last-child,
.panel > .table-responsive:last-child > .table:last-child {
  border-bottom-right-radius: 1px;
  border-bottom-left-radius: 1px;
}
.panel > .table:last-child > tbody:last-child > tr:last-child,
.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child,
.panel > .table:last-child > tfoot:last-child > tr:last-child,
.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child {
  border-bottom-left-radius: 1px;
  border-bottom-right-radius: 1px;
}
.panel > .table:last-child > tbody:last-child > tr:last-child td:first-child,
.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child td:first-child,
.panel > .table:last-child > tfoot:last-child > tr:last-child td:first-child,
.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child td:first-child,
.panel > .table:last-child > tbody:last-child > tr:last-child th:first-child,
.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child th:first-child,
.panel > .table:last-child > tfoot:last-child > tr:last-child th:first-child,
.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child th:first-child {
  border-bottom-left-radius: 1px;
}
.panel > .table:last-child > tbody:last-child > tr:last-child td:last-child,
.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child td:last-child,
.panel > .table:last-child > tfoot:last-child > tr:last-child td:last-child,
.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child td:last-child,
.panel > .table:last-child > tbody:last-child > tr:last-child th:last-child,
.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child th:last-child,
.panel > .table:last-child > tfoot:last-child > tr:last-child th:last-child,
.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child th:last-child {
  border-bottom-right-radius: 1px;
}
.panel > .panel-body + .table,
.panel > .panel-body + .table-responsive,
.panel > .table + .panel-body,
.panel > .table-responsive + .panel-body {
  border-top: 1px solid #ddd;
}
.panel > .table > tbody:first-child > tr:first-child th,
.panel > .table > tbody:first-child > tr:first-child td {
  border-top: 0;
}
.panel > .table-bordered,
.panel > .table-responsive > .table-bordered {
  border: 0;
}
.panel > .table-bordered > thead > tr > th:first-child,
.panel > .table-responsive > .table-bordered > thead > tr > th:first-child,
.panel > .table-bordered > tbody > tr > th:first-child,
.panel > .table-responsive > .table-bordered > tbody > tr > th:first-child,
.panel > .table-bordered > tfoot > tr > th:first-child,
.panel > .table-responsive > .table-bordered > tfoot > tr > th:first-child,
.panel > .table-bordered > thead > tr > td:first-child,
.panel > .table-responsive > .table-bordered > thead > tr > td:first-child,
.panel > .table-bordered > tbody > tr > td:first-child,
.panel > .table-responsive > .table-bordered > tbody > tr > td:first-child,
.panel > .table-bordered > tfoot > tr > td:first-child,
.panel > .table-responsive > .table-bordered > tfoot > tr > td:first-child {
  border-left: 0;
}
.panel > .table-bordered > thead > tr > th:last-child,
.panel > .table-responsive > .table-bordered > thead > tr > th:last-child,
.panel > .table-bordered > tbody > tr > th:last-child,
.panel > .table-responsive > .table-bordered > tbody > tr > th:last-child,
.panel > .table-bordered > tfoot > tr > th:last-child,
.panel > .table-responsive > .table-bordered > tfoot > tr > th:last-child,
.panel > .table-bordered > thead > tr > td:last-child,
.panel > .table-responsive > .table-bordered > thead > tr > td:last-child,
.panel > .table-bordered > tbody > tr > td:last-child,
.panel > .table-responsive > .table-bordered > tbody > tr > td:last-child,
.panel > .table-bordered > tfoot > tr > td:last-child,
.panel > .table-responsive > .table-bordered > tfoot > tr > td:last-child {
  border-right: 0;
}
.panel > .table-bordered > thead > tr:first-child > td,
.panel > .table-responsive > .table-bordered > thead > tr:first-child > td,
.panel > .table-bordered > tbody > tr:first-child > td,
.panel > .table-responsive > .table-bordered > tbody > tr:first-child > td,
.panel > .table-bordered > thead > tr:first-child > th,
.panel > .table-responsive > .table-bordered > thead > tr:first-child > th,
.panel > .table-bordered > tbody > tr:first-child > th,
.panel > .table-responsive > .table-bordered > tbody > tr:first-child > th {
  border-bottom: 0;
}
.panel > .table-bordered > tbody > tr:last-child > td,
.panel > .table-responsive > .table-bordered > tbody > tr:last-child > td,
.panel > .table-bordered > tfoot > tr:last-child > td,
.panel > .table-responsive > .table-bordered > tfoot > tr:last-child > td,
.panel > .table-bordered > tbody > tr:last-child > th,
.panel > .table-responsive > .table-bordered > tbody > tr:last-child > th,
.panel > .table-bordered > tfoot > tr:last-child > th,
.panel > .table-responsive > .table-bordered > tfoot > tr:last-child > th {
  border-bottom: 0;
}
.panel > .table-responsive {
  border: 0;
  margin-bottom: 0;
}
.panel-group {
  margin-bottom: 18px;
}
.panel-group .panel {
  margin-bottom: 0;
  border-radius: 2px;
}
.panel-group .panel + .panel {
  margin-top: 5px;
}
.panel-group .panel-heading {
  border-bottom: 0;
}
.panel-group .panel-heading + .panel-collapse > .panel-body,
.panel-group .panel-heading + .panel-collapse > .list-group {
  border-top: 1px solid #ddd;
}
.panel-group .panel-footer {
  border-top: 0;
}
.panel-group .panel-footer + .panel-collapse .panel-body {
  border-bottom: 1px solid #ddd;
}
.panel-default {
  border-color: #ddd;
}
.panel-default > .panel-heading {
  color: #333333;
  background-color: #f5f5f5;
  border-color: #ddd;
}
.panel-default > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #ddd;
}
.panel-default > .panel-heading .badge {
  color: #f5f5f5;
  background-color: #333333;
}
.panel-default > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #ddd;
}
.panel-primary {
  border-color: #337ab7;
}
.panel-primary > .panel-heading {
  color: #fff;
  background-color: #337ab7;
  border-color: #337ab7;
}
.panel-primary > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #337ab7;
}
.panel-primary > .panel-heading .badge {
  color: #337ab7;
  background-color: #fff;
}
.panel-primary > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #337ab7;
}
.panel-success {
  border-color: #d6e9c6;
}
.panel-success > .panel-heading {
  color: #3c763d;
  background-color: #dff0d8;
  border-color: #d6e9c6;
}
.panel-success > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #d6e9c6;
}
.panel-success > .panel-heading .badge {
  color: #dff0d8;
  background-color: #3c763d;
}
.panel-success > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #d6e9c6;
}
.panel-info {
  border-color: #bce8f1;
}
.panel-info > .panel-heading {
  color: #31708f;
  background-color: #d9edf7;
  border-color: #bce8f1;
}
.panel-info > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #bce8f1;
}
.panel-info > .panel-heading .badge {
  color: #d9edf7;
  background-color: #31708f;
}
.panel-info > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #bce8f1;
}
.panel-warning {
  border-color: #faebcc;
}
.panel-warning > .panel-heading {
  color: #8a6d3b;
  background-color: #fcf8e3;
  border-color: #faebcc;
}
.panel-warning > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #faebcc;
}
.panel-warning > .panel-heading .badge {
  color: #fcf8e3;
  background-color: #8a6d3b;
}
.panel-warning > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #faebcc;
}
.panel-danger {
  border-color: #ebccd1;
}
.panel-danger > .panel-heading {
  color: #a94442;
  background-color: #f2dede;
  border-color: #ebccd1;
}
.panel-danger > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #ebccd1;
}
.panel-danger > .panel-heading .badge {
  color: #f2dede;
  background-color: #a94442;
}
.panel-danger > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #ebccd1;
}
.embed-responsive {
  position: relative;
  display: block;
  height: 0;
  padding: 0;
  overflow: hidden;
}
.embed-responsive .embed-responsive-item,
.embed-responsive iframe,
.embed-responsive embed,
.embed-responsive object,
.embed-responsive video {
  position: absolute;
  top: 0;
  left: 0;
  bottom: 0;
  height: 100%;
  width: 100%;
  border: 0;
}
.embed-responsive-16by9 {
  padding-bottom: 56.25%;
}
.embed-responsive-4by3 {
  padding-bottom: 75%;
}
.well {
  min-height: 20px;
  padding: 19px;
  margin-bottom: 20px;
  background-color: #f5f5f5;
  border: 1px solid #e3e3e3;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.05);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.05);
}
.well blockquote {
  border-color: #ddd;
  border-color: rgba(0, 0, 0, 0.15);
}
.well-lg {
  padding: 24px;
  border-radius: 3px;
}
.well-sm {
  padding: 9px;
  border-radius: 1px;
}
.close {
  float: right;
  font-size: 19.5px;
  font-weight: bold;
  line-height: 1;
  color: #000;
  text-shadow: 0 1px 0 #fff;
  opacity: 0.2;
  filter: alpha(opacity=20);
}
.close:hover,
.close:focus {
  color: #000;
  text-decoration: none;
  cursor: pointer;
  opacity: 0.5;
  filter: alpha(opacity=50);
}
button.close {
  padding: 0;
  cursor: pointer;
  background: transparent;
  border: 0;
  -webkit-appearance: none;
}
.modal-open {
  overflow: hidden;
}
.modal {
  display: none;
  overflow: hidden;
  position: fixed;
  top: 0;
  right: 0;
  bottom: 0;
  left: 0;
  z-index: 1050;
  -webkit-overflow-scrolling: touch;
  outline: 0;
}
.modal.fade .modal-dialog {
  -webkit-transform: translate(0, -25%);
  -ms-transform: translate(0, -25%);
  -o-transform: translate(0, -25%);
  transform: translate(0, -25%);
  -webkit-transition: -webkit-transform 0.3s ease-out;
  -moz-transition: -moz-transform 0.3s ease-out;
  -o-transition: -o-transform 0.3s ease-out;
  transition: transform 0.3s ease-out;
}
.modal.in .modal-dialog {
  -webkit-transform: translate(0, 0);
  -ms-transform: translate(0, 0);
  -o-transform: translate(0, 0);
  transform: translate(0, 0);
}
.modal-open .modal {
  overflow-x: hidden;
  overflow-y: auto;
}
.modal-dialog {
  position: relative;
  width: auto;
  margin: 10px;
}
.modal-content {
  position: relative;
  background-color: #fff;
  border: 1px solid #999;
  border: 1px solid rgba(0, 0, 0, 0.2);
  border-radius: 3px;
  -webkit-box-shadow: 0 3px 9px rgba(0, 0, 0, 0.5);
  box-shadow: 0 3px 9px rgba(0, 0, 0, 0.5);
  background-clip: padding-box;
  outline: 0;
}
.modal-backdrop {
  position: fixed;
  top: 0;
  right: 0;
  bottom: 0;
  left: 0;
  z-index: 1040;
  background-color: #000;
}
.modal-backdrop.fade {
  opacity: 0;
  filter: alpha(opacity=0);
}
.modal-backdrop.in {
  opacity: 0.5;
  filter: alpha(opacity=50);
}
.modal-header {
  padding: 15px;
  border-bottom: 1px solid #e5e5e5;
}
.modal-header .close {
  margin-top: -2px;
}
.modal-title {
  margin: 0;
  line-height: 1.42857143;
}
.modal-body {
  position: relative;
  padding: 15px;
}
.modal-footer {
  padding: 15px;
  text-align: right;
  border-top: 1px solid #e5e5e5;
}
.modal-footer .btn + .btn {
  margin-left: 5px;
  margin-bottom: 0;
}
.modal-footer .btn-group .btn + .btn {
  margin-left: -1px;
}
.modal-footer .btn-block + .btn-block {
  margin-left: 0;
}
.modal-scrollbar-measure {
  position: absolute;
  top: -9999px;
  width: 50px;
  height: 50px;
  overflow: scroll;
}
@media (min-width: 768px) {
  .modal-dialog {
    width: 600px;
    margin: 30px auto;
  }
  .modal-content {
    -webkit-box-shadow: 0 5px 15px rgba(0, 0, 0, 0.5);
    box-shadow: 0 5px 15px rgba(0, 0, 0, 0.5);
  }
  .modal-sm {
    width: 300px;
  }
}
@media (min-width: 992px) {
  .modal-lg {
    width: 900px;
  }
}
.tooltip {
  position: absolute;
  z-index: 1070;
  display: block;
  font-family: "Helvetica Neue", Helvetica, Arial, sans-serif;
  font-style: normal;
  font-weight: normal;
  letter-spacing: normal;
  line-break: auto;
  line-height: 1.42857143;
  text-align: left;
  text-align: start;
  text-decoration: none;
  text-shadow: none;
  text-transform: none;
  white-space: normal;
  word-break: normal;
  word-spacing: normal;
  word-wrap: normal;
  font-size: 12px;
  opacity: 0;
  filter: alpha(opacity=0);
}
.tooltip.in {
  opacity: 0.9;
  filter: alpha(opacity=90);
}
.tooltip.top {
  margin-top: -3px;
  padding: 5px 0;
}
.tooltip.right {
  margin-left: 3px;
  padding: 0 5px;
}
.tooltip.bottom {
  margin-top: 3px;
  padding: 5px 0;
}
.tooltip.left {
  margin-left: -3px;
  padding: 0 5px;
}
.tooltip-inner {
  max-width: 200px;
  padding: 3px 8px;
  color: #fff;
  text-align: center;
  background-color: #000;
  border-radius: 2px;
}
.tooltip-arrow {
  position: absolute;
  width: 0;
  height: 0;
  border-color: transparent;
  border-style: solid;
}
.tooltip.top .tooltip-arrow {
  bottom: 0;
  left: 50%;
  margin-left: -5px;
  border-width: 5px 5px 0;
  border-top-color: #000;
}
.tooltip.top-left .tooltip-arrow {
  bottom: 0;
  right: 5px;
  margin-bottom: -5px;
  border-width: 5px 5px 0;
  border-top-color: #000;
}
.tooltip.top-right .tooltip-arrow {
  bottom: 0;
  left: 5px;
  margin-bottom: -5px;
  border-width: 5px 5px 0;
  border-top-color: #000;
}
.tooltip.right .tooltip-arrow {
  top: 50%;
  left: 0;
  margin-top: -5px;
  border-width: 5px 5px 5px 0;
  border-right-color: #000;
}
.tooltip.left .tooltip-arrow {
  top: 50%;
  right: 0;
  margin-top: -5px;
  border-width: 5px 0 5px 5px;
  border-left-color: #000;
}
.tooltip.bottom .tooltip-arrow {
  top: 0;
  left: 50%;
  margin-left: -5px;
  border-width: 0 5px 5px;
  border-bottom-color: #000;
}
.tooltip.bottom-left .tooltip-arrow {
  top: 0;
  right: 5px;
  margin-top: -5px;
  border-width: 0 5px 5px;
  border-bottom-color: #000;
}
.tooltip.bottom-right .tooltip-arrow {
  top: 0;
  left: 5px;
  margin-top: -5px;
  border-width: 0 5px 5px;
  border-bottom-color: #000;
}
.popover {
  position: absolute;
  top: 0;
  left: 0;
  z-index: 1060;
  display: none;
  max-width: 276px;
  padding: 1px;
  font-family: "Helvetica Neue", Helvetica, Arial, sans-serif;
  font-style: normal;
  font-weight: normal;
  letter-spacing: normal;
  line-break: auto;
  line-height: 1.42857143;
  text-align: left;
  text-align: start;
  text-decoration: none;
  text-shadow: none;
  text-transform: none;
  white-space: normal;
  word-break: normal;
  word-spacing: normal;
  word-wrap: normal;
  font-size: 13px;
  background-color: #fff;
  background-clip: padding-box;
  border: 1px solid #ccc;
  border: 1px solid rgba(0, 0, 0, 0.2);
  border-radius: 3px;
  -webkit-box-shadow: 0 5px 10px rgba(0, 0, 0, 0.2);
  box-shadow: 0 5px 10px rgba(0, 0, 0, 0.2);
}
.popover.top {
  margin-top: -10px;
}
.popover.right {
  margin-left: 10px;
}
.popover.bottom {
  margin-top: 10px;
}
.popover.left {
  margin-left: -10px;
}
.popover-title {
  margin: 0;
  padding: 8px 14px;
  font-size: 13px;
  background-color: #f7f7f7;
  border-bottom: 1px solid #ebebeb;
  border-radius: 2px 2px 0 0;
}
.popover-content {
  padding: 9px 14px;
}
.popover > .arrow,
.popover > .arrow:after {
  position: absolute;
  display: block;
  width: 0;
  height: 0;
  border-color: transparent;
  border-style: solid;
}
.popover > .arrow {
  border-width: 11px;
}
.popover > .arrow:after {
  border-width: 10px;
  content: "";
}
.popover.top > .arrow {
  left: 50%;
  margin-left: -11px;
  border-bottom-width: 0;
  border-top-color: #999999;
  border-top-color: rgba(0, 0, 0, 0.25);
  bottom: -11px;
}
.popover.top > .arrow:after {
  content: " ";
  bottom: 1px;
  margin-left: -10px;
  border-bottom-width: 0;
  border-top-color: #fff;
}
.popover.right > .arrow {
  top: 50%;
  left: -11px;
  margin-top: -11px;
  border-left-width: 0;
  border-right-color: #999999;
  border-right-color: rgba(0, 0, 0, 0.25);
}
.popover.right > .arrow:after {
  content: " ";
  left: 1px;
  bottom: -10px;
  border-left-width: 0;
  border-right-color: #fff;
}
.popover.bottom > .arrow {
  left: 50%;
  margin-left: -11px;
  border-top-width: 0;
  border-bottom-color: #999999;
  border-bottom-color: rgba(0, 0, 0, 0.25);
  top: -11px;
}
.popover.bottom > .arrow:after {
  content: " ";
  top: 1px;
  margin-left: -10px;
  border-top-width: 0;
  border-bottom-color: #fff;
}
.popover.left > .arrow {
  top: 50%;
  right: -11px;
  margin-top: -11px;
  border-right-width: 0;
  border-left-color: #999999;
  border-left-color: rgba(0, 0, 0, 0.25);
}
.popover.left > .arrow:after {
  content: " ";
  right: 1px;
  border-right-width: 0;
  border-left-color: #fff;
  bottom: -10px;
}
.carousel {
  position: relative;
}
.carousel-inner {
  position: relative;
  overflow: hidden;
  width: 100%;
}
.carousel-inner > .item {
  display: none;
  position: relative;
  -webkit-transition: 0.6s ease-in-out left;
  -o-transition: 0.6s ease-in-out left;
  transition: 0.6s ease-in-out left;
}
.carousel-inner > .item > img,
.carousel-inner > .item > a > img {
  line-height: 1;
}
@media all and (transform-3d), (-webkit-transform-3d) {
  .carousel-inner > .item {
    -webkit-transition: -webkit-transform 0.6s ease-in-out;
    -moz-transition: -moz-transform 0.6s ease-in-out;
    -o-transition: -o-transform 0.6s ease-in-out;
    transition: transform 0.6s ease-in-out;
    -webkit-backface-visibility: hidden;
    -moz-backface-visibility: hidden;
    backface-visibility: hidden;
    -webkit-perspective: 1000px;
    -moz-perspective: 1000px;
    perspective: 1000px;
  }
  .carousel-inner > .item.next,
  .carousel-inner > .item.active.right {
    -webkit-transform: translate3d(100%, 0, 0);
    transform: translate3d(100%, 0, 0);
    left: 0;
  }
  .carousel-inner > .item.prev,
  .carousel-inner > .item.active.left {
    -webkit-transform: translate3d(-100%, 0, 0);
    transform: translate3d(-100%, 0, 0);
    left: 0;
  }
  .carousel-inner > .item.next.left,
  .carousel-inner > .item.prev.right,
  .carousel-inner > .item.active {
    -webkit-transform: translate3d(0, 0, 0);
    transform: translate3d(0, 0, 0);
    left: 0;
  }
}
.carousel-inner > .active,
.carousel-inner > .next,
.carousel-inner > .prev {
  display: block;
}
.carousel-inner > .active {
  left: 0;
}
.carousel-inner > .next,
.carousel-inner > .prev {
  position: absolute;
  top: 0;
  width: 100%;
}
.carousel-inner > .next {
  left: 100%;
}
.carousel-inner > .prev {
  left: -100%;
}
.carousel-inner > .next.left,
.carousel-inner > .prev.right {
  left: 0;
}
.carousel-inner > .active.left {
  left: -100%;
}
.carousel-inner > .active.right {
  left: 100%;
}
.carousel-control {
  position: absolute;
  top: 0;
  left: 0;
  bottom: 0;
  width: 15%;
  opacity: 0.5;
  filter: alpha(opacity=50);
  font-size: 20px;
  color: #fff;
  text-align: center;
  text-shadow: 0 1px 2px rgba(0, 0, 0, 0.6);
  background-color: rgba(0, 0, 0, 0);
}
.carousel-control.left {
  background-image: -webkit-linear-gradient(left, rgba(0, 0, 0, 0.5) 0%, rgba(0, 0, 0, 0.0001) 100%);
  background-image: -o-linear-gradient(left, rgba(0, 0, 0, 0.5) 0%, rgba(0, 0, 0, 0.0001) 100%);
  background-image: linear-gradient(to right, rgba(0, 0, 0, 0.5) 0%, rgba(0, 0, 0, 0.0001) 100%);
  background-repeat: repeat-x;
  filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#80000000', endColorstr='#00000000', GradientType=1);
}
.carousel-control.right {
  left: auto;
  right: 0;
  background-image: -webkit-linear-gradient(left, rgba(0, 0, 0, 0.0001) 0%, rgba(0, 0, 0, 0.5) 100%);
  background-image: -o-linear-gradient(left, rgba(0, 0, 0, 0.0001) 0%, rgba(0, 0, 0, 0.5) 100%);
  background-image: linear-gradient(to right, rgba(0, 0, 0, 0.0001) 0%, rgba(0, 0, 0, 0.5) 100%);
  background-repeat: repeat-x;
  filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#00000000', endColorstr='#80000000', GradientType=1);
}
.carousel-control:hover,
.carousel-control:focus {
  outline: 0;
  color: #fff;
  text-decoration: none;
  opacity: 0.9;
  filter: alpha(opacity=90);
}
.carousel-control .icon-prev,
.carousel-control .icon-next,
.carousel-control .glyphicon-chevron-left,
.carousel-control .glyphicon-chevron-right {
  position: absolute;
  top: 50%;
  margin-top: -10px;
  z-index: 5;
  display: inline-block;
}
.carousel-control .icon-prev,
.carousel-control .glyphicon-chevron-left {
  left: 50%;
  margin-left: -10px;
}
.carousel-control .icon-next,
.carousel-control .glyphicon-chevron-right {
  right: 50%;
  margin-right: -10px;
}
.carousel-control .icon-prev,
.carousel-control .icon-next {
  width: 20px;
  height: 20px;
  line-height: 1;
  font-family: serif;
}
.carousel-control .icon-prev:before {
  content: '\2039';
}
.carousel-control .icon-next:before {
  content: '\203a';
}
.carousel-indicators {
  position: absolute;
  bottom: 10px;
  left: 50%;
  z-index: 15;
  width: 60%;
  margin-left: -30%;
  padding-left: 0;
  list-style: none;
  text-align: center;
}
.carousel-indicators li {
  display: inline-block;
  width: 10px;
  height: 10px;
  margin: 1px;
  text-indent: -999px;
  border: 1px solid #fff;
  border-radius: 10px;
  cursor: pointer;
  background-color: #000 \9;
  background-color: rgba(0, 0, 0, 0);
}
.carousel-indicators .active {
  margin: 0;
  width: 12px;
  height: 12px;
  background-color: #fff;
}
.carousel-caption {
  position: absolute;
  left: 15%;
  right: 15%;
  bottom: 20px;
  z-index: 10;
  padding-top: 20px;
  padding-bottom: 20px;
  color: #fff;
  text-align: center;
  text-shadow: 0 1px 2px rgba(0, 0, 0, 0.6);
}
.carousel-caption .btn {
  text-shadow: none;
}
@media screen and (min-width: 768px) {
  .carousel-control .glyphicon-chevron-left,
  .carousel-control .glyphicon-chevron-right,
  .carousel-control .icon-prev,
  .carousel-control .icon-next {
    width: 30px;
    height: 30px;
    margin-top: -10px;
    font-size: 30px;
  }
  .carousel-control .glyphicon-chevron-left,
  .carousel-control .icon-prev {
    margin-left: -10px;
  }
  .carousel-control .glyphicon-chevron-right,
  .carousel-control .icon-next {
    margin-right: -10px;
  }
  .carousel-caption {
    left: 20%;
    right: 20%;
    padding-bottom: 30px;
  }
  .carousel-indicators {
    bottom: 20px;
  }
}
.clearfix:before,
.clearfix:after,
.dl-horizontal dd:before,
.dl-horizontal dd:after,
.container:before,
.container:after,
.container-fluid:before,
.container-fluid:after,
.row:before,
.row:after,
.form-horizontal .form-group:before,
.form-horizontal .form-group:after,
.btn-toolbar:before,
.btn-toolbar:after,
.btn-group-vertical > .btn-group:before,
.btn-group-vertical > .btn-group:after,
.nav:before,
.nav:after,
.navbar:before,
.navbar:after,
.navbar-header:before,
.navbar-header:after,
.navbar-collapse:before,
.navbar-collapse:after,
.pager:before,
.pager:after,
.panel-body:before,
.panel-body:after,
.modal-header:before,
.modal-header:after,
.modal-footer:before,
.modal-footer:after,
.item_buttons:before,
.item_buttons:after {
  content: " ";
  display: table;
}
.clearfix:after,
.dl-horizontal dd:after,
.container:after,
.container-fluid:after,
.row:after,
.form-horizontal .form-group:after,
.btn-toolbar:after,
.btn-group-vertical > .btn-group:after,
.nav:after,
.navbar:after,
.navbar-header:after,
.navbar-collapse:after,
.pager:after,
.panel-body:after,
.modal-header:after,
.modal-footer:after,
.item_buttons:after {
  clear: both;
}
.center-block {
  display: block;
  margin-left: auto;
  margin-right: auto;
}
.pull-right {
  float: right !important;
}
.pull-left {
  float: left !important;
}
.hide {
  display: none !important;
}
.show {
  display: block !important;
}
.invisible {
  visibility: hidden;
}
.text-hide {
  font: 0/0 a;
  color: transparent;
  text-shadow: none;
  background-color: transparent;
  border: 0;
}
.hidden {
  display: none !important;
}
.affix {
  position: fixed;
}
@-ms-viewport {
  width: device-width;
}
.visible-xs,
.visible-sm,
.visible-md,
.visible-lg {
  display: none !important;
}
.visible-xs-block,
.visible-xs-inline,
.visible-xs-inline-block,
.visible-sm-block,
.visible-sm-inline,
.visible-sm-inline-block,
.visible-md-block,
.visible-md-inline,
.visible-md-inline-block,
.visible-lg-block,
.visible-lg-inline,
.visible-lg-inline-block {
  display: none !important;
}
@media (max-width: 767px) {
  .visible-xs {
    display: block !important;
  }
  table.visible-xs {
    display: table !important;
  }
  tr.visible-xs {
    display: table-row !important;
  }
  th.visible-xs,
  td.visible-xs {
    display: table-cell !important;
  }
}
@media (max-width: 767px) {
  .visible-xs-block {
    display: block !important;
  }
}
@media (max-width: 767px) {
  .visible-xs-inline {
    display: inline !important;
  }
}
@media (max-width: 767px) {
  .visible-xs-inline-block {
    display: inline-block !important;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  .visible-sm {
    display: block !important;
  }
  table.visible-sm {
    display: table !important;
  }
  tr.visible-sm {
    display: table-row !important;
  }
  th.visible-sm,
  td.visible-sm {
    display: table-cell !important;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  .visible-sm-block {
    display: block !important;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  .visible-sm-inline {
    display: inline !important;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  .visible-sm-inline-block {
    display: inline-block !important;
  }
}
@media (min-width: 992px) and (max-width: 1199px) {
  .visible-md {
    display: block !important;
  }
  table.visible-md {
    display: table !important;
  }
  tr.visible-md {
    display: table-row !important;
  }
  th.visible-md,
  td.visible-md {
    display: table-cell !important;
  }
}
@media (min-width: 992px) and (max-width: 1199px) {
  .visible-md-block {
    display: block !important;
  }
}
@media (min-width: 992px) and (max-width: 1199px) {
  .visible-md-inline {
    display: inline !important;
  }
}
@media (min-width: 992px) and (max-width: 1199px) {
  .visible-md-inline-block {
    display: inline-block !important;
  }
}
@media (min-width: 1200px) {
  .visible-lg {
    display: block !important;
  }
  table.visible-lg {
    display: table !important;
  }
  tr.visible-lg {
    display: table-row !important;
  }
  th.visible-lg,
  td.visible-lg {
    display: table-cell !important;
  }
}
@media (min-width: 1200px) {
  .visible-lg-block {
    display: block !important;
  }
}
@media (min-width: 1200px) {
  .visible-lg-inline {
    display: inline !important;
  }
}
@media (min-width: 1200px) {
  .visible-lg-inline-block {
    display: inline-block !important;
  }
}
@media (max-width: 767px) {
  .hidden-xs {
    display: none !important;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  .hidden-sm {
    display: none !important;
  }
}
@media (min-width: 992px) and (max-width: 1199px) {
  .hidden-md {
    display: none !important;
  }
}
@media (min-width: 1200px) {
  .hidden-lg {
    display: none !important;
  }
}
.visible-print {
  display: none !important;
}
@media print {
  .visible-print {
    display: block !important;
  }
  table.visible-print {
    display: table !important;
  }
  tr.visible-print {
    display: table-row !important;
  }
  th.visible-print,
  td.visible-print {
    display: table-cell !important;
  }
}
.visible-print-block {
  display: none !important;
}
@media print {
  .visible-print-block {
    display: block !important;
  }
}
.visible-print-inline {
  display: none !important;
}
@media print {
  .visible-print-inline {
    display: inline !important;
  }
}
.visible-print-inline-block {
  display: none !important;
}
@media print {
  .visible-print-inline-block {
    display: inline-block !important;
  }
}
@media print {
  .hidden-print {
    display: none !important;
  }
}
/*!
*
* Font Awesome
*
*/
/*!
 *  Font Awesome 4.7.0 by @davegandy - http://fontawesome.io - @fontawesome
 *  License - http://fontawesome.io/license (Font: SIL OFL 1.1, CSS: MIT License)
 */
/* FONT PATH
 * -------------------------- */
@font-face {
  font-family: 'FontAwesome';
  src: url('../components/font-awesome/fonts/fontawesome-webfont.eot?v=4.7.0');
  src: url('../components/font-awesome/fonts/fontawesome-webfont.eot?#iefix&v=4.7.0') format('embedded-opentype'), url('../components/font-awesome/fonts/fontawesome-webfont.woff2?v=4.7.0') format('woff2'), url('../components/font-awesome/fonts/fontawesome-webfont.woff?v=4.7.0') format('woff'), url('../components/font-awesome/fonts/fontawesome-webfont.ttf?v=4.7.0') format('truetype'), url('../components/font-awesome/fonts/fontawesome-webfont.svg?v=4.7.0#fontawesomeregular') format('svg');
  font-weight: normal;
  font-style: normal;
}
.fa {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
}
/* makes the font 33% larger relative to the icon container */
.fa-lg {
  font-size: 1.33333333em;
  line-height: 0.75em;
  vertical-align: -15%;
}
.fa-2x {
  font-size: 2em;
}
.fa-3x {
  font-size: 3em;
}
.fa-4x {
  font-size: 4em;
}
.fa-5x {
  font-size: 5em;
}
.fa-fw {
  width: 1.28571429em;
  text-align: center;
}
.fa-ul {
  padding-left: 0;
  margin-left: 2.14285714em;
  list-style-type: none;
}
.fa-ul > li {
  position: relative;
}
.fa-li {
  position: absolute;
  left: -2.14285714em;
  width: 2.14285714em;
  top: 0.14285714em;
  text-align: center;
}
.fa-li.fa-lg {
  left: -1.85714286em;
}
.fa-border {
  padding: .2em .25em .15em;
  border: solid 0.08em #eee;
  border-radius: .1em;
}
.fa-pull-left {
  float: left;
}
.fa-pull-right {
  float: right;
}
.fa.fa-pull-left {
  margin-right: .3em;
}
.fa.fa-pull-right {
  margin-left: .3em;
}
/* Deprecated as of 4.4.0 */
.pull-right {
  float: right;
}
.pull-left {
  float: left;
}
.fa.pull-left {
  margin-right: .3em;
}
.fa.pull-right {
  margin-left: .3em;
}
.fa-spin {
  -webkit-animation: fa-spin 2s infinite linear;
  animation: fa-spin 2s infinite linear;
}
.fa-pulse {
  -webkit-animation: fa-spin 1s infinite steps(8);
  animation: fa-spin 1s infinite steps(8);
}
@-webkit-keyframes fa-spin {
  0% {
    -webkit-transform: rotate(0deg);
    transform: rotate(0deg);
  }
  100% {
    -webkit-transform: rotate(359deg);
    transform: rotate(359deg);
  }
}
@keyframes fa-spin {
  0% {
    -webkit-transform: rotate(0deg);
    transform: rotate(0deg);
  }
  100% {
    -webkit-transform: rotate(359deg);
    transform: rotate(359deg);
  }
}
.fa-rotate-90 {
  -ms-filter: "progid:DXImageTransform.Microsoft.BasicImage(rotation=1)";
  -webkit-transform: rotate(90deg);
  -ms-transform: rotate(90deg);
  transform: rotate(90deg);
}
.fa-rotate-180 {
  -ms-filter: "progid:DXImageTransform.Microsoft.BasicImage(rotation=2)";
  -webkit-transform: rotate(180deg);
  -ms-transform: rotate(180deg);
  transform: rotate(180deg);
}
.fa-rotate-270 {
  -ms-filter: "progid:DXImageTransform.Microsoft.BasicImage(rotation=3)";
  -webkit-transform: rotate(270deg);
  -ms-transform: rotate(270deg);
  transform: rotate(270deg);
}
.fa-flip-horizontal {
  -ms-filter: "progid:DXImageTransform.Microsoft.BasicImage(rotation=0, mirror=1)";
  -webkit-transform: scale(-1, 1);
  -ms-transform: scale(-1, 1);
  transform: scale(-1, 1);
}
.fa-flip-vertical {
  -ms-filter: "progid:DXImageTransform.Microsoft.BasicImage(rotation=2, mirror=1)";
  -webkit-transform: scale(1, -1);
  -ms-transform: scale(1, -1);
  transform: scale(1, -1);
}
:root .fa-rotate-90,
:root .fa-rotate-180,
:root .fa-rotate-270,
:root .fa-flip-horizontal,
:root .fa-flip-vertical {
  filter: none;
}
.fa-stack {
  position: relative;
  display: inline-block;
  width: 2em;
  height: 2em;
  line-height: 2em;
  vertical-align: middle;
}
.fa-stack-1x,
.fa-stack-2x {
  position: absolute;
  left: 0;
  width: 100%;
  text-align: center;
}
.fa-stack-1x {
  line-height: inherit;
}
.fa-stack-2x {
  font-size: 2em;
}
.fa-inverse {
  color: #fff;
}
/* Font Awesome uses the Unicode Private Use Area (PUA) to ensure screen
   readers do not read off random characters that represent icons */
.fa-glass:before {
  content: "\f000";
}
.fa-music:before {
  content: "\f001";
}
.fa-search:before {
  content: "\f002";
}
.fa-envelope-o:before {
  content: "\f003";
}
.fa-heart:before {
  content: "\f004";
}
.fa-star:before {
  content: "\f005";
}
.fa-star-o:before {
  content: "\f006";
}
.fa-user:before {
  content: "\f007";
}
.fa-film:before {
  content: "\f008";
}
.fa-th-large:before {
  content: "\f009";
}
.fa-th:before {
  content: "\f00a";
}
.fa-th-list:before {
  content: "\f00b";
}
.fa-check:before {
  content: "\f00c";
}
.fa-remove:before,
.fa-close:before,
.fa-times:before {
  content: "\f00d";
}
.fa-search-plus:before {
  content: "\f00e";
}
.fa-search-minus:before {
  content: "\f010";
}
.fa-power-off:before {
  content: "\f011";
}
.fa-signal:before {
  content: "\f012";
}
.fa-gear:before,
.fa-cog:before {
  content: "\f013";
}
.fa-trash-o:before {
  content: "\f014";
}
.fa-home:before {
  content: "\f015";
}
.fa-file-o:before {
  content: "\f016";
}
.fa-clock-o:before {
  content: "\f017";
}
.fa-road:before {
  content: "\f018";
}
.fa-download:before {
  content: "\f019";
}
.fa-arrow-circle-o-down:before {
  content: "\f01a";
}
.fa-arrow-circle-o-up:before {
  content: "\f01b";
}
.fa-inbox:before {
  content: "\f01c";
}
.fa-play-circle-o:before {
  content: "\f01d";
}
.fa-rotate-right:before,
.fa-repeat:before {
  content: "\f01e";
}
.fa-refresh:before {
  content: "\f021";
}
.fa-list-alt:before {
  content: "\f022";
}
.fa-lock:before {
  content: "\f023";
}
.fa-flag:before {
  content: "\f024";
}
.fa-headphones:before {
  content: "\f025";
}
.fa-volume-off:before {
  content: "\f026";
}
.fa-volume-down:before {
  content: "\f027";
}
.fa-volume-up:before {
  content: "\f028";
}
.fa-qrcode:before {
  content: "\f029";
}
.fa-barcode:before {
  content: "\f02a";
}
.fa-tag:before {
  content: "\f02b";
}
.fa-tags:before {
  content: "\f02c";
}
.fa-book:before {
  content: "\f02d";
}
.fa-bookmark:before {
  content: "\f02e";
}
.fa-print:before {
  content: "\f02f";
}
.fa-camera:before {
  content: "\f030";
}
.fa-font:before {
  content: "\f031";
}
.fa-bold:before {
  content: "\f032";
}
.fa-italic:before {
  content: "\f033";
}
.fa-text-height:before {
  content: "\f034";
}
.fa-text-width:before {
  content: "\f035";
}
.fa-align-left:before {
  content: "\f036";
}
.fa-align-center:before {
  content: "\f037";
}
.fa-align-right:before {
  content: "\f038";
}
.fa-align-justify:before {
  content: "\f039";
}
.fa-list:before {
  content: "\f03a";
}
.fa-dedent:before,
.fa-outdent:before {
  content: "\f03b";
}
.fa-indent:before {
  content: "\f03c";
}
.fa-video-camera:before {
  content: "\f03d";
}
.fa-photo:before,
.fa-image:before,
.fa-picture-o:before {
  content: "\f03e";
}
.fa-pencil:before {
  content: "\f040";
}
.fa-map-marker:before {
  content: "\f041";
}
.fa-adjust:before {
  content: "\f042";
}
.fa-tint:before {
  content: "\f043";
}
.fa-edit:before,
.fa-pencil-square-o:before {
  content: "\f044";
}
.fa-share-square-o:before {
  content: "\f045";
}
.fa-check-square-o:before {
  content: "\f046";
}
.fa-arrows:before {
  content: "\f047";
}
.fa-step-backward:before {
  content: "\f048";
}
.fa-fast-backward:before {
  content: "\f049";
}
.fa-backward:before {
  content: "\f04a";
}
.fa-play:before {
  content: "\f04b";
}
.fa-pause:before {
  content: "\f04c";
}
.fa-stop:before {
  content: "\f04d";
}
.fa-forward:before {
  content: "\f04e";
}
.fa-fast-forward:before {
  content: "\f050";
}
.fa-step-forward:before {
  content: "\f051";
}
.fa-eject:before {
  content: "\f052";
}
.fa-chevron-left:before {
  content: "\f053";
}
.fa-chevron-right:before {
  content: "\f054";
}
.fa-plus-circle:before {
  content: "\f055";
}
.fa-minus-circle:before {
  content: "\f056";
}
.fa-times-circle:before {
  content: "\f057";
}
.fa-check-circle:before {
  content: "\f058";
}
.fa-question-circle:before {
  content: "\f059";
}
.fa-info-circle:before {
  content: "\f05a";
}
.fa-crosshairs:before {
  content: "\f05b";
}
.fa-times-circle-o:before {
  content: "\f05c";
}
.fa-check-circle-o:before {
  content: "\f05d";
}
.fa-ban:before {
  content: "\f05e";
}
.fa-arrow-left:before {
  content: "\f060";
}
.fa-arrow-right:before {
  content: "\f061";
}
.fa-arrow-up:before {
  content: "\f062";
}
.fa-arrow-down:before {
  content: "\f063";
}
.fa-mail-forward:before,
.fa-share:before {
  content: "\f064";
}
.fa-expand:before {
  content: "\f065";
}
.fa-compress:before {
  content: "\f066";
}
.fa-plus:before {
  content: "\f067";
}
.fa-minus:before {
  content: "\f068";
}
.fa-asterisk:before {
  content: "\f069";
}
.fa-exclamation-circle:before {
  content: "\f06a";
}
.fa-gift:before {
  content: "\f06b";
}
.fa-leaf:before {
  content: "\f06c";
}
.fa-fire:before {
  content: "\f06d";
}
.fa-eye:before {
  content: "\f06e";
}
.fa-eye-slash:before {
  content: "\f070";
}
.fa-warning:before,
.fa-exclamation-triangle:before {
  content: "\f071";
}
.fa-plane:before {
  content: "\f072";
}
.fa-calendar:before {
  content: "\f073";
}
.fa-random:before {
  content: "\f074";
}
.fa-comment:before {
  content: "\f075";
}
.fa-magnet:before {
  content: "\f076";
}
.fa-chevron-up:before {
  content: "\f077";
}
.fa-chevron-down:before {
  content: "\f078";
}
.fa-retweet:before {
  content: "\f079";
}
.fa-shopping-cart:before {
  content: "\f07a";
}
.fa-folder:before {
  content: "\f07b";
}
.fa-folder-open:before {
  content: "\f07c";
}
.fa-arrows-v:before {
  content: "\f07d";
}
.fa-arrows-h:before {
  content: "\f07e";
}
.fa-bar-chart-o:before,
.fa-bar-chart:before {
  content: "\f080";
}
.fa-twitter-square:before {
  content: "\f081";
}
.fa-facebook-square:before {
  content: "\f082";
}
.fa-camera-retro:before {
  content: "\f083";
}
.fa-key:before {
  content: "\f084";
}
.fa-gears:before,
.fa-cogs:before {
  content: "\f085";
}
.fa-comments:before {
  content: "\f086";
}
.fa-thumbs-o-up:before {
  content: "\f087";
}
.fa-thumbs-o-down:before {
  content: "\f088";
}
.fa-star-half:before {
  content: "\f089";
}
.fa-heart-o:before {
  content: "\f08a";
}
.fa-sign-out:before {
  content: "\f08b";
}
.fa-linkedin-square:before {
  content: "\f08c";
}
.fa-thumb-tack:before {
  content: "\f08d";
}
.fa-external-link:before {
  content: "\f08e";
}
.fa-sign-in:before {
  content: "\f090";
}
.fa-trophy:before {
  content: "\f091";
}
.fa-github-square:before {
  content: "\f092";
}
.fa-upload:before {
  content: "\f093";
}
.fa-lemon-o:before {
  content: "\f094";
}
.fa-phone:before {
  content: "\f095";
}
.fa-square-o:before {
  content: "\f096";
}
.fa-bookmark-o:before {
  content: "\f097";
}
.fa-phone-square:before {
  content: "\f098";
}
.fa-twitter:before {
  content: "\f099";
}
.fa-facebook-f:before,
.fa-facebook:before {
  content: "\f09a";
}
.fa-github:before {
  content: "\f09b";
}
.fa-unlock:before {
  content: "\f09c";
}
.fa-credit-card:before {
  content: "\f09d";
}
.fa-feed:before,
.fa-rss:before {
  content: "\f09e";
}
.fa-hdd-o:before {
  content: "\f0a0";
}
.fa-bullhorn:before {
  content: "\f0a1";
}
.fa-bell:before {
  content: "\f0f3";
}
.fa-certificate:before {
  content: "\f0a3";
}
.fa-hand-o-right:before {
  content: "\f0a4";
}
.fa-hand-o-left:before {
  content: "\f0a5";
}
.fa-hand-o-up:before {
  content: "\f0a6";
}
.fa-hand-o-down:before {
  content: "\f0a7";
}
.fa-arrow-circle-left:before {
  content: "\f0a8";
}
.fa-arrow-circle-right:before {
  content: "\f0a9";
}
.fa-arrow-circle-up:before {
  content: "\f0aa";
}
.fa-arrow-circle-down:before {
  content: "\f0ab";
}
.fa-globe:before {
  content: "\f0ac";
}
.fa-wrench:before {
  content: "\f0ad";
}
.fa-tasks:before {
  content: "\f0ae";
}
.fa-filter:before {
  content: "\f0b0";
}
.fa-briefcase:before {
  content: "\f0b1";
}
.fa-arrows-alt:before {
  content: "\f0b2";
}
.fa-group:before,
.fa-users:before {
  content: "\f0c0";
}
.fa-chain:before,
.fa-link:before {
  content: "\f0c1";
}
.fa-cloud:before {
  content: "\f0c2";
}
.fa-flask:before {
  content: "\f0c3";
}
.fa-cut:before,
.fa-scissors:before {
  content: "\f0c4";
}
.fa-copy:before,
.fa-files-o:before {
  content: "\f0c5";
}
.fa-paperclip:before {
  content: "\f0c6";
}
.fa-save:before,
.fa-floppy-o:before {
  content: "\f0c7";
}
.fa-square:before {
  content: "\f0c8";
}
.fa-navicon:before,
.fa-reorder:before,
.fa-bars:before {
  content: "\f0c9";
}
.fa-list-ul:before {
  content: "\f0ca";
}
.fa-list-ol:before {
  content: "\f0cb";
}
.fa-strikethrough:before {
  content: "\f0cc";
}
.fa-underline:before {
  content: "\f0cd";
}
.fa-table:before {
  content: "\f0ce";
}
.fa-magic:before {
  content: "\f0d0";
}
.fa-truck:before {
  content: "\f0d1";
}
.fa-pinterest:before {
  content: "\f0d2";
}
.fa-pinterest-square:before {
  content: "\f0d3";
}
.fa-google-plus-square:before {
  content: "\f0d4";
}
.fa-google-plus:before {
  content: "\f0d5";
}
.fa-money:before {
  content: "\f0d6";
}
.fa-caret-down:before {
  content: "\f0d7";
}
.fa-caret-up:before {
  content: "\f0d8";
}
.fa-caret-left:before {
  content: "\f0d9";
}
.fa-caret-right:before {
  content: "\f0da";
}
.fa-columns:before {
  content: "\f0db";
}
.fa-unsorted:before,
.fa-sort:before {
  content: "\f0dc";
}
.fa-sort-down:before,
.fa-sort-desc:before {
  content: "\f0dd";
}
.fa-sort-up:before,
.fa-sort-asc:before {
  content: "\f0de";
}
.fa-envelope:before {
  content: "\f0e0";
}
.fa-linkedin:before {
  content: "\f0e1";
}
.fa-rotate-left:before,
.fa-undo:before {
  content: "\f0e2";
}
.fa-legal:before,
.fa-gavel:before {
  content: "\f0e3";
}
.fa-dashboard:before,
.fa-tachometer:before {
  content: "\f0e4";
}
.fa-comment-o:before {
  content: "\f0e5";
}
.fa-comments-o:before {
  content: "\f0e6";
}
.fa-flash:before,
.fa-bolt:before {
  content: "\f0e7";
}
.fa-sitemap:before {
  content: "\f0e8";
}
.fa-umbrella:before {
  content: "\f0e9";
}
.fa-paste:before,
.fa-clipboard:before {
  content: "\f0ea";
}
.fa-lightbulb-o:before {
  content: "\f0eb";
}
.fa-exchange:before {
  content: "\f0ec";
}
.fa-cloud-download:before {
  content: "\f0ed";
}
.fa-cloud-upload:before {
  content: "\f0ee";
}
.fa-user-md:before {
  content: "\f0f0";
}
.fa-stethoscope:before {
  content: "\f0f1";
}
.fa-suitcase:before {
  content: "\f0f2";
}
.fa-bell-o:before {
  content: "\f0a2";
}
.fa-coffee:before {
  content: "\f0f4";
}
.fa-cutlery:before {
  content: "\f0f5";
}
.fa-file-text-o:before {
  content: "\f0f6";
}
.fa-building-o:before {
  content: "\f0f7";
}
.fa-hospital-o:before {
  content: "\f0f8";
}
.fa-ambulance:before {
  content: "\f0f9";
}
.fa-medkit:before {
  content: "\f0fa";
}
.fa-fighter-jet:before {
  content: "\f0fb";
}
.fa-beer:before {
  content: "\f0fc";
}
.fa-h-square:before {
  content: "\f0fd";
}
.fa-plus-square:before {
  content: "\f0fe";
}
.fa-angle-double-left:before {
  content: "\f100";
}
.fa-angle-double-right:before {
  content: "\f101";
}
.fa-angle-double-up:before {
  content: "\f102";
}
.fa-angle-double-down:before {
  content: "\f103";
}
.fa-angle-left:before {
  content: "\f104";
}
.fa-angle-right:before {
  content: "\f105";
}
.fa-angle-up:before {
  content: "\f106";
}
.fa-angle-down:before {
  content: "\f107";
}
.fa-desktop:before {
  content: "\f108";
}
.fa-laptop:before {
  content: "\f109";
}
.fa-tablet:before {
  content: "\f10a";
}
.fa-mobile-phone:before,
.fa-mobile:before {
  content: "\f10b";
}
.fa-circle-o:before {
  content: "\f10c";
}
.fa-quote-left:before {
  content: "\f10d";
}
.fa-quote-right:before {
  content: "\f10e";
}
.fa-spinner:before {
  content: "\f110";
}
.fa-circle:before {
  content: "\f111";
}
.fa-mail-reply:before,
.fa-reply:before {
  content: "\f112";
}
.fa-github-alt:before {
  content: "\f113";
}
.fa-folder-o:before {
  content: "\f114";
}
.fa-folder-open-o:before {
  content: "\f115";
}
.fa-smile-o:before {
  content: "\f118";
}
.fa-frown-o:before {
  content: "\f119";
}
.fa-meh-o:before {
  content: "\f11a";
}
.fa-gamepad:before {
  content: "\f11b";
}
.fa-keyboard-o:before {
  content: "\f11c";
}
.fa-flag-o:before {
  content: "\f11d";
}
.fa-flag-checkered:before {
  content: "\f11e";
}
.fa-terminal:before {
  content: "\f120";
}
.fa-code:before {
  content: "\f121";
}
.fa-mail-reply-all:before,
.fa-reply-all:before {
  content: "\f122";
}
.fa-star-half-empty:before,
.fa-star-half-full:before,
.fa-star-half-o:before {
  content: "\f123";
}
.fa-location-arrow:before {
  content: "\f124";
}
.fa-crop:before {
  content: "\f125";
}
.fa-code-fork:before {
  content: "\f126";
}
.fa-unlink:before,
.fa-chain-broken:before {
  content: "\f127";
}
.fa-question:before {
  content: "\f128";
}
.fa-info:before {
  content: "\f129";
}
.fa-exclamation:before {
  content: "\f12a";
}
.fa-superscript:before {
  content: "\f12b";
}
.fa-subscript:before {
  content: "\f12c";
}
.fa-eraser:before {
  content: "\f12d";
}
.fa-puzzle-piece:before {
  content: "\f12e";
}
.fa-microphone:before {
  content: "\f130";
}
.fa-microphone-slash:before {
  content: "\f131";
}
.fa-shield:before {
  content: "\f132";
}
.fa-calendar-o:before {
  content: "\f133";
}
.fa-fire-extinguisher:before {
  content: "\f134";
}
.fa-rocket:before {
  content: "\f135";
}
.fa-maxcdn:before {
  content: "\f136";
}
.fa-chevron-circle-left:before {
  content: "\f137";
}
.fa-chevron-circle-right:before {
  content: "\f138";
}
.fa-chevron-circle-up:before {
  content: "\f139";
}
.fa-chevron-circle-down:before {
  content: "\f13a";
}
.fa-html5:before {
  content: "\f13b";
}
.fa-css3:before {
  content: "\f13c";
}
.fa-anchor:before {
  content: "\f13d";
}
.fa-unlock-alt:before {
  content: "\f13e";
}
.fa-bullseye:before {
  content: "\f140";
}
.fa-ellipsis-h:before {
  content: "\f141";
}
.fa-ellipsis-v:before {
  content: "\f142";
}
.fa-rss-square:before {
  content: "\f143";
}
.fa-play-circle:before {
  content: "\f144";
}
.fa-ticket:before {
  content: "\f145";
}
.fa-minus-square:before {
  content: "\f146";
}
.fa-minus-square-o:before {
  content: "\f147";
}
.fa-level-up:before {
  content: "\f148";
}
.fa-level-down:before {
  content: "\f149";
}
.fa-check-square:before {
  content: "\f14a";
}
.fa-pencil-square:before {
  content: "\f14b";
}
.fa-external-link-square:before {
  content: "\f14c";
}
.fa-share-square:before {
  content: "\f14d";
}
.fa-compass:before {
  content: "\f14e";
}
.fa-toggle-down:before,
.fa-caret-square-o-down:before {
  content: "\f150";
}
.fa-toggle-up:before,
.fa-caret-square-o-up:before {
  content: "\f151";
}
.fa-toggle-right:before,
.fa-caret-square-o-right:before {
  content: "\f152";
}
.fa-euro:before,
.fa-eur:before {
  content: "\f153";
}
.fa-gbp:before {
  content: "\f154";
}
.fa-dollar:before,
.fa-usd:before {
  content: "\f155";
}
.fa-rupee:before,
.fa-inr:before {
  content: "\f156";
}
.fa-cny:before,
.fa-rmb:before,
.fa-yen:before,
.fa-jpy:before {
  content: "\f157";
}
.fa-ruble:before,
.fa-rouble:before,
.fa-rub:before {
  content: "\f158";
}
.fa-won:before,
.fa-krw:before {
  content: "\f159";
}
.fa-bitcoin:before,
.fa-btc:before {
  content: "\f15a";
}
.fa-file:before {
  content: "\f15b";
}
.fa-file-text:before {
  content: "\f15c";
}
.fa-sort-alpha-asc:before {
  content: "\f15d";
}
.fa-sort-alpha-desc:before {
  content: "\f15e";
}
.fa-sort-amount-asc:before {
  content: "\f160";
}
.fa-sort-amount-desc:before {
  content: "\f161";
}
.fa-sort-numeric-asc:before {
  content: "\f162";
}
.fa-sort-numeric-desc:before {
  content: "\f163";
}
.fa-thumbs-up:before {
  content: "\f164";
}
.fa-thumbs-down:before {
  content: "\f165";
}
.fa-youtube-square:before {
  content: "\f166";
}
.fa-youtube:before {
  content: "\f167";
}
.fa-xing:before {
  content: "\f168";
}
.fa-xing-square:before {
  content: "\f169";
}
.fa-youtube-play:before {
  content: "\f16a";
}
.fa-dropbox:before {
  content: "\f16b";
}
.fa-stack-overflow:before {
  content: "\f16c";
}
.fa-instagram:before {
  content: "\f16d";
}
.fa-flickr:before {
  content: "\f16e";
}
.fa-adn:before {
  content: "\f170";
}
.fa-bitbucket:before {
  content: "\f171";
}
.fa-bitbucket-square:before {
  content: "\f172";
}
.fa-tumblr:before {
  content: "\f173";
}
.fa-tumblr-square:before {
  content: "\f174";
}
.fa-long-arrow-down:before {
  content: "\f175";
}
.fa-long-arrow-up:before {
  content: "\f176";
}
.fa-long-arrow-left:before {
  content: "\f177";
}
.fa-long-arrow-right:before {
  content: "\f178";
}
.fa-apple:before {
  content: "\f179";
}
.fa-windows:before {
  content: "\f17a";
}
.fa-android:before {
  content: "\f17b";
}
.fa-linux:before {
  content: "\f17c";
}
.fa-dribbble:before {
  content: "\f17d";
}
.fa-skype:before {
  content: "\f17e";
}
.fa-foursquare:before {
  content: "\f180";
}
.fa-trello:before {
  content: "\f181";
}
.fa-female:before {
  content: "\f182";
}
.fa-male:before {
  content: "\f183";
}
.fa-gittip:before,
.fa-gratipay:before {
  content: "\f184";
}
.fa-sun-o:before {
  content: "\f185";
}
.fa-moon-o:before {
  content: "\f186";
}
.fa-archive:before {
  content: "\f187";
}
.fa-bug:before {
  content: "\f188";
}
.fa-vk:before {
  content: "\f189";
}
.fa-weibo:before {
  content: "\f18a";
}
.fa-renren:before {
  content: "\f18b";
}
.fa-pagelines:before {
  content: "\f18c";
}
.fa-stack-exchange:before {
  content: "\f18d";
}
.fa-arrow-circle-o-right:before {
  content: "\f18e";
}
.fa-arrow-circle-o-left:before {
  content: "\f190";
}
.fa-toggle-left:before,
.fa-caret-square-o-left:before {
  content: "\f191";
}
.fa-dot-circle-o:before {
  content: "\f192";
}
.fa-wheelchair:before {
  content: "\f193";
}
.fa-vimeo-square:before {
  content: "\f194";
}
.fa-turkish-lira:before,
.fa-try:before {
  content: "\f195";
}
.fa-plus-square-o:before {
  content: "\f196";
}
.fa-space-shuttle:before {
  content: "\f197";
}
.fa-slack:before {
  content: "\f198";
}
.fa-envelope-square:before {
  content: "\f199";
}
.fa-wordpress:before {
  content: "\f19a";
}
.fa-openid:before {
  content: "\f19b";
}
.fa-institution:before,
.fa-bank:before,
.fa-university:before {
  content: "\f19c";
}
.fa-mortar-board:before,
.fa-graduation-cap:before {
  content: "\f19d";
}
.fa-yahoo:before {
  content: "\f19e";
}
.fa-google:before {
  content: "\f1a0";
}
.fa-reddit:before {
  content: "\f1a1";
}
.fa-reddit-square:before {
  content: "\f1a2";
}
.fa-stumbleupon-circle:before {
  content: "\f1a3";
}
.fa-stumbleupon:before {
  content: "\f1a4";
}
.fa-delicious:before {
  content: "\f1a5";
}
.fa-digg:before {
  content: "\f1a6";
}
.fa-pied-piper-pp:before {
  content: "\f1a7";
}
.fa-pied-piper-alt:before {
  content: "\f1a8";
}
.fa-drupal:before {
  content: "\f1a9";
}
.fa-joomla:before {
  content: "\f1aa";
}
.fa-language:before {
  content: "\f1ab";
}
.fa-fax:before {
  content: "\f1ac";
}
.fa-building:before {
  content: "\f1ad";
}
.fa-child:before {
  content: "\f1ae";
}
.fa-paw:before {
  content: "\f1b0";
}
.fa-spoon:before {
  content: "\f1b1";
}
.fa-cube:before {
  content: "\f1b2";
}
.fa-cubes:before {
  content: "\f1b3";
}
.fa-behance:before {
  content: "\f1b4";
}
.fa-behance-square:before {
  content: "\f1b5";
}
.fa-steam:before {
  content: "\f1b6";
}
.fa-steam-square:before {
  content: "\f1b7";
}
.fa-recycle:before {
  content: "\f1b8";
}
.fa-automobile:before,
.fa-car:before {
  content: "\f1b9";
}
.fa-cab:before,
.fa-taxi:before {
  content: "\f1ba";
}
.fa-tree:before {
  content: "\f1bb";
}
.fa-spotify:before {
  content: "\f1bc";
}
.fa-deviantart:before {
  content: "\f1bd";
}
.fa-soundcloud:before {
  content: "\f1be";
}
.fa-database:before {
  content: "\f1c0";
}
.fa-file-pdf-o:before {
  content: "\f1c1";
}
.fa-file-word-o:before {
  content: "\f1c2";
}
.fa-file-excel-o:before {
  content: "\f1c3";
}
.fa-file-powerpoint-o:before {
  content: "\f1c4";
}
.fa-file-photo-o:before,
.fa-file-picture-o:before,
.fa-file-image-o:before {
  content: "\f1c5";
}
.fa-file-zip-o:before,
.fa-file-archive-o:before {
  content: "\f1c6";
}
.fa-file-sound-o:before,
.fa-file-audio-o:before {
  content: "\f1c7";
}
.fa-file-movie-o:before,
.fa-file-video-o:before {
  content: "\f1c8";
}
.fa-file-code-o:before {
  content: "\f1c9";
}
.fa-vine:before {
  content: "\f1ca";
}
.fa-codepen:before {
  content: "\f1cb";
}
.fa-jsfiddle:before {
  content: "\f1cc";
}
.fa-life-bouy:before,
.fa-life-buoy:before,
.fa-life-saver:before,
.fa-support:before,
.fa-life-ring:before {
  content: "\f1cd";
}
.fa-circle-o-notch:before {
  content: "\f1ce";
}
.fa-ra:before,
.fa-resistance:before,
.fa-rebel:before {
  content: "\f1d0";
}
.fa-ge:before,
.fa-empire:before {
  content: "\f1d1";
}
.fa-git-square:before {
  content: "\f1d2";
}
.fa-git:before {
  content: "\f1d3";
}
.fa-y-combinator-square:before,
.fa-yc-square:before,
.fa-hacker-news:before {
  content: "\f1d4";
}
.fa-tencent-weibo:before {
  content: "\f1d5";
}
.fa-qq:before {
  content: "\f1d6";
}
.fa-wechat:before,
.fa-weixin:before {
  content: "\f1d7";
}
.fa-send:before,
.fa-paper-plane:before {
  content: "\f1d8";
}
.fa-send-o:before,
.fa-paper-plane-o:before {
  content: "\f1d9";
}
.fa-history:before {
  content: "\f1da";
}
.fa-circle-thin:before {
  content: "\f1db";
}
.fa-header:before {
  content: "\f1dc";
}
.fa-paragraph:before {
  content: "\f1dd";
}
.fa-sliders:before {
  content: "\f1de";
}
.fa-share-alt:before {
  content: "\f1e0";
}
.fa-share-alt-square:before {
  content: "\f1e1";
}
.fa-bomb:before {
  content: "\f1e2";
}
.fa-soccer-ball-o:before,
.fa-futbol-o:before {
  content: "\f1e3";
}
.fa-tty:before {
  content: "\f1e4";
}
.fa-binoculars:before {
  content: "\f1e5";
}
.fa-plug:before {
  content: "\f1e6";
}
.fa-slideshare:before {
  content: "\f1e7";
}
.fa-twitch:before {
  content: "\f1e8";
}
.fa-yelp:before {
  content: "\f1e9";
}
.fa-newspaper-o:before {
  content: "\f1ea";
}
.fa-wifi:before {
  content: "\f1eb";
}
.fa-calculator:before {
  content: "\f1ec";
}
.fa-paypal:before {
  content: "\f1ed";
}
.fa-google-wallet:before {
  content: "\f1ee";
}
.fa-cc-visa:before {
  content: "\f1f0";
}
.fa-cc-mastercard:before {
  content: "\f1f1";
}
.fa-cc-discover:before {
  content: "\f1f2";
}
.fa-cc-amex:before {
  content: "\f1f3";
}
.fa-cc-paypal:before {
  content: "\f1f4";
}
.fa-cc-stripe:before {
  content: "\f1f5";
}
.fa-bell-slash:before {
  content: "\f1f6";
}
.fa-bell-slash-o:before {
  content: "\f1f7";
}
.fa-trash:before {
  content: "\f1f8";
}
.fa-copyright:before {
  content: "\f1f9";
}
.fa-at:before {
  content: "\f1fa";
}
.fa-eyedropper:before {
  content: "\f1fb";
}
.fa-paint-brush:before {
  content: "\f1fc";
}
.fa-birthday-cake:before {
  content: "\f1fd";
}
.fa-area-chart:before {
  content: "\f1fe";
}
.fa-pie-chart:before {
  content: "\f200";
}
.fa-line-chart:before {
  content: "\f201";
}
.fa-lastfm:before {
  content: "\f202";
}
.fa-lastfm-square:before {
  content: "\f203";
}
.fa-toggle-off:before {
  content: "\f204";
}
.fa-toggle-on:before {
  content: "\f205";
}
.fa-bicycle:before {
  content: "\f206";
}
.fa-bus:before {
  content: "\f207";
}
.fa-ioxhost:before {
  content: "\f208";
}
.fa-angellist:before {
  content: "\f209";
}
.fa-cc:before {
  content: "\f20a";
}
.fa-shekel:before,
.fa-sheqel:before,
.fa-ils:before {
  content: "\f20b";
}
.fa-meanpath:before {
  content: "\f20c";
}
.fa-buysellads:before {
  content: "\f20d";
}
.fa-connectdevelop:before {
  content: "\f20e";
}
.fa-dashcube:before {
  content: "\f210";
}
.fa-forumbee:before {
  content: "\f211";
}
.fa-leanpub:before {
  content: "\f212";
}
.fa-sellsy:before {
  content: "\f213";
}
.fa-shirtsinbulk:before {
  content: "\f214";
}
.fa-simplybuilt:before {
  content: "\f215";
}
.fa-skyatlas:before {
  content: "\f216";
}
.fa-cart-plus:before {
  content: "\f217";
}
.fa-cart-arrow-down:before {
  content: "\f218";
}
.fa-diamond:before {
  content: "\f219";
}
.fa-ship:before {
  content: "\f21a";
}
.fa-user-secret:before {
  content: "\f21b";
}
.fa-motorcycle:before {
  content: "\f21c";
}
.fa-street-view:before {
  content: "\f21d";
}
.fa-heartbeat:before {
  content: "\f21e";
}
.fa-venus:before {
  content: "\f221";
}
.fa-mars:before {
  content: "\f222";
}
.fa-mercury:before {
  content: "\f223";
}
.fa-intersex:before,
.fa-transgender:before {
  content: "\f224";
}
.fa-transgender-alt:before {
  content: "\f225";
}
.fa-venus-double:before {
  content: "\f226";
}
.fa-mars-double:before {
  content: "\f227";
}
.fa-venus-mars:before {
  content: "\f228";
}
.fa-mars-stroke:before {
  content: "\f229";
}
.fa-mars-stroke-v:before {
  content: "\f22a";
}
.fa-mars-stroke-h:before {
  content: "\f22b";
}
.fa-neuter:before {
  content: "\f22c";
}
.fa-genderless:before {
  content: "\f22d";
}
.fa-facebook-official:before {
  content: "\f230";
}
.fa-pinterest-p:before {
  content: "\f231";
}
.fa-whatsapp:before {
  content: "\f232";
}
.fa-server:before {
  content: "\f233";
}
.fa-user-plus:before {
  content: "\f234";
}
.fa-user-times:before {
  content: "\f235";
}
.fa-hotel:before,
.fa-bed:before {
  content: "\f236";
}
.fa-viacoin:before {
  content: "\f237";
}
.fa-train:before {
  content: "\f238";
}
.fa-subway:before {
  content: "\f239";
}
.fa-medium:before {
  content: "\f23a";
}
.fa-yc:before,
.fa-y-combinator:before {
  content: "\f23b";
}
.fa-optin-monster:before {
  content: "\f23c";
}
.fa-opencart:before {
  content: "\f23d";
}
.fa-expeditedssl:before {
  content: "\f23e";
}
.fa-battery-4:before,
.fa-battery:before,
.fa-battery-full:before {
  content: "\f240";
}
.fa-battery-3:before,
.fa-battery-three-quarters:before {
  content: "\f241";
}
.fa-battery-2:before,
.fa-battery-half:before {
  content: "\f242";
}
.fa-battery-1:before,
.fa-battery-quarter:before {
  content: "\f243";
}
.fa-battery-0:before,
.fa-battery-empty:before {
  content: "\f244";
}
.fa-mouse-pointer:before {
  content: "\f245";
}
.fa-i-cursor:before {
  content: "\f246";
}
.fa-object-group:before {
  content: "\f247";
}
.fa-object-ungroup:before {
  content: "\f248";
}
.fa-sticky-note:before {
  content: "\f249";
}
.fa-sticky-note-o:before {
  content: "\f24a";
}
.fa-cc-jcb:before {
  content: "\f24b";
}
.fa-cc-diners-club:before {
  content: "\f24c";
}
.fa-clone:before {
  content: "\f24d";
}
.fa-balance-scale:before {
  content: "\f24e";
}
.fa-hourglass-o:before {
  content: "\f250";
}
.fa-hourglass-1:before,
.fa-hourglass-start:before {
  content: "\f251";
}
.fa-hourglass-2:before,
.fa-hourglass-half:before {
  content: "\f252";
}
.fa-hourglass-3:before,
.fa-hourglass-end:before {
  content: "\f253";
}
.fa-hourglass:before {
  content: "\f254";
}
.fa-hand-grab-o:before,
.fa-hand-rock-o:before {
  content: "\f255";
}
.fa-hand-stop-o:before,
.fa-hand-paper-o:before {
  content: "\f256";
}
.fa-hand-scissors-o:before {
  content: "\f257";
}
.fa-hand-lizard-o:before {
  content: "\f258";
}
.fa-hand-spock-o:before {
  content: "\f259";
}
.fa-hand-pointer-o:before {
  content: "\f25a";
}
.fa-hand-peace-o:before {
  content: "\f25b";
}
.fa-trademark:before {
  content: "\f25c";
}
.fa-registered:before {
  content: "\f25d";
}
.fa-creative-commons:before {
  content: "\f25e";
}
.fa-gg:before {
  content: "\f260";
}
.fa-gg-circle:before {
  content: "\f261";
}
.fa-tripadvisor:before {
  content: "\f262";
}
.fa-odnoklassniki:before {
  content: "\f263";
}
.fa-odnoklassniki-square:before {
  content: "\f264";
}
.fa-get-pocket:before {
  content: "\f265";
}
.fa-wikipedia-w:before {
  content: "\f266";
}
.fa-safari:before {
  content: "\f267";
}
.fa-chrome:before {
  content: "\f268";
}
.fa-firefox:before {
  content: "\f269";
}
.fa-opera:before {
  content: "\f26a";
}
.fa-internet-explorer:before {
  content: "\f26b";
}
.fa-tv:before,
.fa-television:before {
  content: "\f26c";
}
.fa-contao:before {
  content: "\f26d";
}
.fa-500px:before {
  content: "\f26e";
}
.fa-amazon:before {
  content: "\f270";
}
.fa-calendar-plus-o:before {
  content: "\f271";
}
.fa-calendar-minus-o:before {
  content: "\f272";
}
.fa-calendar-times-o:before {
  content: "\f273";
}
.fa-calendar-check-o:before {
  content: "\f274";
}
.fa-industry:before {
  content: "\f275";
}
.fa-map-pin:before {
  content: "\f276";
}
.fa-map-signs:before {
  content: "\f277";
}
.fa-map-o:before {
  content: "\f278";
}
.fa-map:before {
  content: "\f279";
}
.fa-commenting:before {
  content: "\f27a";
}
.fa-commenting-o:before {
  content: "\f27b";
}
.fa-houzz:before {
  content: "\f27c";
}
.fa-vimeo:before {
  content: "\f27d";
}
.fa-black-tie:before {
  content: "\f27e";
}
.fa-fonticons:before {
  content: "\f280";
}
.fa-reddit-alien:before {
  content: "\f281";
}
.fa-edge:before {
  content: "\f282";
}
.fa-credit-card-alt:before {
  content: "\f283";
}
.fa-codiepie:before {
  content: "\f284";
}
.fa-modx:before {
  content: "\f285";
}
.fa-fort-awesome:before {
  content: "\f286";
}
.fa-usb:before {
  content: "\f287";
}
.fa-product-hunt:before {
  content: "\f288";
}
.fa-mixcloud:before {
  content: "\f289";
}
.fa-scribd:before {
  content: "\f28a";
}
.fa-pause-circle:before {
  content: "\f28b";
}
.fa-pause-circle-o:before {
  content: "\f28c";
}
.fa-stop-circle:before {
  content: "\f28d";
}
.fa-stop-circle-o:before {
  content: "\f28e";
}
.fa-shopping-bag:before {
  content: "\f290";
}
.fa-shopping-basket:before {
  content: "\f291";
}
.fa-hashtag:before {
  content: "\f292";
}
.fa-bluetooth:before {
  content: "\f293";
}
.fa-bluetooth-b:before {
  content: "\f294";
}
.fa-percent:before {
  content: "\f295";
}
.fa-gitlab:before {
  content: "\f296";
}
.fa-wpbeginner:before {
  content: "\f297";
}
.fa-wpforms:before {
  content: "\f298";
}
.fa-envira:before {
  content: "\f299";
}
.fa-universal-access:before {
  content: "\f29a";
}
.fa-wheelchair-alt:before {
  content: "\f29b";
}
.fa-question-circle-o:before {
  content: "\f29c";
}
.fa-blind:before {
  content: "\f29d";
}
.fa-audio-description:before {
  content: "\f29e";
}
.fa-volume-control-phone:before {
  content: "\f2a0";
}
.fa-braille:before {
  content: "\f2a1";
}
.fa-assistive-listening-systems:before {
  content: "\f2a2";
}
.fa-asl-interpreting:before,
.fa-american-sign-language-interpreting:before {
  content: "\f2a3";
}
.fa-deafness:before,
.fa-hard-of-hearing:before,
.fa-deaf:before {
  content: "\f2a4";
}
.fa-glide:before {
  content: "\f2a5";
}
.fa-glide-g:before {
  content: "\f2a6";
}
.fa-signing:before,
.fa-sign-language:before {
  content: "\f2a7";
}
.fa-low-vision:before {
  content: "\f2a8";
}
.fa-viadeo:before {
  content: "\f2a9";
}
.fa-viadeo-square:before {
  content: "\f2aa";
}
.fa-snapchat:before {
  content: "\f2ab";
}
.fa-snapchat-ghost:before {
  content: "\f2ac";
}
.fa-snapchat-square:before {
  content: "\f2ad";
}
.fa-pied-piper:before {
  content: "\f2ae";
}
.fa-first-order:before {
  content: "\f2b0";
}
.fa-yoast:before {
  content: "\f2b1";
}
.fa-themeisle:before {
  content: "\f2b2";
}
.fa-google-plus-circle:before,
.fa-google-plus-official:before {
  content: "\f2b3";
}
.fa-fa:before,
.fa-font-awesome:before {
  content: "\f2b4";
}
.fa-handshake-o:before {
  content: "\f2b5";
}
.fa-envelope-open:before {
  content: "\f2b6";
}
.fa-envelope-open-o:before {
  content: "\f2b7";
}
.fa-linode:before {
  content: "\f2b8";
}
.fa-address-book:before {
  content: "\f2b9";
}
.fa-address-book-o:before {
  content: "\f2ba";
}
.fa-vcard:before,
.fa-address-card:before {
  content: "\f2bb";
}
.fa-vcard-o:before,
.fa-address-card-o:before {
  content: "\f2bc";
}
.fa-user-circle:before {
  content: "\f2bd";
}
.fa-user-circle-o:before {
  content: "\f2be";
}
.fa-user-o:before {
  content: "\f2c0";
}
.fa-id-badge:before {
  content: "\f2c1";
}
.fa-drivers-license:before,
.fa-id-card:before {
  content: "\f2c2";
}
.fa-drivers-license-o:before,
.fa-id-card-o:before {
  content: "\f2c3";
}
.fa-quora:before {
  content: "\f2c4";
}
.fa-free-code-camp:before {
  content: "\f2c5";
}
.fa-telegram:before {
  content: "\f2c6";
}
.fa-thermometer-4:before,
.fa-thermometer:before,
.fa-thermometer-full:before {
  content: "\f2c7";
}
.fa-thermometer-3:before,
.fa-thermometer-three-quarters:before {
  content: "\f2c8";
}
.fa-thermometer-2:before,
.fa-thermometer-half:before {
  content: "\f2c9";
}
.fa-thermometer-1:before,
.fa-thermometer-quarter:before {
  content: "\f2ca";
}
.fa-thermometer-0:before,
.fa-thermometer-empty:before {
  content: "\f2cb";
}
.fa-shower:before {
  content: "\f2cc";
}
.fa-bathtub:before,
.fa-s15:before,
.fa-bath:before {
  content: "\f2cd";
}
.fa-podcast:before {
  content: "\f2ce";
}
.fa-window-maximize:before {
  content: "\f2d0";
}
.fa-window-minimize:before {
  content: "\f2d1";
}
.fa-window-restore:before {
  content: "\f2d2";
}
.fa-times-rectangle:before,
.fa-window-close:before {
  content: "\f2d3";
}
.fa-times-rectangle-o:before,
.fa-window-close-o:before {
  content: "\f2d4";
}
.fa-bandcamp:before {
  content: "\f2d5";
}
.fa-grav:before {
  content: "\f2d6";
}
.fa-etsy:before {
  content: "\f2d7";
}
.fa-imdb:before {
  content: "\f2d8";
}
.fa-ravelry:before {
  content: "\f2d9";
}
.fa-eercast:before {
  content: "\f2da";
}
.fa-microchip:before {
  content: "\f2db";
}
.fa-snowflake-o:before {
  content: "\f2dc";
}
.fa-superpowers:before {
  content: "\f2dd";
}
.fa-wpexplorer:before {
  content: "\f2de";
}
.fa-meetup:before {
  content: "\f2e0";
}
.sr-only {
  position: absolute;
  width: 1px;
  height: 1px;
  padding: 0;
  margin: -1px;
  overflow: hidden;
  clip: rect(0, 0, 0, 0);
  border: 0;
}
.sr-only-focusable:active,
.sr-only-focusable:focus {
  position: static;
  width: auto;
  height: auto;
  margin: 0;
  overflow: visible;
  clip: auto;
}
.sr-only-focusable:active,
.sr-only-focusable:focus {
  position: static;
  width: auto;
  height: auto;
  margin: 0;
  overflow: visible;
  clip: auto;
}
/*!
*
* IPython base
*
*/
.modal.fade .modal-dialog {
  -webkit-transform: translate(0, 0);
  -ms-transform: translate(0, 0);
  -o-transform: translate(0, 0);
  transform: translate(0, 0);
}
code {
  color: #000;
}
pre {
  font-size: inherit;
  line-height: inherit;
}
label {
  font-weight: normal;
}
/* Make the page background atleast 100% the height of the view port */
/* Make the page itself atleast 70% the height of the view port */
.border-box-sizing {
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
}
.corner-all {
  border-radius: 2px;
}
.no-padding {
  padding: 0px;
}
/* Flexible box model classes */
/* Taken from Alex Russell http://infrequently.org/2009/08/css-3-progress/ */
/* This file is a compatability layer.  It allows the usage of flexible box
model layouts accross multiple browsers, including older browsers.  The newest,
universal implementation of the flexible box model is used when available (see
`Modern browsers` comments below).  Browsers that are known to implement this
new spec completely include:

    Firefox 28.0+
    Chrome 29.0+
    Internet Explorer 11+
    Opera 17.0+

Browsers not listed, including Safari, are supported via the styling under the
`Old browsers` comments below.
*/
.hbox {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
}
.hbox > * {
  /* Old browsers */
  -webkit-box-flex: 0;
  -moz-box-flex: 0;
  box-flex: 0;
  /* Modern browsers */
  flex: none;
}
.vbox {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
}
.vbox > * {
  /* Old browsers */
  -webkit-box-flex: 0;
  -moz-box-flex: 0;
  box-flex: 0;
  /* Modern browsers */
  flex: none;
}
.hbox.reverse,
.vbox.reverse,
.reverse {
  /* Old browsers */
  -webkit-box-direction: reverse;
  -moz-box-direction: reverse;
  box-direction: reverse;
  /* Modern browsers */
  flex-direction: row-reverse;
}
.hbox.box-flex0,
.vbox.box-flex0,
.box-flex0 {
  /* Old browsers */
  -webkit-box-flex: 0;
  -moz-box-flex: 0;
  box-flex: 0;
  /* Modern browsers */
  flex: none;
  width: auto;
}
.hbox.box-flex1,
.vbox.box-flex1,
.box-flex1 {
  /* Old browsers */
  -webkit-box-flex: 1;
  -moz-box-flex: 1;
  box-flex: 1;
  /* Modern browsers */
  flex: 1;
}
.hbox.box-flex,
.vbox.box-flex,
.box-flex {
  /* Old browsers */
  /* Old browsers */
  -webkit-box-flex: 1;
  -moz-box-flex: 1;
  box-flex: 1;
  /* Modern browsers */
  flex: 1;
}
.hbox.box-flex2,
.vbox.box-flex2,
.box-flex2 {
  /* Old browsers */
  -webkit-box-flex: 2;
  -moz-box-flex: 2;
  box-flex: 2;
  /* Modern browsers */
  flex: 2;
}
.box-group1 {
  /*  Deprecated */
  -webkit-box-flex-group: 1;
  -moz-box-flex-group: 1;
  box-flex-group: 1;
}
.box-group2 {
  /* Deprecated */
  -webkit-box-flex-group: 2;
  -moz-box-flex-group: 2;
  box-flex-group: 2;
}
.hbox.start,
.vbox.start,
.start {
  /* Old browsers */
  -webkit-box-pack: start;
  -moz-box-pack: start;
  box-pack: start;
  /* Modern browsers */
  justify-content: flex-start;
}
.hbox.end,
.vbox.end,
.end {
  /* Old browsers */
  -webkit-box-pack: end;
  -moz-box-pack: end;
  box-pack: end;
  /* Modern browsers */
  justify-content: flex-end;
}
.hbox.center,
.vbox.center,
.center {
  /* Old browsers */
  -webkit-box-pack: center;
  -moz-box-pack: center;
  box-pack: center;
  /* Modern browsers */
  justify-content: center;
}
.hbox.baseline,
.vbox.baseline,
.baseline {
  /* Old browsers */
  -webkit-box-pack: baseline;
  -moz-box-pack: baseline;
  box-pack: baseline;
  /* Modern browsers */
  justify-content: baseline;
}
.hbox.stretch,
.vbox.stretch,
.stretch {
  /* Old browsers */
  -webkit-box-pack: stretch;
  -moz-box-pack: stretch;
  box-pack: stretch;
  /* Modern browsers */
  justify-content: stretch;
}
.hbox.align-start,
.vbox.align-start,
.align-start {
  /* Old browsers */
  -webkit-box-align: start;
  -moz-box-align: start;
  box-align: start;
  /* Modern browsers */
  align-items: flex-start;
}
.hbox.align-end,
.vbox.align-end,
.align-end {
  /* Old browsers */
  -webkit-box-align: end;
  -moz-box-align: end;
  box-align: end;
  /* Modern browsers */
  align-items: flex-end;
}
.hbox.align-center,
.vbox.align-center,
.align-center {
  /* Old browsers */
  -webkit-box-align: center;
  -moz-box-align: center;
  box-align: center;
  /* Modern browsers */
  align-items: center;
}
.hbox.align-baseline,
.vbox.align-baseline,
.align-baseline {
  /* Old browsers */
  -webkit-box-align: baseline;
  -moz-box-align: baseline;
  box-align: baseline;
  /* Modern browsers */
  align-items: baseline;
}
.hbox.align-stretch,
.vbox.align-stretch,
.align-stretch {
  /* Old browsers */
  -webkit-box-align: stretch;
  -moz-box-align: stretch;
  box-align: stretch;
  /* Modern browsers */
  align-items: stretch;
}
div.error {
  margin: 2em;
  text-align: center;
}
div.error > h1 {
  font-size: 500%;
  line-height: normal;
}
div.error > p {
  font-size: 200%;
  line-height: normal;
}
div.traceback-wrapper {
  text-align: left;
  max-width: 800px;
  margin: auto;
}
div.traceback-wrapper pre.traceback {
  max-height: 600px;
  overflow: auto;
}
/**
 * Primary styles
 *
 * Author: Jupyter Development Team
 */
body {
  background-color: #fff;
  /* This makes sure that the body covers the entire window and needs to
       be in a different element than the display: box in wrapper below */
  position: absolute;
  left: 0px;
  right: 0px;
  top: 0px;
  bottom: 0px;
  overflow: visible;
}
body > #header {
  /* Initially hidden to prevent FLOUC */
  display: none;
  background-color: #fff;
  /* Display over codemirror */
  position: relative;
  z-index: 100;
}
body > #header #header-container {
  display: flex;
  flex-direction: row;
  justify-content: space-between;
  padding: 5px;
  padding-bottom: 5px;
  padding-top: 5px;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
}
body > #header .header-bar {
  width: 100%;
  height: 1px;
  background: #e7e7e7;
  margin-bottom: -1px;
}
@media print {
  body > #header {
    display: none !important;
  }
}
#header-spacer {
  width: 100%;
  visibility: hidden;
}
@media print {
  #header-spacer {
    display: none;
  }
}
#ipython_notebook {
  padding-left: 0px;
  padding-top: 1px;
  padding-bottom: 1px;
}
[dir="rtl"] #ipython_notebook {
  margin-right: 10px;
  margin-left: 0;
}
[dir="rtl"] #ipython_notebook.pull-left {
  float: right !important;
  float: right;
}
.flex-spacer {
  flex: 1;
}
#noscript {
  width: auto;
  padding-top: 16px;
  padding-bottom: 16px;
  text-align: center;
  font-size: 22px;
  color: red;
  font-weight: bold;
}
#ipython_notebook img {
  height: 28px;
}
#site {
  width: 100%;
  display: none;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  overflow: auto;
}
@media print {
  #site {
    height: auto !important;
  }
}
/* Smaller buttons */
.ui-button .ui-button-text {
  padding: 0.2em 0.8em;
  font-size: 77%;
}
input.ui-button {
  padding: 0.3em 0.9em;
}
span#kernel_logo_widget {
  margin: 0 10px;
}
span#login_widget {
  float: right;
}
[dir="rtl"] span#login_widget {
  float: left;
}
span#login_widget > .button,
#logout {
  color: #333;
  background-color: #fff;
  border-color: #ccc;
}
span#login_widget > .button:focus,
#logout:focus,
span#login_widget > .button.focus,
#logout.focus {
  color: #333;
  background-color: #e6e6e6;
  border-color: #8c8c8c;
}
span#login_widget > .button:hover,
#logout:hover {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
span#login_widget > .button:active,
#logout:active,
span#login_widget > .button.active,
#logout.active,
.open > .dropdown-togglespan#login_widget > .button,
.open > .dropdown-toggle#logout {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
span#login_widget > .button:active:hover,
#logout:active:hover,
span#login_widget > .button.active:hover,
#logout.active:hover,
.open > .dropdown-togglespan#login_widget > .button:hover,
.open > .dropdown-toggle#logout:hover,
span#login_widget > .button:active:focus,
#logout:active:focus,
span#login_widget > .button.active:focus,
#logout.active:focus,
.open > .dropdown-togglespan#login_widget > .button:focus,
.open > .dropdown-toggle#logout:focus,
span#login_widget > .button:active.focus,
#logout:active.focus,
span#login_widget > .button.active.focus,
#logout.active.focus,
.open > .dropdown-togglespan#login_widget > .button.focus,
.open > .dropdown-toggle#logout.focus {
  color: #333;
  background-color: #d4d4d4;
  border-color: #8c8c8c;
}
span#login_widget > .button:active,
#logout:active,
span#login_widget > .button.active,
#logout.active,
.open > .dropdown-togglespan#login_widget > .button,
.open > .dropdown-toggle#logout {
  background-image: none;
}
span#login_widget > .button.disabled:hover,
#logout.disabled:hover,
span#login_widget > .button[disabled]:hover,
#logout[disabled]:hover,
fieldset[disabled] span#login_widget > .button:hover,
fieldset[disabled] #logout:hover,
span#login_widget > .button.disabled:focus,
#logout.disabled:focus,
span#login_widget > .button[disabled]:focus,
#logout[disabled]:focus,
fieldset[disabled] span#login_widget > .button:focus,
fieldset[disabled] #logout:focus,
span#login_widget > .button.disabled.focus,
#logout.disabled.focus,
span#login_widget > .button[disabled].focus,
#logout[disabled].focus,
fieldset[disabled] span#login_widget > .button.focus,
fieldset[disabled] #logout.focus {
  background-color: #fff;
  border-color: #ccc;
}
span#login_widget > .button .badge,
#logout .badge {
  color: #fff;
  background-color: #333;
}
.nav-header {
  text-transform: none;
}
#header > span {
  margin-top: 10px;
}
.modal_stretch .modal-dialog {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
  min-height: 80vh;
}
.modal_stretch .modal-dialog .modal-body {
  max-height: calc(100vh - 200px);
  overflow: auto;
  flex: 1;
}
.modal-header {
  cursor: move;
}
@media (min-width: 768px) {
  .modal .modal-dialog {
    width: 700px;
  }
}
@media (min-width: 768px) {
  select.form-control {
    margin-left: 12px;
    margin-right: 12px;
  }
}
/*!
*
* IPython auth
*
*/
.center-nav {
  display: inline-block;
  margin-bottom: -4px;
}
[dir="rtl"] .center-nav form.pull-left {
  float: right !important;
  float: right;
}
[dir="rtl"] .center-nav .navbar-text {
  float: right;
}
[dir="rtl"] .navbar-inner {
  text-align: right;
}
[dir="rtl"] div.text-left {
  text-align: right;
}
/*!
*
* IPython tree view
*
*/
/* We need an invisible input field on top of the sentense*/
/* "Drag file onto the list ..." */
.alternate_upload {
  background-color: none;
  display: inline;
}
.alternate_upload.form {
  padding: 0;
  margin: 0;
}
.alternate_upload input.fileinput {
  position: absolute;
  display: block;
  width: 100%;
  height: 100%;
  overflow: hidden;
  cursor: pointer;
  opacity: 0;
  z-index: 2;
}
.alternate_upload .btn-xs > input.fileinput {
  margin: -1px -5px;
}
.alternate_upload .btn-upload {
  position: relative;
  height: 22px;
}
::-webkit-file-upload-button {
  cursor: pointer;
}
/**
 * Primary styles
 *
 * Author: Jupyter Development Team
 */
ul#tabs {
  margin-bottom: 4px;
}
ul#tabs a {
  padding-top: 6px;
  padding-bottom: 4px;
}
[dir="rtl"] ul#tabs.nav-tabs > li {
  float: right;
}
[dir="rtl"] ul#tabs.nav.nav-tabs {
  padding-right: 0;
}
ul.breadcrumb a:focus,
ul.breadcrumb a:hover {
  text-decoration: none;
}
ul.breadcrumb i.icon-home {
  font-size: 16px;
  margin-right: 4px;
}
ul.breadcrumb span {
  color: #5e5e5e;
}
.list_toolbar {
  padding: 4px 0 4px 0;
  vertical-align: middle;
}
.list_toolbar .tree-buttons {
  padding-top: 1px;
}
[dir="rtl"] .list_toolbar .tree-buttons .pull-right {
  float: left !important;
  float: left;
}
[dir="rtl"] .list_toolbar .col-sm-4,
[dir="rtl"] .list_toolbar .col-sm-8 {
  float: right;
}
.dynamic-buttons {
  padding-top: 3px;
  display: inline-block;
}
.list_toolbar [class*="span"] {
  min-height: 24px;
}
.list_header {
  font-weight: bold;
  background-color: #EEE;
}
.list_placeholder {
  font-weight: bold;
  padding-top: 4px;
  padding-bottom: 4px;
  padding-left: 7px;
  padding-right: 7px;
}
.list_container {
  margin-top: 4px;
  margin-bottom: 20px;
  border: 1px solid #ddd;
  border-radius: 2px;
}
.list_container > div {
  border-bottom: 1px solid #ddd;
}
.list_container > div:hover .list-item {
  background-color: red;
}
.list_container > div:last-child {
  border: none;
}
.list_item:hover .list_item {
  background-color: #ddd;
}
.list_item a {
  text-decoration: none;
}
.list_item:hover {
  background-color: #fafafa;
}
.list_header > div,
.list_item > div {
  padding-top: 4px;
  padding-bottom: 4px;
  padding-left: 7px;
  padding-right: 7px;
  line-height: 22px;
}
.list_header > div input,
.list_item > div input {
  margin-right: 7px;
  margin-left: 14px;
  vertical-align: text-bottom;
  line-height: 22px;
  position: relative;
  top: -1px;
}
.list_header > div .item_link,
.list_item > div .item_link {
  margin-left: -1px;
  vertical-align: baseline;
  line-height: 22px;
}
[dir="rtl"] .list_item > div input {
  margin-right: 0;
}
.new-file input[type=checkbox] {
  visibility: hidden;
}
.item_name {
  line-height: 22px;
  height: 24px;
}
.item_icon {
  font-size: 14px;
  color: #5e5e5e;
  margin-right: 7px;
  margin-left: 7px;
  line-height: 22px;
  vertical-align: baseline;
}
.item_modified {
  margin-right: 7px;
  margin-left: 7px;
}
[dir="rtl"] .item_modified.pull-right {
  float: left !important;
  float: left;
}
.item_buttons {
  line-height: 1em;
  margin-left: -5px;
}
.item_buttons .btn,
.item_buttons .btn-group,
.item_buttons .input-group {
  float: left;
}
.item_buttons > .btn,
.item_buttons > .btn-group,
.item_buttons > .input-group {
  margin-left: 5px;
}
.item_buttons .btn {
  min-width: 13ex;
}
.item_buttons .running-indicator {
  padding-top: 4px;
  color: #5cb85c;
}
.item_buttons .kernel-name {
  padding-top: 4px;
  color: #5bc0de;
  margin-right: 7px;
  float: left;
}
[dir="rtl"] .item_buttons.pull-right {
  float: left !important;
  float: left;
}
[dir="rtl"] .item_buttons .kernel-name {
  margin-left: 7px;
  float: right;
}
.toolbar_info {
  height: 24px;
  line-height: 24px;
}
.list_item input:not([type=checkbox]) {
  padding-top: 3px;
  padding-bottom: 3px;
  height: 22px;
  line-height: 14px;
  margin: 0px;
}
.highlight_text {
  color: blue;
}
#project_name {
  display: inline-block;
  padding-left: 7px;
  margin-left: -2px;
}
#project_name > .breadcrumb {
  padding: 0px;
  margin-bottom: 0px;
  background-color: transparent;
  font-weight: bold;
}
.sort_button {
  display: inline-block;
  padding-left: 7px;
}
[dir="rtl"] .sort_button.pull-right {
  float: left !important;
  float: left;
}
#tree-selector {
  padding-right: 0px;
}
#button-select-all {
  min-width: 50px;
}
[dir="rtl"] #button-select-all.btn {
  float: right ;
}
#select-all {
  margin-left: 7px;
  margin-right: 2px;
  margin-top: 2px;
  height: 16px;
}
[dir="rtl"] #select-all.pull-left {
  float: right !important;
  float: right;
}
.menu_icon {
  margin-right: 2px;
}
.tab-content .row {
  margin-left: 0px;
  margin-right: 0px;
}
.folder_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f114";
}
.folder_icon:before.fa-pull-left {
  margin-right: .3em;
}
.folder_icon:before.fa-pull-right {
  margin-left: .3em;
}
.folder_icon:before.pull-left {
  margin-right: .3em;
}
.folder_icon:before.pull-right {
  margin-left: .3em;
}
.notebook_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f02d";
  position: relative;
  top: -1px;
}
.notebook_icon:before.fa-pull-left {
  margin-right: .3em;
}
.notebook_icon:before.fa-pull-right {
  margin-left: .3em;
}
.notebook_icon:before.pull-left {
  margin-right: .3em;
}
.notebook_icon:before.pull-right {
  margin-left: .3em;
}
.running_notebook_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f02d";
  position: relative;
  top: -1px;
  color: #5cb85c;
}
.running_notebook_icon:before.fa-pull-left {
  margin-right: .3em;
}
.running_notebook_icon:before.fa-pull-right {
  margin-left: .3em;
}
.running_notebook_icon:before.pull-left {
  margin-right: .3em;
}
.running_notebook_icon:before.pull-right {
  margin-left: .3em;
}
.file_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f016";
  position: relative;
  top: -2px;
}
.file_icon:before.fa-pull-left {
  margin-right: .3em;
}
.file_icon:before.fa-pull-right {
  margin-left: .3em;
}
.file_icon:before.pull-left {
  margin-right: .3em;
}
.file_icon:before.pull-right {
  margin-left: .3em;
}
#notebook_toolbar .pull-right {
  padding-top: 0px;
  margin-right: -1px;
}
ul#new-menu {
  left: auto;
  right: 0;
}
#new-menu .dropdown-header {
  font-size: 10px;
  border-bottom: 1px solid #e5e5e5;
  padding: 0 0 3px;
  margin: -3px 20px 0;
}
.kernel-menu-icon {
  padding-right: 12px;
  width: 24px;
  content: "\f096";
}
.kernel-menu-icon:before {
  content: "\f096";
}
.kernel-menu-icon-current:before {
  content: "\f00c";
}
#tab_content {
  padding-top: 20px;
}
#running .panel-group .panel {
  margin-top: 3px;
  margin-bottom: 1em;
}
#running .panel-group .panel .panel-heading {
  background-color: #EEE;
  padding-top: 4px;
  padding-bottom: 4px;
  padding-left: 7px;
  padding-right: 7px;
  line-height: 22px;
}
#running .panel-group .panel .panel-heading a:focus,
#running .panel-group .panel .panel-heading a:hover {
  text-decoration: none;
}
#running .panel-group .panel .panel-body {
  padding: 0px;
}
#running .panel-group .panel .panel-body .list_container {
  margin-top: 0px;
  margin-bottom: 0px;
  border: 0px;
  border-radius: 0px;
}
#running .panel-group .panel .panel-body .list_container .list_item {
  border-bottom: 1px solid #ddd;
}
#running .panel-group .panel .panel-body .list_container .list_item:last-child {
  border-bottom: 0px;
}
.delete-button {
  display: none;
}
.duplicate-button {
  display: none;
}
.rename-button {
  display: none;
}
.move-button {
  display: none;
}
.download-button {
  display: none;
}
.shutdown-button {
  display: none;
}
.dynamic-instructions {
  display: inline-block;
  padding-top: 4px;
}
/*!
*
* IPython text editor webapp
*
*/
.selected-keymap i.fa {
  padding: 0px 5px;
}
.selected-keymap i.fa:before {
  content: "\f00c";
}
#mode-menu {
  overflow: auto;
  max-height: 20em;
}
.edit_app #header {
  -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
}
.edit_app #menubar .navbar {
  /* Use a negative 1 bottom margin, so the border overlaps the border of the
    header */
  margin-bottom: -1px;
}
.dirty-indicator {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  width: 20px;
}
.dirty-indicator.fa-pull-left {
  margin-right: .3em;
}
.dirty-indicator.fa-pull-right {
  margin-left: .3em;
}
.dirty-indicator.pull-left {
  margin-right: .3em;
}
.dirty-indicator.pull-right {
  margin-left: .3em;
}
.dirty-indicator-dirty {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  width: 20px;
}
.dirty-indicator-dirty.fa-pull-left {
  margin-right: .3em;
}
.dirty-indicator-dirty.fa-pull-right {
  margin-left: .3em;
}
.dirty-indicator-dirty.pull-left {
  margin-right: .3em;
}
.dirty-indicator-dirty.pull-right {
  margin-left: .3em;
}
.dirty-indicator-clean {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  width: 20px;
}
.dirty-indicator-clean.fa-pull-left {
  margin-right: .3em;
}
.dirty-indicator-clean.fa-pull-right {
  margin-left: .3em;
}
.dirty-indicator-clean.pull-left {
  margin-right: .3em;
}
.dirty-indicator-clean.pull-right {
  margin-left: .3em;
}
.dirty-indicator-clean:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f00c";
}
.dirty-indicator-clean:before.fa-pull-left {
  margin-right: .3em;
}
.dirty-indicator-clean:before.fa-pull-right {
  margin-left: .3em;
}
.dirty-indicator-clean:before.pull-left {
  margin-right: .3em;
}
.dirty-indicator-clean:before.pull-right {
  margin-left: .3em;
}
#filename {
  font-size: 16pt;
  display: table;
  padding: 0px 5px;
}
#current-mode {
  padding-left: 5px;
  padding-right: 5px;
}
#texteditor-backdrop {
  padding-top: 20px;
  padding-bottom: 20px;
}
@media not print {
  #texteditor-backdrop {
    background-color: #EEE;
  }
}
@media print {
  #texteditor-backdrop #texteditor-container .CodeMirror-gutter,
  #texteditor-backdrop #texteditor-container .CodeMirror-gutters {
    background-color: #fff;
  }
}
@media not print {
  #texteditor-backdrop #texteditor-container .CodeMirror-gutter,
  #texteditor-backdrop #texteditor-container .CodeMirror-gutters {
    background-color: #fff;
  }
}
@media not print {
  #texteditor-backdrop #texteditor-container {
    padding: 0px;
    background-color: #fff;
    -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
    box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  }
}
.CodeMirror-dialog {
  background-color: #fff;
}
/*!
*
* IPython notebook
*
*/
/* CSS font colors for translated ANSI escape sequences */
/* The color values are a mix of
   http://www.xcolors.net/dl/baskerville-ivorylight and
   http://www.xcolors.net/dl/euphrasia */
.ansi-black-fg {
  color: #3E424D;
}
.ansi-black-bg {
  background-color: #3E424D;
}
.ansi-black-intense-fg {
  color: #282C36;
}
.ansi-black-intense-bg {
  background-color: #282C36;
}
.ansi-red-fg {
  color: #E75C58;
}
.ansi-red-bg {
  background-color: #E75C58;
}
.ansi-red-intense-fg {
  color: #B22B31;
}
.ansi-red-intense-bg {
  background-color: #B22B31;
}
.ansi-green-fg {
  color: #00A250;
}
.ansi-green-bg {
  background-color: #00A250;
}
.ansi-green-intense-fg {
  color: #007427;
}
.ansi-green-intense-bg {
  background-color: #007427;
}
.ansi-yellow-fg {
  color: #DDB62B;
}
.ansi-yellow-bg {
  background-color: #DDB62B;
}
.ansi-yellow-intense-fg {
  color: #B27D12;
}
.ansi-yellow-intense-bg {
  background-color: #B27D12;
}
.ansi-blue-fg {
  color: #208FFB;
}
.ansi-blue-bg {
  background-color: #208FFB;
}
.ansi-blue-intense-fg {
  color: #0065CA;
}
.ansi-blue-intense-bg {
  background-color: #0065CA;
}
.ansi-magenta-fg {
  color: #D160C4;
}
.ansi-magenta-bg {
  background-color: #D160C4;
}
.ansi-magenta-intense-fg {
  color: #A03196;
}
.ansi-magenta-intense-bg {
  background-color: #A03196;
}
.ansi-cyan-fg {
  color: #60C6C8;
}
.ansi-cyan-bg {
  background-color: #60C6C8;
}
.ansi-cyan-intense-fg {
  color: #258F8F;
}
.ansi-cyan-intense-bg {
  background-color: #258F8F;
}
.ansi-white-fg {
  color: #C5C1B4;
}
.ansi-white-bg {
  background-color: #C5C1B4;
}
.ansi-white-intense-fg {
  color: #A1A6B2;
}
.ansi-white-intense-bg {
  background-color: #A1A6B2;
}
.ansi-default-inverse-fg {
  color: #FFFFFF;
}
.ansi-default-inverse-bg {
  background-color: #000000;
}
.ansi-bold {
  font-weight: bold;
}
.ansi-underline {
  text-decoration: underline;
}
/* The following styles are deprecated an will be removed in a future version */
.ansibold {
  font-weight: bold;
}
.ansi-inverse {
  outline: 0.5px dotted;
}
/* use dark versions for foreground, to improve visibility */
.ansiblack {
  color: black;
}
.ansired {
  color: darkred;
}
.ansigreen {
  color: darkgreen;
}
.ansiyellow {
  color: #c4a000;
}
.ansiblue {
  color: darkblue;
}
.ansipurple {
  color: darkviolet;
}
.ansicyan {
  color: steelblue;
}
.ansigray {
  color: gray;
}
/* and light for background, for the same reason */
.ansibgblack {
  background-color: black;
}
.ansibgred {
  background-color: red;
}
.ansibggreen {
  background-color: green;
}
.ansibgyellow {
  background-color: yellow;
}
.ansibgblue {
  background-color: blue;
}
.ansibgpurple {
  background-color: magenta;
}
.ansibgcyan {
  background-color: cyan;
}
.ansibggray {
  background-color: gray;
}
div.cell {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
  border-radius: 2px;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  border-width: 1px;
  border-style: solid;
  border-color: transparent;
  width: 100%;
  padding: 5px;
  /* This acts as a spacer between cells, that is outside the border */
  margin: 0px;
  outline: none;
  position: relative;
  overflow: visible;
}
div.cell:before {
  position: absolute;
  display: block;
  top: -1px;
  left: -1px;
  width: 5px;
  height: calc(100% +  2px);
  content: '';
  background: transparent;
}
div.cell.jupyter-soft-selected {
  border-left-color: #E3F2FD;
  border-left-width: 1px;
  padding-left: 5px;
  border-right-color: #E3F2FD;
  border-right-width: 1px;
  background: #E3F2FD;
}
@media print {
  div.cell.jupyter-soft-selected {
    border-color: transparent;
  }
}
div.cell.selected,
div.cell.selected.jupyter-soft-selected {
  border-color: #ababab;
}
div.cell.selected:before,
div.cell.selected.jupyter-soft-selected:before {
  position: absolute;
  display: block;
  top: -1px;
  left: -1px;
  width: 5px;
  height: calc(100% +  2px);
  content: '';
  background: #42A5F5;
}
@media print {
  div.cell.selected,
  div.cell.selected.jupyter-soft-selected {
    border-color: transparent;
  }
}
.edit_mode div.cell.selected {
  border-color: #66BB6A;
}
.edit_mode div.cell.selected:before {
  position: absolute;
  display: block;
  top: -1px;
  left: -1px;
  width: 5px;
  height: calc(100% +  2px);
  content: '';
  background: #66BB6A;
}
@media print {
  .edit_mode div.cell.selected {
    border-color: transparent;
  }
}
.prompt {
  /* This needs to be wide enough for 3 digit prompt numbers: In[100]: */
  min-width: 14ex;
  /* This padding is tuned to match the padding on the CodeMirror editor. */
  padding: 0.4em;
  margin: 0px;
  font-family: monospace;
  text-align: right;
  /* This has to match that of the the CodeMirror class line-height below */
  line-height: 1.21429em;
  /* Don't highlight prompt number selection */
  -webkit-touch-callout: none;
  -webkit-user-select: none;
  -khtml-user-select: none;
  -moz-user-select: none;
  -ms-user-select: none;
  user-select: none;
  /* Use default cursor */
  cursor: default;
}
@media (max-width: 540px) {
  .prompt {
    text-align: left;
  }
}
div.inner_cell {
  min-width: 0;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
  /* Old browsers */
  -webkit-box-flex: 1;
  -moz-box-flex: 1;
  box-flex: 1;
  /* Modern browsers */
  flex: 1;
}
/* input_area and input_prompt must match in top border and margin for alignment */
div.input_area {
  border: 1px solid #cfcfcf;
  border-radius: 2px;
  background: #f7f7f7;
  line-height: 1.21429em;
}
/* This is needed so that empty prompt areas can collapse to zero height when there
   is no content in the output_subarea and the prompt. The main purpose of this is
   to make sure that empty JavaScript output_subareas have no height. */
div.prompt:empty {
  padding-top: 0;
  padding-bottom: 0;
}
div.unrecognized_cell {
  padding: 5px 5px 5px 0px;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
}
div.unrecognized_cell .inner_cell {
  border-radius: 2px;
  padding: 5px;
  font-weight: bold;
  color: red;
  border: 1px solid #cfcfcf;
  background: #eaeaea;
}
div.unrecognized_cell .inner_cell a {
  color: inherit;
  text-decoration: none;
}
div.unrecognized_cell .inner_cell a:hover {
  color: inherit;
  text-decoration: none;
}
@media (max-width: 540px) {
  div.unrecognized_cell > div.prompt {
    display: none;
  }
}
div.code_cell {
  /* avoid page breaking on code cells when printing */
}
@media print {
  div.code_cell {
    page-break-inside: avoid;
  }
}
/* any special styling for code cells that are currently running goes here */
div.input {
  page-break-inside: avoid;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
}
@media (max-width: 540px) {
  div.input {
    /* Old browsers */
    display: -webkit-box;
    -webkit-box-orient: vertical;
    -webkit-box-align: stretch;
    display: -moz-box;
    -moz-box-orient: vertical;
    -moz-box-align: stretch;
    display: box;
    box-orient: vertical;
    box-align: stretch;
    /* Modern browsers */
    display: flex;
    flex-direction: column;
    align-items: stretch;
  }
}
/* input_area and input_prompt must match in top border and margin for alignment */
div.input_prompt {
  color: #303F9F;
  border-top: 1px solid transparent;
}
div.input_area > div.highlight {
  margin: 0.4em;
  border: none;
  padding: 0px;
  background-color: transparent;
}
div.input_area > div.highlight > pre {
  margin: 0px;
  border: none;
  padding: 0px;
  background-color: transparent;
}
/* The following gets added to the <head> if it is detected that the user has a
 * monospace font with inconsistent normal/bold/italic height.  See
 * notebookmain.js.  Such fonts will have keywords vertically offset with
 * respect to the rest of the text.  The user should select a better font.
 * See: https://github.com/ipython/ipython/issues/1503
 *
 * .CodeMirror span {
 *      vertical-align: bottom;
 * }
 */
.CodeMirror {
  line-height: 1.21429em;
  /* Changed from 1em to our global default */
  font-size: 14px;
  height: auto;
  /* Changed to auto to autogrow */
  background: none;
  /* Changed from white to allow our bg to show through */
}
.CodeMirror-scroll {
  /*  The CodeMirror docs are a bit fuzzy on if overflow-y should be hidden or visible.*/
  /*  We have found that if it is visible, vertical scrollbars appear with font size changes.*/
  overflow-y: hidden;
  overflow-x: auto;
}
.CodeMirror-lines {
  /* In CM2, this used to be 0.4em, but in CM3 it went to 4px. We need the em value because */
  /* we have set a different line-height and want this to scale with that. */
  /* Note that this should set vertical padding only, since CodeMirror assumes
       that horizontal padding will be set on CodeMirror pre */
  padding: 0.4em 0;
}
.CodeMirror-linenumber {
  padding: 0 8px 0 4px;
}
.CodeMirror-gutters {
  border-bottom-left-radius: 2px;
  border-top-left-radius: 2px;
}
.CodeMirror pre {
  /* In CM3 this went to 4px from 0 in CM2. This sets horizontal padding only,
    use .CodeMirror-lines for vertical */
  padding: 0 0.4em;
  border: 0;
  border-radius: 0;
}
.CodeMirror-cursor {
  border-left: 1.4px solid black;
}
@media screen and (min-width: 2138px) and (max-width: 4319px) {
  .CodeMirror-cursor {
    border-left: 2px solid black;
  }
}
@media screen and (min-width: 4320px) {
  .CodeMirror-cursor {
    border-left: 4px solid black;
  }
}
/*

Original style from softwaremaniacs.org (c) Ivan Sagalaev <Maniac@SoftwareManiacs.Org>
Adapted from GitHub theme

*/
.highlight-base {
  color: #000;
}
.highlight-variable {
  color: #000;
}
.highlight-variable-2 {
  color: #1a1a1a;
}
.highlight-variable-3 {
  color: #333333;
}
.highlight-string {
  color: #BA2121;
}
.highlight-comment {
  color: #408080;
  font-style: italic;
}
.highlight-number {
  color: #080;
}
.highlight-atom {
  color: #88F;
}
.highlight-keyword {
  color: #008000;
  font-weight: bold;
}
.highlight-builtin {
  color: #008000;
}
.highlight-error {
  color: #f00;
}
.highlight-operator {
  color: #AA22FF;
  font-weight: bold;
}
.highlight-meta {
  color: #AA22FF;
}
/* previously not defined, copying from default codemirror */
.highlight-def {
  color: #00f;
}
.highlight-string-2 {
  color: #f50;
}
.highlight-qualifier {
  color: #555;
}
.highlight-bracket {
  color: #997;
}
.highlight-tag {
  color: #170;
}
.highlight-attribute {
  color: #00c;
}
.highlight-header {
  color: blue;
}
.highlight-quote {
  color: #090;
}
.highlight-link {
  color: #00c;
}
/* apply the same style to codemirror */
.cm-s-ipython span.cm-keyword {
  color: #008000;
  font-weight: bold;
}
.cm-s-ipython span.cm-atom {
  color: #88F;
}
.cm-s-ipython span.cm-number {
  color: #080;
}
.cm-s-ipython span.cm-def {
  color: #00f;
}
.cm-s-ipython span.cm-variable {
  color: #000;
}
.cm-s-ipython span.cm-operator {
  color: #AA22FF;
  font-weight: bold;
}
.cm-s-ipython span.cm-variable-2 {
  color: #1a1a1a;
}
.cm-s-ipython span.cm-variable-3 {
  color: #333333;
}
.cm-s-ipython span.cm-comment {
  color: #408080;
  font-style: italic;
}
.cm-s-ipython span.cm-string {
  color: #BA2121;
}
.cm-s-ipython span.cm-string-2 {
  color: #f50;
}
.cm-s-ipython span.cm-meta {
  color: #AA22FF;
}
.cm-s-ipython span.cm-qualifier {
  color: #555;
}
.cm-s-ipython span.cm-builtin {
  color: #008000;
}
.cm-s-ipython span.cm-bracket {
  color: #997;
}
.cm-s-ipython span.cm-tag {
  color: #170;
}
.cm-s-ipython span.cm-attribute {
  color: #00c;
}
.cm-s-ipython span.cm-header {
  color: blue;
}
.cm-s-ipython span.cm-quote {
  color: #090;
}
.cm-s-ipython span.cm-link {
  color: #00c;
}
.cm-s-ipython span.cm-error {
  color: #f00;
}
.cm-s-ipython span.cm-tab {
  background: url(data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAADAAAAAMCAYAAAAkuj5RAAAAAXNSR0IArs4c6QAAAGFJREFUSMft1LsRQFAQheHPowAKoACx3IgEKtaEHujDjORSgWTH/ZOdnZOcM/sgk/kFFWY0qV8foQwS4MKBCS3qR6ixBJvElOobYAtivseIE120FaowJPN75GMu8j/LfMwNjh4HUpwg4LUAAAAASUVORK5CYII=);
  background-position: right;
  background-repeat: no-repeat;
}
div.output_wrapper {
  /* this position must be relative to enable descendents to be absolute within it */
  position: relative;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
  z-index: 1;
}
/* class for the output area when it should be height-limited */
div.output_scroll {
  /* ideally, this would be max-height, but FF barfs all over that */
  height: 24em;
  /* FF needs this *and the wrapper* to specify full width, or it will shrinkwrap */
  width: 100%;
  overflow: auto;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 2px 8px rgba(0, 0, 0, 0.8);
  box-shadow: inset 0 2px 8px rgba(0, 0, 0, 0.8);
  display: block;
}
/* output div while it is collapsed */
div.output_collapsed {
  margin: 0px;
  padding: 0px;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
}
div.out_prompt_overlay {
  height: 100%;
  padding: 0px 0.4em;
  position: absolute;
  border-radius: 2px;
}
div.out_prompt_overlay:hover {
  /* use inner shadow to get border that is computed the same on WebKit/FF */
  -webkit-box-shadow: inset 0 0 1px #000;
  box-shadow: inset 0 0 1px #000;
  background: rgba(240, 240, 240, 0.5);
}
div.output_prompt {
  color: #D84315;
}
/* This class is the outer container of all output sections. */
div.output_area {
  padding: 0px;
  page-break-inside: avoid;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
}
div.output_area .MathJax_Display {
  text-align: left !important;
}
div.output_area .rendered_html table {
  margin-left: 0;
  margin-right: 0;
}
div.output_area .rendered_html img {
  margin-left: 0;
  margin-right: 0;
}
div.output_area img,
div.output_area svg {
  max-width: 100%;
  height: auto;
}
div.output_area img.unconfined,
div.output_area svg.unconfined {
  max-width: none;
}
div.output_area .mglyph > img {
  max-width: none;
}
/* This is needed to protect the pre formating from global settings such
   as that of bootstrap */
.output {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
}
@media (max-width: 540px) {
  div.output_area {
    /* Old browsers */
    display: -webkit-box;
    -webkit-box-orient: vertical;
    -webkit-box-align: stretch;
    display: -moz-box;
    -moz-box-orient: vertical;
    -moz-box-align: stretch;
    display: box;
    box-orient: vertical;
    box-align: stretch;
    /* Modern browsers */
    display: flex;
    flex-direction: column;
    align-items: stretch;
  }
}
div.output_area pre {
  margin: 0;
  padding: 1px 0 1px 0;
  border: 0;
  vertical-align: baseline;
  color: black;
  background-color: transparent;
  border-radius: 0;
}
/* This class is for the output subarea inside the output_area and after
   the prompt div. */
div.output_subarea {
  overflow-x: auto;
  padding: 0.4em;
  /* Old browsers */
  -webkit-box-flex: 1;
  -moz-box-flex: 1;
  box-flex: 1;
  /* Modern browsers */
  flex: 1;
  max-width: calc(100% - 14ex);
}
div.output_scroll div.output_subarea {
  overflow-x: visible;
}
/* The rest of the output_* classes are for special styling of the different
   output types */
/* all text output has this class: */
div.output_text {
  text-align: left;
  color: #000;
  /* This has to match that of the the CodeMirror class line-height below */
  line-height: 1.21429em;
}
/* stdout/stderr are 'text' as well as 'stream', but execute_result/error are *not* streams */
div.output_stderr {
  background: #fdd;
  /* very light red background for stderr */
}
div.output_latex {
  text-align: left;
}
/* Empty output_javascript divs should have no height */
div.output_javascript:empty {
  padding: 0;
}
.js-error {
  color: darkred;
}
/* raw_input styles */
div.raw_input_container {
  line-height: 1.21429em;
  padding-top: 5px;
}
pre.raw_input_prompt {
  /* nothing needed here. */
}
input.raw_input {
  font-family: monospace;
  font-size: inherit;
  color: inherit;
  width: auto;
  /* make sure input baseline aligns with prompt */
  vertical-align: baseline;
  /* padding + margin = 0.5em between prompt and cursor */
  padding: 0em 0.25em;
  margin: 0em 0.25em;
}
input.raw_input:focus {
  box-shadow: none;
}
p.p-space {
  margin-bottom: 10px;
}
div.output_unrecognized {
  padding: 5px;
  font-weight: bold;
  color: red;
}
div.output_unrecognized a {
  color: inherit;
  text-decoration: none;
}
div.output_unrecognized a:hover {
  color: inherit;
  text-decoration: none;
}
.rendered_html {
  color: #000;
  /* any extras will just be numbers: */
}
.rendered_html em {
  font-style: italic;
}
.rendered_html strong {
  font-weight: bold;
}
.rendered_html u {
  text-decoration: underline;
}
.rendered_html :link {
  text-decoration: underline;
}
.rendered_html :visited {
  text-decoration: underline;
}
.rendered_html h1 {
  font-size: 185.7%;
  margin: 1.08em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
}
.rendered_html h2 {
  font-size: 157.1%;
  margin: 1.27em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
}
.rendered_html h3 {
  font-size: 128.6%;
  margin: 1.55em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
}
.rendered_html h4 {
  font-size: 100%;
  margin: 2em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
}
.rendered_html h5 {
  font-size: 100%;
  margin: 2em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
  font-style: italic;
}
.rendered_html h6 {
  font-size: 100%;
  margin: 2em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
  font-style: italic;
}
.rendered_html h1:first-child {
  margin-top: 0.538em;
}
.rendered_html h2:first-child {
  margin-top: 0.636em;
}
.rendered_html h3:first-child {
  margin-top: 0.777em;
}
.rendered_html h4:first-child {
  margin-top: 1em;
}
.rendered_html h5:first-child {
  margin-top: 1em;
}
.rendered_html h6:first-child {
  margin-top: 1em;
}
.rendered_html ul:not(.list-inline),
.rendered_html ol:not(.list-inline) {
  padding-left: 2em;
}
.rendered_html ul {
  list-style: disc;
}
.rendered_html ul ul {
  list-style: square;
  margin-top: 0;
}
.rendered_html ul ul ul {
  list-style: circle;
}
.rendered_html ol {
  list-style: decimal;
}
.rendered_html ol ol {
  list-style: upper-alpha;
  margin-top: 0;
}
.rendered_html ol ol ol {
  list-style: lower-alpha;
}
.rendered_html ol ol ol ol {
  list-style: lower-roman;
}
.rendered_html ol ol ol ol ol {
  list-style: decimal;
}
.rendered_html * + ul {
  margin-top: 1em;
}
.rendered_html * + ol {
  margin-top: 1em;
}
.rendered_html hr {
  color: black;
  background-color: black;
}
.rendered_html pre {
  margin: 1em 2em;
  padding: 0px;
  background-color: #fff;
}
.rendered_html code {
  background-color: #eff0f1;
}
.rendered_html p code {
  padding: 1px 5px;
}
.rendered_html pre code {
  background-color: #fff;
}
.rendered_html pre,
.rendered_html code {
  border: 0;
  color: #000;
  font-size: 100%;
}
.rendered_html blockquote {
  margin: 1em 2em;
}
.rendered_html table {
  margin-left: auto;
  margin-right: auto;
  border: none;
  border-collapse: collapse;
  border-spacing: 0;
  color: black;
  font-size: 12px;
  table-layout: fixed;
}
.rendered_html thead {
  border-bottom: 1px solid black;
  vertical-align: bottom;
}
.rendered_html tr,
.rendered_html th,
.rendered_html td {
  text-align: right;
  vertical-align: middle;
  padding: 0.5em 0.5em;
  line-height: normal;
  white-space: normal;
  max-width: none;
  border: none;
}
.rendered_html th {
  font-weight: bold;
}
.rendered_html tbody tr:nth-child(odd) {
  background: #f5f5f5;
}
.rendered_html tbody tr:hover {
  background: rgba(66, 165, 245, 0.2);
}
.rendered_html * + table {
  margin-top: 1em;
}
.rendered_html p {
  text-align: left;
}
.rendered_html * + p {
  margin-top: 1em;
}
.rendered_html img {
  display: block;
  margin-left: auto;
  margin-right: auto;
}
.rendered_html * + img {
  margin-top: 1em;
}
.rendered_html img,
.rendered_html svg {
  max-width: 100%;
  height: auto;
}
.rendered_html img.unconfined,
.rendered_html svg.unconfined {
  max-width: none;
}
.rendered_html .alert {
  margin-bottom: initial;
}
.rendered_html * + .alert {
  margin-top: 1em;
}
[dir="rtl"] .rendered_html p {
  text-align: right;
}
div.text_cell {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
}
@media (max-width: 540px) {
  div.text_cell > div.prompt {
    display: none;
  }
}
div.text_cell_render {
  /*font-family: "Helvetica Neue", Arial, Helvetica, Geneva, sans-serif;*/
  outline: none;
  resize: none;
  width: inherit;
  border-style: none;
  padding: 0.5em 0.5em 0.5em 0.4em;
  color: #000;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
}
a.anchor-link:link {
  text-decoration: none;
  padding: 0px 20px;
  visibility: hidden;
}
h1:hover .anchor-link,
h2:hover .anchor-link,
h3:hover .anchor-link,
h4:hover .anchor-link,
h5:hover .anchor-link,
h6:hover .anchor-link {
  visibility: visible;
}
.text_cell.rendered .input_area {
  display: none;
}
.text_cell.rendered .rendered_html {
  overflow-x: auto;
  overflow-y: hidden;
}
.text_cell.rendered .rendered_html tr,
.text_cell.rendered .rendered_html th,
.text_cell.rendered .rendered_html td {
  max-width: none;
}
.text_cell.unrendered .text_cell_render {
  display: none;
}
.text_cell .dropzone .input_area {
  border: 2px dashed #bababa;
  margin: -1px;
}
.cm-header-1,
.cm-header-2,
.cm-header-3,
.cm-header-4,
.cm-header-5,
.cm-header-6 {
  font-weight: bold;
  font-family: "Helvetica Neue", Helvetica, Arial, sans-serif;
}
.cm-header-1 {
  font-size: 185.7%;
}
.cm-header-2 {
  font-size: 157.1%;
}
.cm-header-3 {
  font-size: 128.6%;
}
.cm-header-4 {
  font-size: 110%;
}
.cm-header-5 {
  font-size: 100%;
  font-style: italic;
}
.cm-header-6 {
  font-size: 100%;
  font-style: italic;
}
/*!
*
* IPython notebook webapp
*
*/
@media (max-width: 767px) {
  .notebook_app {
    padding-left: 0px;
    padding-right: 0px;
  }
}
#ipython-main-app {
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  height: 100%;
}
div#notebook_panel {
  margin: 0px;
  padding: 0px;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  height: 100%;
}
div#notebook {
  font-size: 14px;
  line-height: 20px;
  overflow-y: hidden;
  overflow-x: auto;
  width: 100%;
  /* This spaces the page away from the edge of the notebook area */
  padding-top: 20px;
  margin: 0px;
  outline: none;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  min-height: 100%;
}
@media not print {
  #notebook-container {
    padding: 15px;
    background-color: #fff;
    min-height: 0;
    -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
    box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  }
}
@media print {
  #notebook-container {
    width: 100%;
  }
}
div.ui-widget-content {
  border: 1px solid #ababab;
  outline: none;
}
pre.dialog {
  background-color: #f7f7f7;
  border: 1px solid #ddd;
  border-radius: 2px;
  padding: 0.4em;
  padding-left: 2em;
}
p.dialog {
  padding: 0.2em;
}
/* Word-wrap output correctly.  This is the CSS3 spelling, though Firefox seems
   to not honor it correctly.  Webkit browsers (Chrome, rekonq, Safari) do.
 */
pre,
code,
kbd,
samp {
  white-space: pre-wrap;
}
#fonttest {
  font-family: monospace;
}
p {
  margin-bottom: 0;
}
.end_space {
  min-height: 100px;
  transition: height .2s ease;
}
.notebook_app > #header {
  -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
}
@media not print {
  .notebook_app {
    background-color: #EEE;
  }
}
kbd {
  border-style: solid;
  border-width: 1px;
  box-shadow: none;
  margin: 2px;
  padding-left: 2px;
  padding-right: 2px;
  padding-top: 1px;
  padding-bottom: 1px;
}
.jupyter-keybindings {
  padding: 1px;
  line-height: 24px;
  border-bottom: 1px solid gray;
}
.jupyter-keybindings input {
  margin: 0;
  padding: 0;
  border: none;
}
.jupyter-keybindings i {
  padding: 6px;
}
.well code {
  background-color: #ffffff;
  border-color: #ababab;
  border-width: 1px;
  border-style: solid;
  padding: 2px;
  padding-top: 1px;
  padding-bottom: 1px;
}
/* CSS for the cell toolbar */
.celltoolbar {
  border: thin solid #CFCFCF;
  border-bottom: none;
  background: #EEE;
  border-radius: 2px 2px 0px 0px;
  width: 100%;
  height: 29px;
  padding-right: 4px;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
  /* Old browsers */
  -webkit-box-pack: end;
  -moz-box-pack: end;
  box-pack: end;
  /* Modern browsers */
  justify-content: flex-end;
  display: -webkit-flex;
}
@media print {
  .celltoolbar {
    display: none;
  }
}
.ctb_hideshow {
  display: none;
  vertical-align: bottom;
}
/* ctb_show is added to the ctb_hideshow div to show the cell toolbar.
   Cell toolbars are only shown when the ctb_global_show class is also set.
*/
.ctb_global_show .ctb_show.ctb_hideshow {
  display: block;
}
.ctb_global_show .ctb_show + .input_area,
.ctb_global_show .ctb_show + div.text_cell_input,
.ctb_global_show .ctb_show ~ div.text_cell_render {
  border-top-right-radius: 0px;
  border-top-left-radius: 0px;
}
.ctb_global_show .ctb_show ~ div.text_cell_render {
  border: 1px solid #cfcfcf;
}
.celltoolbar {
  font-size: 87%;
  padding-top: 3px;
}
.celltoolbar select {
  display: block;
  width: 100%;
  height: 32px;
  padding: 6px 12px;
  font-size: 13px;
  line-height: 1.42857143;
  color: #555555;
  background-color: #fff;
  background-image: none;
  border: 1px solid #ccc;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  -webkit-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  -o-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  height: 30px;
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
  width: inherit;
  font-size: inherit;
  height: 22px;
  padding: 0px;
  display: inline-block;
}
.celltoolbar select:focus {
  border-color: #66afe9;
  outline: 0;
  -webkit-box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
  box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
}
.celltoolbar select::-moz-placeholder {
  color: #999;
  opacity: 1;
}
.celltoolbar select:-ms-input-placeholder {
  color: #999;
}
.celltoolbar select::-webkit-input-placeholder {
  color: #999;
}
.celltoolbar select::-ms-expand {
  border: 0;
  background-color: transparent;
}
.celltoolbar select[disabled],
.celltoolbar select[readonly],
fieldset[disabled] .celltoolbar select {
  background-color: #eeeeee;
  opacity: 1;
}
.celltoolbar select[disabled],
fieldset[disabled] .celltoolbar select {
  cursor: not-allowed;
}
textarea.celltoolbar select {
  height: auto;
}
select.celltoolbar select {
  height: 30px;
  line-height: 30px;
}
textarea.celltoolbar select,
select[multiple].celltoolbar select {
  height: auto;
}
.celltoolbar label {
  margin-left: 5px;
  margin-right: 5px;
}
.tags_button_container {
  width: 100%;
  display: flex;
}
.tag-container {
  display: flex;
  flex-direction: row;
  flex-grow: 1;
  overflow: hidden;
  position: relative;
}
.tag-container > * {
  margin: 0 4px;
}
.remove-tag-btn {
  margin-left: 4px;
}
.tags-input {
  display: flex;
}
.cell-tag:last-child:after {
  content: "";
  position: absolute;
  right: 0;
  width: 40px;
  height: 100%;
  /* Fade to background color of cell toolbar */
  background: linear-gradient(to right, rgba(0, 0, 0, 0), #EEE);
}
.tags-input > * {
  margin-left: 4px;
}
.cell-tag,
.tags-input input,
.tags-input button {
  display: block;
  width: 100%;
  height: 32px;
  padding: 6px 12px;
  font-size: 13px;
  line-height: 1.42857143;
  color: #555555;
  background-color: #fff;
  background-image: none;
  border: 1px solid #ccc;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  -webkit-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  -o-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  height: 30px;
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
  box-shadow: none;
  width: inherit;
  font-size: inherit;
  height: 22px;
  line-height: 22px;
  padding: 0px 4px;
  display: inline-block;
}
.cell-tag:focus,
.tags-input input:focus,
.tags-input button:focus {
  border-color: #66afe9;
  outline: 0;
  -webkit-box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
  box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
}
.cell-tag::-moz-placeholder,
.tags-input input::-moz-placeholder,
.tags-input button::-moz-placeholder {
  color: #999;
  opacity: 1;
}
.cell-tag:-ms-input-placeholder,
.tags-input input:-ms-input-placeholder,
.tags-input button:-ms-input-placeholder {
  color: #999;
}
.cell-tag::-webkit-input-placeholder,
.tags-input input::-webkit-input-placeholder,
.tags-input button::-webkit-input-placeholder {
  color: #999;
}
.cell-tag::-ms-expand,
.tags-input input::-ms-expand,
.tags-input button::-ms-expand {
  border: 0;
  background-color: transparent;
}
.cell-tag[disabled],
.tags-input input[disabled],
.tags-input button[disabled],
.cell-tag[readonly],
.tags-input input[readonly],
.tags-input button[readonly],
fieldset[disabled] .cell-tag,
fieldset[disabled] .tags-input input,
fieldset[disabled] .tags-input button {
  background-color: #eeeeee;
  opacity: 1;
}
.cell-tag[disabled],
.tags-input input[disabled],
.tags-input button[disabled],
fieldset[disabled] .cell-tag,
fieldset[disabled] .tags-input input,
fieldset[disabled] .tags-input button {
  cursor: not-allowed;
}
textarea.cell-tag,
textarea.tags-input input,
textarea.tags-input button {
  height: auto;
}
select.cell-tag,
select.tags-input input,
select.tags-input button {
  height: 30px;
  line-height: 30px;
}
textarea.cell-tag,
textarea.tags-input input,
textarea.tags-input button,
select[multiple].cell-tag,
select[multiple].tags-input input,
select[multiple].tags-input button {
  height: auto;
}
.cell-tag,
.tags-input button {
  padding: 0px 4px;
}
.cell-tag {
  background-color: #fff;
  white-space: nowrap;
}
.tags-input input[type=text]:focus {
  outline: none;
  box-shadow: none;
  border-color: #ccc;
}
.completions {
  position: absolute;
  z-index: 110;
  overflow: hidden;
  border: 1px solid #ababab;
  border-radius: 2px;
  -webkit-box-shadow: 0px 6px 10px -1px #adadad;
  box-shadow: 0px 6px 10px -1px #adadad;
  line-height: 1;
}
.completions select {
  background: white;
  outline: none;
  border: none;
  padding: 0px;
  margin: 0px;
  overflow: auto;
  font-family: monospace;
  font-size: 110%;
  color: #000;
  width: auto;
}
.completions select option.context {
  color: #286090;
}
#kernel_logo_widget .current_kernel_logo {
  display: none;
  margin-top: -1px;
  margin-bottom: -1px;
  width: 32px;
  height: 32px;
}
[dir="rtl"] #kernel_logo_widget {
  float: left !important;
  float: left;
}
.modal .modal-body .move-path {
  display: flex;
  flex-direction: row;
  justify-content: space;
  align-items: center;
}
.modal .modal-body .move-path .server-root {
  padding-right: 20px;
}
.modal .modal-body .move-path .path-input {
  flex: 1;
}
#menubar {
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  margin-top: 1px;
}
#menubar .navbar {
  border-top: 1px;
  border-radius: 0px 0px 2px 2px;
  margin-bottom: 0px;
}
#menubar .navbar-toggle {
  float: left;
  padding-top: 7px;
  padding-bottom: 7px;
  border: none;
}
#menubar .navbar-collapse {
  clear: left;
}
[dir="rtl"] #menubar .navbar-toggle {
  float: right;
}
[dir="rtl"] #menubar .navbar-collapse {
  clear: right;
}
[dir="rtl"] #menubar .navbar-nav {
  float: right;
}
[dir="rtl"] #menubar .nav {
  padding-right: 0px;
}
[dir="rtl"] #menubar .navbar-nav > li {
  float: right;
}
[dir="rtl"] #menubar .navbar-right {
  float: left !important;
}
[dir="rtl"] ul.dropdown-menu {
  text-align: right;
  left: auto;
}
[dir="rtl"] ul#new-menu.dropdown-menu {
  right: auto;
  left: 0;
}
.nav-wrapper {
  border-bottom: 1px solid #e7e7e7;
}
i.menu-icon {
  padding-top: 4px;
}
[dir="rtl"] i.menu-icon.pull-right {
  float: left !important;
  float: left;
}
ul#help_menu li a {
  overflow: hidden;
  padding-right: 2.2em;
}
ul#help_menu li a i {
  margin-right: -1.2em;
}
[dir="rtl"] ul#help_menu li a {
  padding-left: 2.2em;
}
[dir="rtl"] ul#help_menu li a i {
  margin-right: 0;
  margin-left: -1.2em;
}
[dir="rtl"] ul#help_menu li a i.pull-right {
  float: left !important;
  float: left;
}
.dropdown-submenu {
  position: relative;
}
.dropdown-submenu > .dropdown-menu {
  top: 0;
  left: 100%;
  margin-top: -6px;
  margin-left: -1px;
}
[dir="rtl"] .dropdown-submenu > .dropdown-menu {
  right: 100%;
  margin-right: -1px;
}
.dropdown-submenu:hover > .dropdown-menu {
  display: block;
}
.dropdown-submenu > a:after {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  display: block;
  content: "\f0da";
  float: right;
  color: #333333;
  margin-top: 2px;
  margin-right: -10px;
}
.dropdown-submenu > a:after.fa-pull-left {
  margin-right: .3em;
}
.dropdown-submenu > a:after.fa-pull-right {
  margin-left: .3em;
}
.dropdown-submenu > a:after.pull-left {
  margin-right: .3em;
}
.dropdown-submenu > a:after.pull-right {
  margin-left: .3em;
}
[dir="rtl"] .dropdown-submenu > a:after {
  float: left;
  content: "\f0d9";
  margin-right: 0;
  margin-left: -10px;
}
.dropdown-submenu:hover > a:after {
  color: #262626;
}
.dropdown-submenu.pull-left {
  float: none;
}
.dropdown-submenu.pull-left > .dropdown-menu {
  left: -100%;
  margin-left: 10px;
}
#notification_area {
  float: right !important;
  float: right;
  z-index: 10;
}
[dir="rtl"] #notification_area {
  float: left !important;
  float: left;
}
.indicator_area {
  float: right !important;
  float: right;
  color: #777;
  margin-left: 5px;
  margin-right: 5px;
  width: 11px;
  z-index: 10;
  text-align: center;
  width: auto;
}
[dir="rtl"] .indicator_area {
  float: left !important;
  float: left;
}
#kernel_indicator {
  float: right !important;
  float: right;
  color: #777;
  margin-left: 5px;
  margin-right: 5px;
  width: 11px;
  z-index: 10;
  text-align: center;
  width: auto;
  border-left: 1px solid;
}
#kernel_indicator .kernel_indicator_name {
  padding-left: 5px;
  padding-right: 5px;
}
[dir="rtl"] #kernel_indicator {
  float: left !important;
  float: left;
  border-left: 0;
  border-right: 1px solid;
}
#modal_indicator {
  float: right !important;
  float: right;
  color: #777;
  margin-left: 5px;
  margin-right: 5px;
  width: 11px;
  z-index: 10;
  text-align: center;
  width: auto;
}
[dir="rtl"] #modal_indicator {
  float: left !important;
  float: left;
}
#readonly-indicator {
  float: right !important;
  float: right;
  color: #777;
  margin-left: 5px;
  margin-right: 5px;
  width: 11px;
  z-index: 10;
  text-align: center;
  width: auto;
  margin-top: 2px;
  margin-bottom: 0px;
  margin-left: 0px;
  margin-right: 0px;
  display: none;
}
.modal_indicator:before {
  width: 1.28571429em;
  text-align: center;
}
.edit_mode .modal_indicator:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f040";
}
.edit_mode .modal_indicator:before.fa-pull-left {
  margin-right: .3em;
}
.edit_mode .modal_indicator:before.fa-pull-right {
  margin-left: .3em;
}
.edit_mode .modal_indicator:before.pull-left {
  margin-right: .3em;
}
.edit_mode .modal_indicator:before.pull-right {
  margin-left: .3em;
}
.command_mode .modal_indicator:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: ' ';
}
.command_mode .modal_indicator:before.fa-pull-left {
  margin-right: .3em;
}
.command_mode .modal_indicator:before.fa-pull-right {
  margin-left: .3em;
}
.command_mode .modal_indicator:before.pull-left {
  margin-right: .3em;
}
.command_mode .modal_indicator:before.pull-right {
  margin-left: .3em;
}
.kernel_idle_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f10c";
}
.kernel_idle_icon:before.fa-pull-left {
  margin-right: .3em;
}
.kernel_idle_icon:before.fa-pull-right {
  margin-left: .3em;
}
.kernel_idle_icon:before.pull-left {
  margin-right: .3em;
}
.kernel_idle_icon:before.pull-right {
  margin-left: .3em;
}
.kernel_busy_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f111";
}
.kernel_busy_icon:before.fa-pull-left {
  margin-right: .3em;
}
.kernel_busy_icon:before.fa-pull-right {
  margin-left: .3em;
}
.kernel_busy_icon:before.pull-left {
  margin-right: .3em;
}
.kernel_busy_icon:before.pull-right {
  margin-left: .3em;
}
.kernel_dead_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f1e2";
}
.kernel_dead_icon:before.fa-pull-left {
  margin-right: .3em;
}
.kernel_dead_icon:before.fa-pull-right {
  margin-left: .3em;
}
.kernel_dead_icon:before.pull-left {
  margin-right: .3em;
}
.kernel_dead_icon:before.pull-right {
  margin-left: .3em;
}
.kernel_disconnected_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f127";
}
.kernel_disconnected_icon:before.fa-pull-left {
  margin-right: .3em;
}
.kernel_disconnected_icon:before.fa-pull-right {
  margin-left: .3em;
}
.kernel_disconnected_icon:before.pull-left {
  margin-right: .3em;
}
.kernel_disconnected_icon:before.pull-right {
  margin-left: .3em;
}
.notification_widget {
  color: #777;
  z-index: 10;
  background: rgba(240, 240, 240, 0.5);
  margin-right: 4px;
  color: #333;
  background-color: #fff;
  border-color: #ccc;
}
.notification_widget:focus,
.notification_widget.focus {
  color: #333;
  background-color: #e6e6e6;
  border-color: #8c8c8c;
}
.notification_widget:hover {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
.notification_widget:active,
.notification_widget.active,
.open > .dropdown-toggle.notification_widget {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
.notification_widget:active:hover,
.notification_widget.active:hover,
.open > .dropdown-toggle.notification_widget:hover,
.notification_widget:active:focus,
.notification_widget.active:focus,
.open > .dropdown-toggle.notification_widget:focus,
.notification_widget:active.focus,
.notification_widget.active.focus,
.open > .dropdown-toggle.notification_widget.focus {
  color: #333;
  background-color: #d4d4d4;
  border-color: #8c8c8c;
}
.notification_widget:active,
.notification_widget.active,
.open > .dropdown-toggle.notification_widget {
  background-image: none;
}
.notification_widget.disabled:hover,
.notification_widget[disabled]:hover,
fieldset[disabled] .notification_widget:hover,
.notification_widget.disabled:focus,
.notification_widget[disabled]:focus,
fieldset[disabled] .notification_widget:focus,
.notification_widget.disabled.focus,
.notification_widget[disabled].focus,
fieldset[disabled] .notification_widget.focus {
  background-color: #fff;
  border-color: #ccc;
}
.notification_widget .badge {
  color: #fff;
  background-color: #333;
}
.notification_widget.warning {
  color: #fff;
  background-color: #f0ad4e;
  border-color: #eea236;
}
.notification_widget.warning:focus,
.notification_widget.warning.focus {
  color: #fff;
  background-color: #ec971f;
  border-color: #985f0d;
}
.notification_widget.warning:hover {
  color: #fff;
  background-color: #ec971f;
  border-color: #d58512;
}
.notification_widget.warning:active,
.notification_widget.warning.active,
.open > .dropdown-toggle.notification_widget.warning {
  color: #fff;
  background-color: #ec971f;
  border-color: #d58512;
}
.notification_widget.warning:active:hover,
.notification_widget.warning.active:hover,
.open > .dropdown-toggle.notification_widget.warning:hover,
.notification_widget.warning:active:focus,
.notification_widget.warning.active:focus,
.open > .dropdown-toggle.notification_widget.warning:focus,
.notification_widget.warning:active.focus,
.notification_widget.warning.active.focus,
.open > .dropdown-toggle.notification_widget.warning.focus {
  color: #fff;
  background-color: #d58512;
  border-color: #985f0d;
}
.notification_widget.warning:active,
.notification_widget.warning.active,
.open > .dropdown-toggle.notification_widget.warning {
  background-image: none;
}
.notification_widget.warning.disabled:hover,
.notification_widget.warning[disabled]:hover,
fieldset[disabled] .notification_widget.warning:hover,
.notification_widget.warning.disabled:focus,
.notification_widget.warning[disabled]:focus,
fieldset[disabled] .notification_widget.warning:focus,
.notification_widget.warning.disabled.focus,
.notification_widget.warning[disabled].focus,
fieldset[disabled] .notification_widget.warning.focus {
  background-color: #f0ad4e;
  border-color: #eea236;
}
.notification_widget.warning .badge {
  color: #f0ad4e;
  background-color: #fff;
}
.notification_widget.success {
  color: #fff;
  background-color: #5cb85c;
  border-color: #4cae4c;
}
.notification_widget.success:focus,
.notification_widget.success.focus {
  color: #fff;
  background-color: #449d44;
  border-color: #255625;
}
.notification_widget.success:hover {
  color: #fff;
  background-color: #449d44;
  border-color: #398439;
}
.notification_widget.success:active,
.notification_widget.success.active,
.open > .dropdown-toggle.notification_widget.success {
  color: #fff;
  background-color: #449d44;
  border-color: #398439;
}
.notification_widget.success:active:hover,
.notification_widget.success.active:hover,
.open > .dropdown-toggle.notification_widget.success:hover,
.notification_widget.success:active:focus,
.notification_widget.success.active:focus,
.open > .dropdown-toggle.notification_widget.success:focus,
.notification_widget.success:active.focus,
.notification_widget.success.active.focus,
.open > .dropdown-toggle.notification_widget.success.focus {
  color: #fff;
  background-color: #398439;
  border-color: #255625;
}
.notification_widget.success:active,
.notification_widget.success.active,
.open > .dropdown-toggle.notification_widget.success {
  background-image: none;
}
.notification_widget.success.disabled:hover,
.notification_widget.success[disabled]:hover,
fieldset[disabled] .notification_widget.success:hover,
.notification_widget.success.disabled:focus,
.notification_widget.success[disabled]:focus,
fieldset[disabled] .notification_widget.success:focus,
.notification_widget.success.disabled.focus,
.notification_widget.success[disabled].focus,
fieldset[disabled] .notification_widget.success.focus {
  background-color: #5cb85c;
  border-color: #4cae4c;
}
.notification_widget.success .badge {
  color: #5cb85c;
  background-color: #fff;
}
.notification_widget.info {
  color: #fff;
  background-color: #5bc0de;
  border-color: #46b8da;
}
.notification_widget.info:focus,
.notification_widget.info.focus {
  color: #fff;
  background-color: #31b0d5;
  border-color: #1b6d85;
}
.notification_widget.info:hover {
  color: #fff;
  background-color: #31b0d5;
  border-color: #269abc;
}
.notification_widget.info:active,
.notification_widget.info.active,
.open > .dropdown-toggle.notification_widget.info {
  color: #fff;
  background-color: #31b0d5;
  border-color: #269abc;
}
.notification_widget.info:active:hover,
.notification_widget.info.active:hover,
.open > .dropdown-toggle.notification_widget.info:hover,
.notification_widget.info:active:focus,
.notification_widget.info.active:focus,
.open > .dropdown-toggle.notification_widget.info:focus,
.notification_widget.info:active.focus,
.notification_widget.info.active.focus,
.open > .dropdown-toggle.notification_widget.info.focus {
  color: #fff;
  background-color: #269abc;
  border-color: #1b6d85;
}
.notification_widget.info:active,
.notification_widget.info.active,
.open > .dropdown-toggle.notification_widget.info {
  background-image: none;
}
.notification_widget.info.disabled:hover,
.notification_widget.info[disabled]:hover,
fieldset[disabled] .notification_widget.info:hover,
.notification_widget.info.disabled:focus,
.notification_widget.info[disabled]:focus,
fieldset[disabled] .notification_widget.info:focus,
.notification_widget.info.disabled.focus,
.notification_widget.info[disabled].focus,
fieldset[disabled] .notification_widget.info.focus {
  background-color: #5bc0de;
  border-color: #46b8da;
}
.notification_widget.info .badge {
  color: #5bc0de;
  background-color: #fff;
}
.notification_widget.danger {
  color: #fff;
  background-color: #d9534f;
  border-color: #d43f3a;
}
.notification_widget.danger:focus,
.notification_widget.danger.focus {
  color: #fff;
  background-color: #c9302c;
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}
.notification_widget.danger:hover {
  color: #fff;
  background-color: #c9302c;
  border-color: #ac2925;
}
.notification_widget.danger:active,
.notification_widget.danger.active,
.open > .dropdown-toggle.notification_widget.danger {
  color: #fff;
  background-color: #c9302c;
  border-color: #ac2925;
}
.notification_widget.danger:active:hover,
.notification_widget.danger.active:hover,
.open > .dropdown-toggle.notification_widget.danger:hover,
.notification_widget.danger:active:focus,
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.open > .dropdown-toggle.notification_widget.danger:focus,
.notification_widget.danger:active.focus,
.notification_widget.danger.active.focus,
.open > .dropdown-toggle.notification_widget.danger.focus {
  color: #fff;
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  border-color: #761c19;
}
.notification_widget.danger:active,
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.open > .dropdown-toggle.notification_widget.danger {
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.notification_widget.danger.disabled:hover,
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fieldset[disabled] .notification_widget.danger:hover,
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.notification_widget.danger[disabled]:focus,
fieldset[disabled] .notification_widget.danger:focus,
.notification_widget.danger.disabled.focus,
.notification_widget.danger[disabled].focus,
fieldset[disabled] .notification_widget.danger.focus {
  background-color: #d9534f;
  border-color: #d43f3a;
}
.notification_widget.danger .badge {
  color: #d9534f;
  background-color: #fff;
}
div#pager {
  background-color: #fff;
  font-size: 14px;
  line-height: 20px;
  overflow: hidden;
  display: none;
  position: fixed;
  bottom: 0px;
  width: 100%;
  max-height: 50%;
  padding-top: 8px;
  -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  /* Display over codemirror */
  z-index: 100;
  /* Hack which prevents jquery ui resizable from changing top. */
  top: auto !important;
}
div#pager pre {
  line-height: 1.21429em;
  color: #000;
  background-color: #f7f7f7;
  padding: 0.4em;
}
div#pager #pager-button-area {
  position: absolute;
  top: 8px;
  right: 20px;
}
div#pager #pager-contents {
  position: relative;
  overflow: auto;
  width: 100%;
  height: 100%;
}
div#pager #pager-contents #pager-container {
  position: relative;
  padding: 15px 0px;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
}
div#pager .ui-resizable-handle {
  top: 0px;
  height: 8px;
  background: #f7f7f7;
  border-top: 1px solid #cfcfcf;
  border-bottom: 1px solid #cfcfcf;
  /* This injects handle bars (a short, wide = symbol) for
        the resize handle. */
}
div#pager .ui-resizable-handle::after {
  content: '';
  top: 2px;
  left: 50%;
  height: 3px;
  width: 30px;
  margin-left: -15px;
  position: absolute;
  border-top: 1px solid #cfcfcf;
}
.quickhelp {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
  line-height: 1.8em;
}
.shortcut_key {
  display: inline-block;
  width: 21ex;
  text-align: right;
  font-family: monospace;
}
.shortcut_descr {
  display: inline-block;
  /* Old browsers */
  -webkit-box-flex: 1;
  -moz-box-flex: 1;
  box-flex: 1;
  /* Modern browsers */
  flex: 1;
}
span.save_widget {
  height: 30px;
  margin-top: 4px;
  display: flex;
  justify-content: flex-start;
  align-items: baseline;
  width: 50%;
  flex: 1;
}
span.save_widget span.filename {
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  line-height: 1em;
  margin-left: 16px;
  border: none;
  font-size: 146.5%;
  text-overflow: ellipsis;
  overflow: hidden;
  white-space: nowrap;
  border-radius: 2px;
}
span.save_widget span.filename:hover {
  background-color: #e6e6e6;
}
[dir="rtl"] span.save_widget.pull-left {
  float: right !important;
  float: right;
}
[dir="rtl"] span.save_widget span.filename {
  margin-left: 0;
  margin-right: 16px;
}
span.checkpoint_status,
span.autosave_status {
  font-size: small;
  white-space: nowrap;
  padding: 0 5px;
}
@media (max-width: 767px) {
  span.save_widget {
    font-size: small;
    padding: 0 0 0 5px;
  }
  span.checkpoint_status,
  span.autosave_status {
    display: none;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  span.checkpoint_status {
    display: none;
  }
  span.autosave_status {
    font-size: x-small;
  }
}
.toolbar {
  padding: 0px;
  margin-left: -5px;
  margin-top: 2px;
  margin-bottom: 5px;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
}
.toolbar select,
.toolbar label {
  width: auto;
  vertical-align: middle;
  margin-right: 2px;
  margin-bottom: 0px;
  display: inline;
  font-size: 92%;
  margin-left: 0.3em;
  margin-right: 0.3em;
  padding: 0px;
  padding-top: 3px;
}
.toolbar .btn {
  padding: 2px 8px;
}
.toolbar .btn-group {
  margin-top: 0px;
  margin-left: 5px;
}
.toolbar-btn-label {
  margin-left: 6px;
}
#maintoolbar {
  margin-bottom: -3px;
  margin-top: -8px;
  border: 0px;
  min-height: 27px;
  margin-left: 0px;
  padding-top: 11px;
  padding-bottom: 3px;
}
#maintoolbar .navbar-text {
  float: none;
  vertical-align: middle;
  text-align: right;
  margin-left: 5px;
  margin-right: 0px;
  margin-top: 0px;
}
.select-xs {
  height: 24px;
}
[dir="rtl"] .btn-group > .btn,
.btn-group-vertical > .btn {
  float: right;
}
.pulse,
.dropdown-menu > li > a.pulse,
li.pulse > a.dropdown-toggle,
li.pulse.open > a.dropdown-toggle {
  background-color: #F37626;
  color: white;
}
/**
 * Primary styles
 *
 * Author: Jupyter Development Team
 */
/** WARNING IF YOU ARE EDITTING THIS FILE, if this is a .css file, It has a lot
 * of chance of beeing generated from the ../less/[samename].less file, you can
 * try to get back the less file by reverting somme commit in history
 **/
/*
 * We'll try to get something pretty, so we
 * have some strange css to have the scroll bar on
 * the left with fix button on the top right of the tooltip
 */
@-moz-keyframes fadeOut {
  from {
    opacity: 1;
  }
  to {
    opacity: 0;
  }
}
@-webkit-keyframes fadeOut {
  from {
    opacity: 1;
  }
  to {
    opacity: 0;
  }
}
@-moz-keyframes fadeIn {
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    opacity: 0;
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  to {
    opacity: 1;
  }
}
@-webkit-keyframes fadeIn {
  from {
    opacity: 0;
  }
  to {
    opacity: 1;
  }
}
/*properties of tooltip after "expand"*/
.bigtooltip {
  overflow: auto;
  height: 200px;
  -webkit-transition-property: height;
  -webkit-transition-duration: 500ms;
  -moz-transition-property: height;
  -moz-transition-duration: 500ms;
  transition-property: height;
  transition-duration: 500ms;
}
/*properties of tooltip before "expand"*/
.smalltooltip {
  -webkit-transition-property: height;
  -webkit-transition-duration: 500ms;
  -moz-transition-property: height;
  -moz-transition-duration: 500ms;
  transition-property: height;
  transition-duration: 500ms;
  text-overflow: ellipsis;
  overflow: hidden;
  height: 80px;
}
.tooltipbuttons {
  position: absolute;
  padding-right: 15px;
  top: 0px;
  right: 0px;
}
.tooltiptext {
  /*avoid the button to overlap on some docstring*/
  padding-right: 30px;
}
.ipython_tooltip {
  max-width: 700px;
  /*fade-in animation when inserted*/
  -webkit-animation: fadeOut 400ms;
  -moz-animation: fadeOut 400ms;
  animation: fadeOut 400ms;
  -webkit-animation: fadeIn 400ms;
  -moz-animation: fadeIn 400ms;
  animation: fadeIn 400ms;
  vertical-align: middle;
  background-color: #f7f7f7;
  overflow: visible;
  border: #ababab 1px solid;
  outline: none;
  padding: 3px;
  margin: 0px;
  padding-left: 7px;
  font-family: monospace;
  min-height: 50px;
  -moz-box-shadow: 0px 6px 10px -1px #adadad;
  -webkit-box-shadow: 0px 6px 10px -1px #adadad;
  box-shadow: 0px 6px 10px -1px #adadad;
  border-radius: 2px;
  position: absolute;
  z-index: 1000;
}
.ipython_tooltip a {
  float: right;
}
.ipython_tooltip .tooltiptext pre {
  border: 0;
  border-radius: 0;
  font-size: 100%;
  background-color: #f7f7f7;
}
.pretooltiparrow {
  left: 0px;
  margin: 0px;
  top: -16px;
  width: 40px;
  height: 16px;
  overflow: hidden;
  position: absolute;
}
.pretooltiparrow:before {
  background-color: #f7f7f7;
  border: 1px #ababab solid;
  z-index: 11;
  content: "";
  position: absolute;
  left: 15px;
  top: 10px;
  width: 25px;
  height: 25px;
  -webkit-transform: rotate(45deg);
  -moz-transform: rotate(45deg);
  -ms-transform: rotate(45deg);
  -o-transform: rotate(45deg);
}
ul.typeahead-list i {
  margin-left: -10px;
  width: 18px;
}
[dir="rtl"] ul.typeahead-list i {
  margin-left: 0;
  margin-right: -10px;
}
ul.typeahead-list {
  max-height: 80vh;
  overflow: auto;
}
ul.typeahead-list > li > a {
  /** Firefox bug **/
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  white-space: normal;
}
ul.typeahead-list  > li > a.pull-right {
  float: left !important;
  float: left;
}
[dir="rtl"] .typeahead-list {
  text-align: right;
}
.cmd-palette .modal-body {
  padding: 7px;
}
.cmd-palette form {
  background: white;
}
.cmd-palette input {
  outline: none;
}
.no-shortcut {
  min-width: 20px;
  color: transparent;
}
[dir="rtl"] .no-shortcut.pull-right {
  float: left !important;
  float: left;
}
[dir="rtl"] .command-shortcut.pull-right {
  float: left !important;
  float: left;
}
.command-shortcut:before {
  content: "(command mode)";
  padding-right: 3px;
  color: #777777;
}
.edit-shortcut:before {
  content: "(edit)";
  padding-right: 3px;
  color: #777777;
}
[dir="rtl"] .edit-shortcut.pull-right {
  float: left !important;
  float: left;
}
#find-and-replace #replace-preview .match,
#find-and-replace #replace-preview .insert {
  background-color: #BBDEFB;
  border-color: #90CAF9;
  border-style: solid;
  border-width: 1px;
  border-radius: 0px;
}
[dir="ltr"] #find-and-replace .input-group-btn + .form-control {
  border-left: none;
}
[dir="rtl"] #find-and-replace .input-group-btn + .form-control {
  border-right: none;
}
#find-and-replace #replace-preview .replace .match {
  background-color: #FFCDD2;
  border-color: #EF9A9A;
  border-radius: 0px;
}
#find-and-replace #replace-preview .replace .insert {
  background-color: #C8E6C9;
  border-color: #A5D6A7;
  border-radius: 0px;
}
#find-and-replace #replace-preview {
  max-height: 60vh;
  overflow: auto;
}
#find-and-replace #replace-preview pre {
  padding: 5px 10px;
}
.terminal-app {
  background: #EEE;
}
.terminal-app #header {
  background: #fff;
  -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
}
.terminal-app .terminal {
  width: 100%;
  float: left;
  font-family: monospace;
  color: white;
  background: black;
  padding: 0.4em;
  border-radius: 2px;
  -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.4);
  box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.4);
}
.terminal-app .terminal,
.terminal-app .terminal dummy-screen {
  line-height: 1em;
  font-size: 14px;
}
.terminal-app .terminal .xterm-rows {
  padding: 10px;
}
.terminal-app .terminal-cursor {
  color: black;
  background: white;
}
.terminal-app #terminado-container {
  margin-top: 20px;
}
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    page-break-inside: avoid;
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  div.output {
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    page-break-inside: avoid;
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}
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<link rel="stylesheet" href="custom.css">

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</div><div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<h1 id="Data-Analytics-Final-Project---Speed-Dating-Predictions">Data Analytics Final Project - Speed Dating Predictions<a class="anchor-link" href="#Data-Analytics-Final-Project---Speed-Dating-Predictions">&#182;</a></h1>
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</div>
</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div><div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<p>By: Chasen Mauldin, Ian Hoang, Aidan Manning, Son K Do</p>

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<h3 id="The-data-science-problem-we-are-trying-to-solve:">The data science problem we are trying to solve:<a class="anchor-link" href="#The-data-science-problem-we-are-trying-to-solve:">&#182;</a></h3>
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<li>What characteristics and interests of an individual influence their match rates while speed dating?</li>
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<h3 id="Why-does-the-problem-matter?">Why does the problem matter?<a class="anchor-link" href="#Why-does-the-problem-matter?">&#182;</a></h3>
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<li>Many people participate in speed dating and desire a sense of value and urn for a romantic relationship with others. At the end of these said speed dates, a lot of people go unmatched and have a feeling of confusion and of being undesirable. In a world of artificial presentation through social media and online dating, how can we be more genuine while also improving our match rates.</li>
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<h3 id="The-results-of-our-predictive-model-can-be-used-for:">The results of our predictive model can be used for:<a class="anchor-link" href="#The-results-of-our-predictive-model-can-be-used-for:">&#182;</a></h3>
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<li>This provides further insight into current day applications of online dating and could be used to improve match algorithms and methods.</li>
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<h3 id="We-are-wanting-to-be-able-to-predict-this-because:">We are wanting to be able to predict this because:<a class="anchor-link" href="#We-are-wanting-to-be-able-to-predict-this-because:">&#182;</a></h3>
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<li>By understanding the information and the relationships between these features and match rates, we’ll better understand what generally influences first impressions in speed dating events or online interests.</li>
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<h3 id="Description-of-the-dataset:">Description of the dataset:<a class="anchor-link" href="#Description-of-the-dataset:">&#182;</a></h3>
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<li>The dataset we are using was recordings from speed dating results between 2002 and 2004. The main purpose was to see what key contributors were influencing first impressions during speed dating.</li>
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<h3 id="Total-number-of-records-of-the-dataset:">Total number of records of the dataset:<a class="anchor-link" href="#Total-number-of-records-of-the-dataset:">&#182;</a></h3>
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<li>There were originally 8,379 records in our dataset. After cleaning, we narrowed it down to 516 records.</li>
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<h3 id="Dataset-total-number-of--features:">Dataset total number of  features:<a class="anchor-link" href="#Dataset-total-number-of--features:">&#182;</a></h3>
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<li>There were originally 195 features. After data cleaning, we narrowed it down to the relevant 31 features for our study. A few of which include number of matches, careers, age, interests, and more. </li>
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<h3 id="What-can-you-try-to-predict-in-this-dataset?">What can you try to predict in this dataset?<a class="anchor-link" href="#What-can-you-try-to-predict-in-this-dataset?">&#182;</a></h3>
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<li><p>From this dataset, we can try to predict a match rate range based on the characteristics of an individual including age, gender, and career as well as their  interests such as yoga, sports, tv, etc.</p>
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<li><p>We could also use the features in this dataset to make other predictions. For example, we could solely focus on a couple specific features, such as preferred race and religion, and discover how those two features contribute to an individual’s match rate.</p>
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<h3 id="Is-this-a-labeled-dataset,-appropriate-for-a-supervised-learning-classification-problem?">Is this a labeled dataset, appropriate for a supervised learning classification problem?<a class="anchor-link" href="#Is-this-a-labeled-dataset,-appropriate-for-a-supervised-learning-classification-problem?">&#182;</a></h3>
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<li>Yes, the data is labeled; the labels are the <code>match</code> field. In the uncleaned data set, this was a boolean value for whether or not someone got a match. In our cleaned version, it gives the percentage of matches dependent on how many people they speed dated.</li>
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<h3 id="Link-to-the-dataset:">Link to the dataset:<a class="anchor-link" href="#Link-to-the-dataset:">&#182;</a></h3>
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<p>Link: <a href="https://data.world/annavmontoya/speed-dating-experiment/workspace/file?filename=Speed+Dating+Data.csv">https://data.world/annavmontoya/speed-dating-experiment/workspace/file?filename=Speed+Dating+Data.csv</a></p>

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<h1 id="0.-Data-Cleaning">0. Data Cleaning<a class="anchor-link" href="#0.-Data-Cleaning">&#182;</a></h1>
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<li>Originally, the dataset contains records for each interaction between two participants. Since the project only focuses on the percentage of how many matches a person will get, we counted up the number of matches each unique person got based on whether the “match” label was 0 or 1. This reduced the records from more than 8000 to 515 unique people who participated in the speed-dating event. </li>
<li>Records from events with confined requirements such as “only undergraduate students” in wave 5 are not included in the final dataset as we want the data to be more random. </li>
<li>Using Google Sheet Conditional Formatting, we were able to identify empty cells in the original data. Records with more than 5 missing cells/columns are deleted. For missing data in the “Age” column, the cell is replaced with the average of the age of people who attend the same event (wave). For missing data in the “career” column, the cell is replaced with the mode of people who attend the same event (wave). </li>
<li>Columns with significant number of missing data, such as “match_es” which indicate the person’s prediction of how many matches he/she gets, are deleted from the dataset</li>
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<h1 id="1.-Featured-Engineering">1. Featured Engineering<a class="anchor-link" href="#1.-Featured-Engineering">&#182;</a></h1>
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<li>To accurately predict the percentage of matches, we transform the continuous attribute “match” into several bins of categorical/nominal attribute (Bin 1 is 0 &lt; match &lt;0.1, etc…). The process of binning is done in Part 2.</li>
<li>In part 5, before doing KNN classifier, the whole dataset is scaled to [0,1]. In order to improve the accuracy of the model, several other feature engineering techniques were used. Sampling was done by reducing the dataset records number to 475 in part 6b. We also tried wrapper method in part 6a by running the model with a subset of attributes. Unfortunately, neither method provides significant improvement on the accuracy or the recall of the model.</li>
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<h1 id="2.-Import-data-and-prepare-bin-range-for-match">2. Import data and prepare bin range for match<a class="anchor-link" href="#2.-Import-data-and-prepare-bin-range-for-match">&#182;</a></h1>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">import</span> <span class="nn">warnings</span>
<span class="n">warnings</span><span class="o">.</span><span class="n">simplefilter</span><span class="p">(</span><span class="s2">&quot;ignore&quot;</span><span class="p">)</span>
<span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span>
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="kn">import</span> <span class="nn">sklearn</span> <span class="k">as</span> <span class="nn">sk</span>
<span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="k">as</span> <span class="nn">plt</span>
<span class="kn">import</span> <span class="nn">time</span>

<span class="c1">#read the CSV</span>
<span class="n">data</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">read_csv</span><span class="p">(</span><span class="s2">&quot;speed_dating_data.csv&quot;</span><span class="p">)</span>
<span class="n">missing_values</span> <span class="o">=</span> <span class="p">[</span><span class="s1">&#39;&#39;</span><span class="p">,</span> <span class="s1">&#39; &#39;</span><span class="p">]</span>

<span class="n">cnt</span><span class="o">=</span><span class="mi">0</span>
<span class="k">for</span> <span class="n">row</span> <span class="ow">in</span> <span class="n">data</span><span class="p">:</span>
    <span class="k">try</span><span class="p">:</span>
        <span class="nb">int</span><span class="p">(</span><span class="n">row</span><span class="p">)</span> <span class="c1">#try converting to an int</span>
        <span class="n">data</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">cnt</span><span class="p">]</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">nan</span> <span class="c1">#it worked, make it nan</span>
    <span class="k">except</span> <span class="ne">ValueError</span><span class="p">:</span>
        <span class="k">pass</span> <span class="c1">#it did not work, must be a string, leave it be</span>
    <span class="n">cnt</span><span class="o">+=</span><span class="mi">1</span>

<span class="c1">#create new columns</span>
<span class="c1">#no matches</span>
<span class="n">data</span><span class="p">[</span><span class="s2">&quot;no_matches&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="n">data</span><span class="p">[</span><span class="s2">&quot;match&quot;</span><span class="p">]</span>
<span class="c1">#0.01 - 0.25</span>
<span class="n">data</span><span class="p">[</span><span class="s2">&quot;matches1&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="n">data</span><span class="p">[</span><span class="s2">&quot;match&quot;</span><span class="p">]</span>
<span class="c1">#0.25+ - 0.5</span>
<span class="n">data</span><span class="p">[</span><span class="s2">&quot;matches2&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="n">data</span><span class="p">[</span><span class="s2">&quot;match&quot;</span><span class="p">]</span>
<span class="c1">#0.50+ - 0.75</span>
<span class="n">data</span><span class="p">[</span><span class="s2">&quot;matches3&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="n">data</span><span class="p">[</span><span class="s2">&quot;match&quot;</span><span class="p">]</span>
<span class="c1">#0.75+ - 1.0</span>
<span class="n">data</span><span class="p">[</span><span class="s2">&quot;matches4&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="n">data</span><span class="p">[</span><span class="s2">&quot;match&quot;</span><span class="p">]</span>


<span class="c1">#hot encode based on match rates</span>
<span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">data</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">0</span><span class="p">]):</span>
    <span class="c1">#bin them into three separate columns</span>
    <span class="c1">#no match bin</span>
    <span class="k">if</span> <span class="p">(</span><span class="n">data</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">i</span><span class="p">,</span> <span class="s2">&quot;match&quot;</span><span class="p">])</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span>
        <span class="n">data</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">i</span><span class="p">,</span><span class="s2">&quot;no_matches&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="mi">1</span>
    <span class="k">else</span><span class="p">:</span>
        <span class="n">data</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">i</span><span class="p">,</span><span class="s2">&quot;no_matches&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="mi">0</span>

<span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">data</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">0</span><span class="p">]):</span>
    <span class="c1">#bin 0.01=0.25</span>
    <span class="k">if</span> <span class="p">(</span><span class="n">data</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">i</span><span class="p">,</span> <span class="s2">&quot;match&quot;</span><span class="p">])</span> <span class="o">&gt;</span> <span class="mi">0</span> <span class="ow">and</span> <span class="p">(</span><span class="n">data</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">i</span><span class="p">,</span> <span class="s2">&quot;match&quot;</span><span class="p">])</span> <span class="o">&lt;</span> <span class="mf">0.25</span><span class="p">:</span>
        <span class="n">data</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">i</span><span class="p">,</span><span class="s2">&quot;matches1&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="mi">1</span>
    <span class="k">else</span><span class="p">:</span>
        <span class="n">data</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">i</span><span class="p">,</span><span class="s2">&quot;matches1&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="mi">0</span>


<span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">data</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">0</span><span class="p">]):</span>
    <span class="k">if</span> <span class="p">(</span><span class="n">data</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">i</span><span class="p">,</span> <span class="s2">&quot;match&quot;</span><span class="p">])</span> <span class="o">&gt;=</span> <span class="mf">0.25</span> <span class="ow">and</span> <span class="p">(</span><span class="n">data</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">i</span><span class="p">,</span> <span class="s2">&quot;match&quot;</span><span class="p">])</span> <span class="o">&lt;</span> <span class="mf">0.50</span><span class="p">:</span>
        <span class="n">data</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">i</span><span class="p">,</span><span class="s2">&quot;matches2&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="mi">1</span>
    <span class="k">else</span><span class="p">:</span>
        <span class="n">data</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">i</span><span class="p">,</span><span class="s2">&quot;matches2&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="mi">0</span>

<span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">data</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">0</span><span class="p">]):</span>
    <span class="k">if</span> <span class="p">(</span><span class="n">data</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">i</span><span class="p">,</span> <span class="s2">&quot;match&quot;</span><span class="p">])</span> <span class="o">&gt;=</span> <span class="mf">0.50</span> <span class="ow">and</span> <span class="p">(</span><span class="n">data</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">i</span><span class="p">,</span> <span class="s2">&quot;match&quot;</span><span class="p">])</span> <span class="o">&lt;</span> <span class="mf">0.75</span><span class="p">:</span>
        <span class="n">data</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">i</span><span class="p">,</span><span class="s2">&quot;matches3&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="mi">1</span>
    <span class="k">else</span><span class="p">:</span>
        <span class="n">data</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">i</span><span class="p">,</span><span class="s2">&quot;matches3&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="mi">0</span>

<span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">data</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">0</span><span class="p">]):</span>
    <span class="k">if</span> <span class="p">(</span><span class="n">data</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">i</span><span class="p">,</span> <span class="s2">&quot;match&quot;</span><span class="p">])</span> <span class="o">&gt;=</span> <span class="mf">0.75</span> <span class="ow">and</span> <span class="p">(</span><span class="n">data</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">i</span><span class="p">,</span> <span class="s2">&quot;match&quot;</span><span class="p">])</span> <span class="o">&lt;=</span> <span class="mf">1.0</span><span class="p">:</span>
        <span class="n">data</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">i</span><span class="p">,</span><span class="s2">&quot;matches4&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="mi">1</span>
    <span class="k">else</span><span class="p">:</span>
        <span class="n">data</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">i</span><span class="p">,</span><span class="s2">&quot;matches4&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="mi">0</span>

<span class="n">ori_data</span> <span class="o">=</span> <span class="n">data</span>
<span class="c1"># print(data.shape)</span>
<span class="n">data</span><span class="o">.</span><span class="n">head</span><span class="p">(</span><span class="mi">10</span><span class="p">)</span>
</pre></div>

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<div>
<style scoped>
    .dataframe tbody tr th:only-of-type {
        vertical-align: middle;
    }

    .dataframe tbody tr th {
        vertical-align: top;
    }

    .dataframe thead th {
        text-align: right;
    }
</style>
<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>iid</th>
      <th>gender</th>
      <th>wave</th>
      <th>round</th>
      <th>match</th>
      <th>age</th>
      <th>race</th>
      <th>imprace</th>
      <th>imprelig</th>
      <th>goal</th>
      <th>...</th>
      <th>concerts</th>
      <th>music</th>
      <th>shopping</th>
      <th>yoga</th>
      <th>match_es</th>
      <th>no_matches</th>
      <th>matches1</th>
      <th>matches2</th>
      <th>matches3</th>
      <th>matches4</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <td>0</td>
      <td>1</td>
      <td>0</td>
      <td>1</td>
      <td>10</td>
      <td>0.4</td>
      <td>21</td>
      <td>4</td>
      <td>2</td>
      <td>4</td>
      <td>2</td>
      <td>...</td>
      <td>10</td>
      <td>9</td>
      <td>8</td>
      <td>1</td>
      <td>4.0</td>
      <td>0.0</td>
      <td>0.0</td>
      <td>1.0</td>
      <td>0.0</td>
      <td>0.0</td>
    </tr>
    <tr>
      <td>1</td>
      <td>2</td>
      <td>0</td>
      <td>1</td>
      <td>10</td>
      <td>0.2</td>
      <td>24</td>
      <td>2</td>
      <td>2</td>
      <td>5</td>
      <td>1</td>
      <td>...</td>
      <td>7</td>
      <td>8</td>
      <td>3</td>
      <td>1</td>
      <td>3.0</td>
      <td>0.0</td>
      <td>1.0</td>
      <td>0.0</td>
      <td>0.0</td>
      <td>0.0</td>
    </tr>
    <tr>
      <td>2</td>
      <td>3</td>
      <td>0</td>
      <td>1</td>
      <td>10</td>
      <td>0.0</td>
      <td>25</td>
      <td>2</td>
      <td>8</td>
      <td>4</td>
      <td>6</td>
      <td>...</td>
      <td>7</td>
      <td>5</td>
      <td>8</td>
      <td>7</td>
      <td>NaN</td>
      <td>1.0</td>
      <td>0.0</td>
      <td>0.0</td>
      <td>0.0</td>
      <td>0.0</td>
    </tr>
    <tr>
      <td>3</td>
      <td>4</td>
      <td>0</td>
      <td>1</td>
      <td>10</td>
      <td>0.2</td>
      <td>23</td>
      <td>2</td>
      <td>1</td>
      <td>1</td>
      <td>1</td>
      <td>...</td>
      <td>8</td>
      <td>7</td>
      <td>1</td>
      <td>8</td>
      <td>2.0</td>
      <td>0.0</td>
      <td>1.0</td>
      <td>0.0</td>
      <td>0.0</td>
      <td>0.0</td>
    </tr>
    <tr>
      <td>4</td>
      <td>5</td>
      <td>0</td>
      <td>1</td>
      <td>10</td>
      <td>0.2</td>
      <td>21</td>
      <td>2</td>
      <td>8</td>
      <td>1</td>
      <td>2</td>
      <td>...</td>
      <td>3</td>
      <td>7</td>
      <td>8</td>
      <td>3</td>
      <td>NaN</td>
      <td>0.0</td>
      <td>1.0</td>
      <td>0.0</td>
      <td>0.0</td>
      <td>0.0</td>
    </tr>
    <tr>
      <td>5</td>
      <td>6</td>
      <td>0</td>
      <td>1</td>
      <td>10</td>
      <td>0.2</td>
      <td>23</td>
      <td>4</td>
      <td>1</td>
      <td>1</td>
      <td>1</td>
      <td>...</td>
      <td>6</td>
      <td>4</td>
      <td>1</td>
      <td>1</td>
      <td>4.0</td>
      <td>0.0</td>
      <td>1.0</td>
      <td>0.0</td>
      <td>0.0</td>
      <td>0.0</td>
    </tr>
    <tr>
      <td>6</td>
      <td>7</td>
      <td>0</td>
      <td>1</td>
      <td>10</td>
      <td>0.2</td>
      <td>22</td>
      <td>4</td>
      <td>2</td>
      <td>4</td>
      <td>1</td>
      <td>...</td>
      <td>10</td>
      <td>10</td>
      <td>10</td>
      <td>10</td>
      <td>2.0</td>
      <td>0.0</td>
      <td>1.0</td>
      <td>0.0</td>
      <td>0.0</td>
      <td>0.0</td>
    </tr>
    <tr>
      <td>7</td>
      <td>8</td>
      <td>0</td>
      <td>1</td>
      <td>10</td>
      <td>0.8</td>
      <td>25</td>
      <td>2</td>
      <td>1</td>
      <td>1</td>
      <td>1</td>
      <td>...</td>
      <td>6</td>
      <td>6</td>
      <td>8</td>
      <td>6</td>
      <td>NaN</td>
      <td>0.0</td>
      <td>0.0</td>
      <td>0.0</td>
      <td>0.0</td>
      <td>1.0</td>
    </tr>
    <tr>
      <td>8</td>
      <td>9</td>
      <td>0</td>
      <td>1</td>
      <td>10</td>
      <td>0.7</td>
      <td>26</td>
      <td>6</td>
      <td>1</td>
      <td>1</td>
      <td>1</td>
      <td>...</td>
      <td>9</td>
      <td>9</td>
      <td>8</td>
      <td>3</td>
      <td>1.0</td>
      <td>0.0</td>
      <td>0.0</td>
      <td>0.0</td>
      <td>1.0</td>
      <td>0.0</td>
    </tr>
    <tr>
      <td>9</td>
      <td>10</td>
      <td>0</td>
      <td>1</td>
      <td>10</td>
      <td>0.2</td>
      <td>26</td>
      <td>2</td>
      <td>4</td>
      <td>4</td>
      <td>2</td>
      <td>...</td>
      <td>7</td>
      <td>8</td>
      <td>7</td>
      <td>7</td>
      <td>NaN</td>
      <td>0.0</td>
      <td>1.0</td>
      <td>0.0</td>
      <td>0.0</td>
      <td>0.0</td>
    </tr>
  </tbody>
</table>
<p>10 rows × 36 columns</p>
</div>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Drop unnecessary column</span>
<span class="n">data</span> <span class="o">=</span> <span class="n">data</span><span class="o">.</span><span class="n">drop</span><span class="p">([</span><span class="s1">&#39;iid&#39;</span><span class="p">,</span> <span class="s1">&#39;round&#39;</span><span class="p">,</span> <span class="s1">&#39;wave&#39;</span><span class="p">,</span> <span class="s1">&#39;match&#39;</span><span class="p">,</span> <span class="s1">&#39;match_es&#39;</span><span class="p">,],</span>  <span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>

<span class="n">data</span><span class="o">.</span><span class="n">head</span><span class="p">()</span>
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<style scoped>
    .dataframe tbody tr th:only-of-type {
        vertical-align: middle;
    }

    .dataframe tbody tr th {
        vertical-align: top;
    }

    .dataframe thead th {
        text-align: right;
    }
</style>
<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>gender</th>
      <th>age</th>
      <th>race</th>
      <th>imprace</th>
      <th>imprelig</th>
      <th>goal</th>
      <th>date</th>
      <th>go_out</th>
      <th>career_c</th>
      <th>sports</th>
      <th>...</th>
      <th>movies</th>
      <th>concerts</th>
      <th>music</th>
      <th>shopping</th>
      <th>yoga</th>
      <th>no_matches</th>
      <th>matches1</th>
      <th>matches2</th>
      <th>matches3</th>
      <th>matches4</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <td>0</td>
      <td>0</td>
      <td>21</td>
      <td>4</td>
      <td>2</td>
      <td>4</td>
      <td>2</td>
      <td>7</td>
      <td>1</td>
      <td>1</td>
      <td>9</td>
      <td>...</td>
      <td>10</td>
      <td>10</td>
      <td>9</td>
      <td>8</td>
      <td>1</td>
      <td>0.0</td>
      <td>0.0</td>
      <td>1.0</td>
      <td>0.0</td>
      <td>0.0</td>
    </tr>
    <tr>
      <td>1</td>
      <td>0</td>
      <td>24</td>
      <td>2</td>
      <td>2</td>
      <td>5</td>
      <td>1</td>
      <td>5</td>
      <td>1</td>
      <td>1</td>
      <td>3</td>
      <td>...</td>
      <td>8</td>
      <td>7</td>
      <td>8</td>
      <td>3</td>
      <td>1</td>
      <td>0.0</td>
      <td>1.0</td>
      <td>0.0</td>
      <td>0.0</td>
      <td>0.0</td>
    </tr>
    <tr>
      <td>2</td>
      <td>0</td>
      <td>25</td>
      <td>2</td>
      <td>8</td>
      <td>4</td>
      <td>6</td>
      <td>3</td>
      <td>1</td>
      <td>7</td>
      <td>3</td>
      <td>...</td>
      <td>7</td>
      <td>7</td>
      <td>5</td>
      <td>8</td>
      <td>7</td>
      <td>1.0</td>
      <td>0.0</td>
      <td>0.0</td>
      <td>0.0</td>
      <td>0.0</td>
    </tr>
    <tr>
      <td>3</td>
      <td>0</td>
      <td>23</td>
      <td>2</td>
      <td>1</td>
      <td>1</td>
      <td>1</td>
      <td>5</td>
      <td>1</td>
      <td>1</td>
      <td>1</td>
      <td>...</td>
      <td>7</td>
      <td>8</td>
      <td>7</td>
      <td>1</td>
      <td>8</td>
      <td>0.0</td>
      <td>1.0</td>
      <td>0.0</td>
      <td>0.0</td>
      <td>0.0</td>
    </tr>
    <tr>
      <td>4</td>
      <td>0</td>
      <td>21</td>
      <td>2</td>
      <td>8</td>
      <td>1</td>
      <td>2</td>
      <td>4</td>
      <td>1</td>
      <td>1</td>
      <td>7</td>
      <td>...</td>
      <td>6</td>
      <td>3</td>
      <td>7</td>
      <td>8</td>
      <td>3</td>
      <td>0.0</td>
      <td>1.0</td>
      <td>0.0</td>
      <td>0.0</td>
      <td>0.0</td>
    </tr>
  </tbody>
</table>
<p>5 rows × 31 columns</p>
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<h1 id="3.-Data-Exploration">3. Data Exploration<a class="anchor-link" href="#3.-Data-Exploration">&#182;</a></h1>
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<h2 id="a.-Bivariate-Analysis-on-match-percentage-and-preference-on-having-the-same-religion:">a. Bivariate Analysis on match percentage and preference on having the same religion:<a class="anchor-link" href="#a.-Bivariate-Analysis-on-match-percentage-and-preference-on-having-the-same-religion:">&#182;</a></h2>
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<h4 id="imprelig--How-important-is-it-to-you-(on-a-scale-of-1-10)-that-a-person-you-date-be-of-the-same-religious-background?">imprelig- How important is it to you (on a scale of 1-10) that a person you date be of the same religious background?<a class="anchor-link" href="#imprelig--How-important-is-it-to-you-(on-a-scale-of-1-10)-that-a-person-you-date-be-of-the-same-religious-background?">&#182;</a></h4>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">ori_data</span><span class="o">.</span><span class="n">plot</span><span class="o">.</span><span class="n">scatter</span><span class="p">(</span><span class="n">y</span><span class="o">=</span><span class="s1">&#39;match&#39;</span><span class="p">,</span> <span class="n">x</span><span class="o">=</span><span class="s1">&#39;imprelig&#39;</span><span class="p">)</span>
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<pre>&lt;matplotlib.axes._subplots.AxesSubplot at 0x10ba9c810&gt;</pre>
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<h3 id="Using-this-Bivariate-Analysis.-You-can-tell-that-people-who-care-less-about-their-partner-being-the-same-religion-as-them,-would-in-turn-get-a-higher-percentange-of-matches.">Using this Bivariate Analysis. You can tell that people who care less about their partner being the same religion as them, would in turn get a higher percentange of matches.<a class="anchor-link" href="#Using-this-Bivariate-Analysis.-You-can-tell-that-people-who-care-less-about-their-partner-being-the-same-religion-as-them,-would-in-turn-get-a-higher-percentange-of-matches.">&#182;</a></h3>
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<h2 id="b.-Bivariate-Analysis-on-match-percentage-and-preference-on-being-the-same-race:">b. Bivariate Analysis on match percentage and preference on being the same race:<a class="anchor-link" href="#b.-Bivariate-Analysis-on-match-percentage-and-preference-on-being-the-same-race:">&#182;</a></h2>
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<h4 id="imprace---How-important-is-it-to-you-(on-a-scale-of-1-10)-that-a-person-you-date-be-of-the-same-racial/ethnic-background?">imprace - How important is it to you (on a scale of 1-10) that a person you date be of the same racial/ethnic background?<a class="anchor-link" href="#imprace---How-important-is-it-to-you-(on-a-scale-of-1-10)-that-a-person-you-date-be-of-the-same-racial/ethnic-background?">&#182;</a></h4>
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<div class="prompt input_prompt">In&nbsp;[4]:</div>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">ori_data</span><span class="o">.</span><span class="n">plot</span><span class="o">.</span><span class="n">scatter</span><span class="p">(</span><span class="n">y</span><span class="o">=</span><span class="s1">&#39;match&#39;</span><span class="p">,</span> <span class="n">x</span><span class="o">=</span><span class="s1">&#39;imprace&#39;</span><span class="p">)</span>
</pre></div>

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    <div class="prompt output_prompt">Out[4]:</div>


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<pre>&lt;matplotlib.axes._subplots.AxesSubplot at 0xa1e173310&gt;</pre>
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<img 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<h3 id="Using-this-Bivariate-Analysis.-Just-like-prefered-religion,-you-can-tell-that-people-who-care-less-about-their-partner-being-the-same-race-or-having-the-same-ethnic-background-as-them,-would-in-turn-get-a-higher-percentange-of-matches.">Using this Bivariate Analysis. Just like prefered religion, you can tell that people who care less about their partner being the same race or having the same ethnic background as them, would in turn get a higher percentange of matches.<a class="anchor-link" href="#Using-this-Bivariate-Analysis.-Just-like-prefered-religion,-you-can-tell-that-people-who-care-less-about-their-partner-being-the-same-race-or-having-the-same-ethnic-background-as-them,-would-in-turn-get-a-higher-percentange-of-matches.">&#182;</a></h3>
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<h2 id="c.-Pie-Chart-showing-total-amount-of-each-gender-participating-in-the-study">c. Pie Chart showing total amount of each gender participating in the study<a class="anchor-link" href="#c.-Pie-Chart-showing-total-amount-of-each-gender-participating-in-the-study">&#182;</a></h2>
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<div class="prompt input_prompt">In&nbsp;[5]:</div>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">groups</span> <span class="o">=</span> <span class="n">data</span><span class="o">.</span><span class="n">groupby</span><span class="p">(</span><span class="s1">&#39;gender&#39;</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="n">groups</span><span class="o">.</span><span class="n">size</span><span class="p">())</span> <span class="c1"># groups.size() is a Series object</span>
<span class="n">groups</span><span class="o">.</span><span class="n">size</span><span class="p">()</span><span class="o">.</span><span class="n">plot</span><span class="o">.</span><span class="n">pie</span><span class="p">()</span>
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<pre>gender
0    254
1    261
dtype: int64
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<pre>&lt;matplotlib.axes._subplots.AxesSubplot at 0xa1e25a2d0&gt;</pre>
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<h2 id="d.-Bivariate-Analysis-on-match-percentage-and-gender:">d. Bivariate Analysis on match percentage and gender:<a class="anchor-link" href="#d.-Bivariate-Analysis-on-match-percentage-and-gender:">&#182;</a></h2>
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<div class="prompt input_prompt">In&nbsp;[6]:</div>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">ori_data</span><span class="o">.</span><span class="n">plot</span><span class="o">.</span><span class="n">scatter</span><span class="p">(</span><span class="n">y</span><span class="o">=</span><span class="s1">&#39;match&#39;</span><span class="p">,</span> <span class="n">x</span><span class="o">=</span><span class="s1">&#39;gender&#39;</span><span class="p">)</span>
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<pre>&lt;matplotlib.axes._subplots.AxesSubplot at 0xa1e2f1a50&gt;</pre>
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<h3 id="Using-this-Bivariate-Analysis.-Males-(1.0-in-the-graph-above)-seemed-to-be-cluster-more-densely--towards-the-lower-match-percentage-where-as-Females-(0.0-in-the-graph-above)-seemed-to-be-a-little-higher-in-match-perentange-relative-to-the-density-of-the-points.">Using this Bivariate Analysis. Males (1.0 in the graph above) seemed to be cluster more densely  towards the lower match percentage where as Females (0.0 in the graph above) seemed to be a little higher in match perentange relative to the density of the points.<a class="anchor-link" href="#Using-this-Bivariate-Analysis.-Males-(1.0-in-the-graph-above)-seemed-to-be-cluster-more-densely--towards-the-lower-match-percentage-where-as-Females-(0.0-in-the-graph-above)-seemed-to-be-a-little-higher-in-match-perentange-relative-to-the-density-of-the-points.">&#182;</a></h3>
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<h1 id="4.-Naive-Bayes-Classifier">4. Naive Bayes Classifier<a class="anchor-link" href="#4.-Naive-Bayes-Classifier">&#182;</a></h1>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">from</span> <span class="nn">sklearn.naive_bayes</span> <span class="k">import</span> <span class="n">GaussianNB</span>
<span class="kn">from</span> <span class="nn">sklearn.model_selection</span> <span class="k">import</span> <span class="n">cross_val_score</span>
<span class="kn">from</span> <span class="nn">sklearn.model_selection</span> <span class="k">import</span> <span class="n">cross_val_predict</span>
<span class="kn">from</span> <span class="nn">sklearn.metrics</span> <span class="k">import</span> <span class="n">confusion_matrix</span>
<span class="kn">from</span> <span class="nn">sklearn.metrics</span> <span class="k">import</span> <span class="n">classification_report</span>

<span class="n">gnb</span> <span class="o">=</span> <span class="n">GaussianNB</span><span class="p">()</span>

<span class="c1">#split class labels from predictor labels</span>
<span class="n">l</span> <span class="o">=</span> <span class="p">[</span><span class="s1">&#39;no_matches&#39;</span><span class="p">,</span> <span class="s1">&#39;matches1&#39;</span><span class="p">,</span> <span class="s1">&#39;matches2&#39;</span><span class="p">,</span> <span class="s1">&#39;matches3&#39;</span><span class="p">,</span> <span class="s1">&#39;matches4&#39;</span><span class="p">]</span>
<span class="n">res</span> <span class="o">=</span> <span class="p">{}</span>

<span class="k">for</span> <span class="n">d</span> <span class="ow">in</span> <span class="n">l</span><span class="p">:</span>
    <span class="n">data_Y</span> <span class="o">=</span> <span class="n">data</span><span class="p">[</span><span class="n">d</span><span class="p">]</span>
    <span class="n">data_X</span> <span class="o">=</span> <span class="n">data</span><span class="o">.</span><span class="n">drop</span><span class="p">([</span><span class="s1">&#39;no_matches&#39;</span><span class="p">,</span> <span class="s1">&#39;matches1&#39;</span><span class="p">,</span> <span class="s1">&#39;matches2&#39;</span><span class="p">,</span> <span class="s1">&#39;matches3&#39;</span><span class="p">,</span> <span class="s1">&#39;matches4&#39;</span><span class="p">],</span>  <span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>

    <span class="c1"># data_Y.head(10)</span>
    <span class="c1"># data_X.head(10)</span>

    <span class="n">cvs</span> <span class="o">=</span> <span class="n">cross_val_score</span><span class="p">(</span><span class="n">gnb</span><span class="p">,</span> <span class="n">data_X</span><span class="p">,</span> <span class="n">data_Y</span><span class="p">,</span> <span class="n">cv</span><span class="o">=</span><span class="mi">10</span><span class="p">)</span>
    <span class="n">a</span> <span class="o">=</span> <span class="n">cvs</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span><span class="o">*</span><span class="mi">100</span>

    <span class="n">cvp</span> <span class="o">=</span> <span class="n">cross_val_predict</span><span class="p">(</span><span class="n">gnb</span><span class="p">,</span> <span class="n">data_X</span><span class="p">,</span> <span class="n">data_Y</span><span class="p">,</span> <span class="n">cv</span><span class="o">=</span><span class="mi">10</span><span class="p">)</span>
    <span class="nb">print</span><span class="p">(</span><span class="n">classification_report</span><span class="p">(</span><span class="n">data_Y</span><span class="p">,</span> <span class="n">cvp</span><span class="p">))</span>

    <span class="n">res</span><span class="p">[</span><span class="n">d</span><span class="p">]</span> <span class="o">=</span> <span class="n">a</span>

<span class="c1">#print accuracy of every bin</span>
<span class="k">for</span> <span class="n">v</span> <span class="ow">in</span> <span class="n">res</span><span class="p">:</span>
    <span class="nb">print</span><span class="p">(</span><span class="n">v</span><span class="p">,</span> <span class="n">res</span><span class="p">[</span><span class="n">v</span><span class="p">])</span>
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<pre>              precision    recall  f1-score   support

         0.0       0.83      0.91      0.87       424
         1.0       0.26      0.15      0.19        91

    accuracy                           0.77       515
   macro avg       0.55      0.53      0.53       515
weighted avg       0.73      0.77      0.75       515

              precision    recall  f1-score   support

         0.0       0.44      0.33      0.38       220
         1.0       0.58      0.68      0.63       295

    accuracy                           0.53       515
   macro avg       0.51      0.51      0.50       515
weighted avg       0.52      0.53      0.52       515

              precision    recall  f1-score   support

         0.0       0.78      0.95      0.86       404
         1.0       0.14      0.03      0.05       111

    accuracy                           0.75       515
   macro avg       0.46      0.49      0.45       515
weighted avg       0.64      0.75      0.68       515

              precision    recall  f1-score   support

         0.0       0.98      0.92      0.95       501
         1.0       0.07      0.21      0.11        14

    accuracy                           0.90       515
   macro avg       0.52      0.57      0.53       515
weighted avg       0.95      0.90      0.93       515

              precision    recall  f1-score   support

         0.0       0.99      0.98      0.99       511
         1.0       0.00      0.00      0.00         4

    accuracy                           0.98       515
   macro avg       0.50      0.49      0.49       515
weighted avg       0.98      0.98      0.98       515

no_matches 77.49786561939726
matches1 53.174962292609365
matches2 75.35957198554313
matches3 90.27106633654913
matches4 97.68811007712227
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<h3 id="Not-only-do-we-have-to-improve-accuracy,-precision-and-recall-is-relatively-low-and-needs-to-be-improved.">Not only do we have to improve accuracy, precision and recall is relatively low and needs to be improved.<a class="anchor-link" href="#Not-only-do-we-have-to-improve-accuracy,-precision-and-recall-is-relatively-low-and-needs-to-be-improved.">&#182;</a></h3>
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<h1 id="5.-Improving-Accuracy-with-a-different-classifier-(KNN)">5. Improving Accuracy with a different classifier (KNN)<a class="anchor-link" href="#5.-Improving-Accuracy-with-a-different-classifier-(KNN)">&#182;</a></h1>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#Trying to see any improvvement in accuracy with a new classifier KNN</span>
<span class="kn">from</span> <span class="nn">sklearn.model_selection</span> <span class="k">import</span> <span class="n">cross_val_predict</span>
<span class="kn">from</span> <span class="nn">sklearn.metrics</span> <span class="k">import</span> <span class="n">confusion_matrix</span>
<span class="kn">from</span> <span class="nn">sklearn.metrics</span> <span class="k">import</span> <span class="n">classification_report</span>
<span class="kn">from</span> <span class="nn">sklearn.model_selection</span> <span class="k">import</span> <span class="n">GridSearchCV</span>
<span class="kn">from</span> <span class="nn">sklearn.neighbors</span> <span class="k">import</span> <span class="n">KNeighborsClassifier</span>
<span class="kn">from</span> <span class="nn">sklearn.preprocessing</span> <span class="k">import</span> <span class="n">MinMaxScaler</span>

<span class="c1">#normalize the data&#39;s features</span>
<span class="n">scaler</span> <span class="o">=</span> <span class="n">MinMaxScaler</span><span class="p">()</span>
<span class="n">scaled_data</span> <span class="o">=</span> <span class="n">scaler</span><span class="o">.</span><span class="n">fit_transform</span><span class="p">(</span><span class="n">data</span><span class="p">)</span>

<span class="c1"># l = [&#39;no_matches&#39;, &#39;matches1&#39;, &#39;matches2&#39;, &#39;matches3&#39;, &#39;matches4&#39;]</span>
<span class="n">d</span> <span class="o">=</span> <span class="p">{</span><span class="s1">&#39;no_matches&#39;</span><span class="p">:</span><span class="o">-</span><span class="mi">5</span><span class="p">,</span><span class="s2">&quot;matches1&quot;</span><span class="p">:</span><span class="o">-</span><span class="mi">4</span><span class="p">,</span><span class="s2">&quot;matches2&quot;</span><span class="p">:</span><span class="o">-</span><span class="mi">3</span><span class="p">,</span><span class="s2">&quot;matches3&quot;</span><span class="p">:</span><span class="o">-</span><span class="mi">2</span><span class="p">,</span><span class="s2">&quot;matches4&quot;</span><span class="p">:</span><span class="o">-</span><span class="mi">1</span><span class="p">}</span>

<span class="k">for</span> <span class="n">k</span><span class="p">,</span><span class="n">v</span> <span class="ow">in</span> <span class="n">d</span><span class="o">.</span><span class="n">items</span><span class="p">():</span>
    <span class="n">scaled_Y</span> <span class="o">=</span> <span class="n">scaled_data</span><span class="p">[:,</span><span class="n">v</span><span class="p">]</span>
    <span class="n">scaled_X</span> <span class="o">=</span> <span class="n">scaled_data</span><span class="p">[:,</span> <span class="p">:</span><span class="o">-</span><span class="mi">5</span><span class="p">]</span>

    <span class="n">neigh</span> <span class="o">=</span> <span class="n">KNeighborsClassifier</span><span class="p">(</span><span class="n">n_neighbors</span><span class="o">=</span><span class="mi">5</span><span class="p">)</span>
    <span class="n">neigh</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">scaled_X</span><span class="p">,</span> <span class="n">scaled_Y</span><span class="p">)</span>

    <span class="n">cvp</span> <span class="o">=</span> <span class="n">cross_val_predict</span><span class="p">(</span><span class="n">neigh</span><span class="p">,</span> <span class="n">scaled_X</span><span class="p">,</span> <span class="n">scaled_Y</span><span class="p">,</span> <span class="n">cv</span><span class="o">=</span><span class="mi">10</span><span class="p">)</span>
    <span class="nb">print</span><span class="p">(</span><span class="n">classification_report</span><span class="p">(</span><span class="n">scaled_Y</span><span class="p">,</span> <span class="n">cvp</span><span class="p">))</span>

    <span class="c1">#k values </span>
    <span class="n">param_grid</span> <span class="o">=</span> <span class="p">{</span><span class="s1">&#39;n_neighbors&#39;</span><span class="p">:</span> <span class="nb">list</span><span class="p">(</span><span class="nb">range</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span><span class="mi">31</span><span class="p">))}</span>

    <span class="c1">#to obtain the best k value, use accuracy</span>
    <span class="n">clf</span> <span class="o">=</span> <span class="n">GridSearchCV</span><span class="p">(</span><span class="n">neigh</span><span class="p">,</span> <span class="n">param_grid</span><span class="p">,</span> <span class="n">cv</span><span class="o">=</span><span class="mi">10</span><span class="p">,</span> <span class="n">scoring</span><span class="o">=</span><span class="s1">&#39;accuracy&#39;</span><span class="p">)</span>
    <span class="n">clf</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">scaled_X</span><span class="p">,</span> <span class="n">scaled_Y</span><span class="p">)</span>

    <span class="nb">print</span><span class="p">(</span><span class="n">k</span><span class="p">)</span>
    <span class="c1">#best k value</span>
    <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;best K value:&quot;</span><span class="p">,</span> <span class="n">clf</span><span class="o">.</span><span class="n">best_params_</span><span class="p">)</span>

    <span class="c1">#accuracy test</span>
    <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Accuracy:&quot;</span><span class="p">,</span> <span class="n">clf</span><span class="o">.</span><span class="n">best_score_</span><span class="o">*</span><span class="mi">100</span><span class="p">)</span>
    <span class="nb">print</span><span class="p">(</span><span class="s2">&quot; &quot;</span><span class="p">)</span>
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<pre>              precision    recall  f1-score   support

         0.0       0.82      0.97      0.89       424
         1.0       0.00      0.00      0.00        91

    accuracy                           0.80       515
   macro avg       0.41      0.49      0.44       515
weighted avg       0.67      0.80      0.73       515

no_matches
best K value: {&#39;n_neighbors&#39;: 14}
Accuracy: 82.52427184466019

              precision    recall  f1-score   support

         0.0       0.48      0.35      0.40       220
         1.0       0.60      0.72      0.65       295

    accuracy                           0.56       515
   macro avg       0.54      0.53      0.53       515
weighted avg       0.55      0.56      0.55       515

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<pre>/opt/anaconda3/lib/python3.7/site-packages/sklearn/model_selection/_search.py:814: DeprecationWarning: The default of the `iid` parameter will change from True to False in version 0.22 and will be removed in 0.24. This will change numeric results when test-set sizes are unequal.
  DeprecationWarning)
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<pre>matches1
best K value: {&#39;n_neighbors&#39;: 17}
Accuracy: 57.0873786407767

              precision    recall  f1-score   support

         0.0       0.78      0.93      0.85       404
         1.0       0.19      0.06      0.10       111

    accuracy                           0.74       515
   macro avg       0.49      0.50      0.47       515
weighted avg       0.66      0.74      0.69       515

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<pre>/opt/anaconda3/lib/python3.7/site-packages/sklearn/model_selection/_search.py:814: DeprecationWarning: The default of the `iid` parameter will change from True to False in version 0.22 and will be removed in 0.24. This will change numeric results when test-set sizes are unequal.
  DeprecationWarning)
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<pre>matches2
best K value: {&#39;n_neighbors&#39;: 18}
Accuracy: 78.44660194174757

              precision    recall  f1-score   support

         0.0       0.97      1.00      0.99       501
         1.0       0.00      0.00      0.00        14

    accuracy                           0.97       515
   macro avg       0.49      0.50      0.49       515
weighted avg       0.95      0.97      0.96       515

matches3
best K value: {&#39;n_neighbors&#39;: 2}
Accuracy: 97.28155339805825

              precision    recall  f1-score   support

         0.0       0.99      1.00      1.00       511
         1.0       0.00      0.00      0.00         4

    accuracy                           0.99       515
   macro avg       0.50      0.50      0.50       515
weighted avg       0.98      0.99      0.99       515

matches4
best K value: {&#39;n_neighbors&#39;: 2}
Accuracy: 99.22330097087378

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<h3 id="KNN-gives-better-accuracy-but-still-has-terrible-precision-and-recall">KNN gives better accuracy but still has terrible precision and recall<a class="anchor-link" href="#KNN-gives-better-accuracy-but-still-has-terrible-precision-and-recall">&#182;</a></h3>
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<h1 id="6.-Manipulating-Data-set-to-improve-accuracy">6. Manipulating Data set to improve accuracy<a class="anchor-link" href="#6.-Manipulating-Data-set-to-improve-accuracy">&#182;</a></h1>
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<h2 id="a.-Only-take-in-account-a-subset-of-columns">a. Only take in account a subset of columns<a class="anchor-link" href="#a.-Only-take-in-account-a-subset-of-columns">&#182;</a></h2>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Targeted column</span>
<span class="n">target_data</span> <span class="o">=</span> <span class="n">data</span><span class="o">.</span><span class="n">iloc</span><span class="p">[:,</span> <span class="p">:</span><span class="mi">9</span><span class="p">]</span>
<span class="n">target_data</span><span class="o">.</span><span class="n">head</span><span class="p">()</span>
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<style scoped>
    .dataframe tbody tr th:only-of-type {
        vertical-align: middle;
    }

    .dataframe tbody tr th {
        vertical-align: top;
    }

    .dataframe thead th {
        text-align: right;
    }
</style>
<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>gender</th>
      <th>age</th>
      <th>race</th>
      <th>imprace</th>
      <th>imprelig</th>
      <th>goal</th>
      <th>date</th>
      <th>go_out</th>
      <th>career_c</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <td>0</td>
      <td>0</td>
      <td>21</td>
      <td>4</td>
      <td>2</td>
      <td>4</td>
      <td>2</td>
      <td>7</td>
      <td>1</td>
      <td>1</td>
    </tr>
    <tr>
      <td>1</td>
      <td>0</td>
      <td>24</td>
      <td>2</td>
      <td>2</td>
      <td>5</td>
      <td>1</td>
      <td>5</td>
      <td>1</td>
      <td>1</td>
    </tr>
    <tr>
      <td>2</td>
      <td>0</td>
      <td>25</td>
      <td>2</td>
      <td>8</td>
      <td>4</td>
      <td>6</td>
      <td>3</td>
      <td>1</td>
      <td>7</td>
    </tr>
    <tr>
      <td>3</td>
      <td>0</td>
      <td>23</td>
      <td>2</td>
      <td>1</td>
      <td>1</td>
      <td>1</td>
      <td>5</td>
      <td>1</td>
      <td>1</td>
    </tr>
    <tr>
      <td>4</td>
      <td>0</td>
      <td>21</td>
      <td>2</td>
      <td>8</td>
      <td>1</td>
      <td>2</td>
      <td>4</td>
      <td>1</td>
      <td>1</td>
    </tr>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#focus on initial characteristics</span>

<span class="c1">#normalize the data&#39;s features</span>
<span class="n">scaler</span> <span class="o">=</span> <span class="n">MinMaxScaler</span><span class="p">()</span>
<span class="n">scaled_data</span> <span class="o">=</span> <span class="n">scaler</span><span class="o">.</span><span class="n">fit_transform</span><span class="p">(</span><span class="n">data</span><span class="p">)</span>

<span class="n">new_data</span> <span class="o">=</span> <span class="n">scaled_data</span><span class="p">[:,</span> <span class="p">:</span><span class="mi">9</span><span class="p">]</span>

<span class="n">d</span> <span class="o">=</span> <span class="p">{</span><span class="s1">&#39;no_matches&#39;</span><span class="p">:</span><span class="o">-</span><span class="mi">5</span><span class="p">,</span><span class="s2">&quot;matches1&quot;</span><span class="p">:</span><span class="o">-</span><span class="mi">4</span><span class="p">,</span><span class="s2">&quot;matches2&quot;</span><span class="p">:</span><span class="o">-</span><span class="mi">3</span><span class="p">,</span><span class="s2">&quot;matches3&quot;</span><span class="p">:</span><span class="o">-</span><span class="mi">2</span><span class="p">,</span><span class="s2">&quot;matches4&quot;</span><span class="p">:</span><span class="o">-</span><span class="mi">1</span><span class="p">}</span>

<span class="k">for</span> <span class="n">k</span><span class="p">,</span><span class="n">v</span> <span class="ow">in</span> <span class="n">d</span><span class="o">.</span><span class="n">items</span><span class="p">():</span>
    <span class="n">scaled_Y</span> <span class="o">=</span> <span class="n">scaled_data</span><span class="p">[:,</span><span class="n">v</span><span class="p">]</span>

    <span class="n">neigh</span> <span class="o">=</span> <span class="n">KNeighborsClassifier</span><span class="p">(</span><span class="n">n_neighbors</span><span class="o">=</span><span class="mi">5</span><span class="p">)</span>
    <span class="n">neigh</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">new_data</span><span class="p">,</span> <span class="n">scaled_Y</span><span class="p">)</span>

    <span class="n">cvp</span> <span class="o">=</span> <span class="n">cross_val_predict</span><span class="p">(</span><span class="n">neigh</span><span class="p">,</span> <span class="n">new_data</span><span class="p">,</span> <span class="n">scaled_Y</span><span class="p">,</span> <span class="n">cv</span><span class="o">=</span><span class="mi">10</span><span class="p">)</span>
    <span class="nb">print</span><span class="p">(</span><span class="n">classification_report</span><span class="p">(</span><span class="n">scaled_Y</span><span class="p">,</span> <span class="n">cvp</span><span class="p">))</span>

    <span class="c1">#k values </span>
    <span class="n">param_grid</span> <span class="o">=</span> <span class="p">{</span><span class="s1">&#39;n_neighbors&#39;</span><span class="p">:</span> <span class="nb">list</span><span class="p">(</span><span class="nb">range</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span><span class="mi">31</span><span class="p">))}</span>

    <span class="c1">#to obtain the best k value, use accuracy</span>
    <span class="n">clf</span> <span class="o">=</span> <span class="n">GridSearchCV</span><span class="p">(</span><span class="n">neigh</span><span class="p">,</span> <span class="n">param_grid</span><span class="p">,</span> <span class="n">cv</span><span class="o">=</span><span class="mi">10</span><span class="p">,</span> <span class="n">scoring</span><span class="o">=</span><span class="s1">&#39;accuracy&#39;</span><span class="p">)</span>
    <span class="n">clf</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">new_data</span><span class="p">,</span> <span class="n">scaled_Y</span><span class="p">)</span>

    <span class="nb">print</span><span class="p">(</span><span class="n">k</span><span class="p">)</span>
    <span class="c1">#best k value</span>
    <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;best K value:&quot;</span><span class="p">,</span> <span class="n">clf</span><span class="o">.</span><span class="n">best_params_</span><span class="p">)</span>

    <span class="c1">#accuracy test</span>
    <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Accuracy:&quot;</span><span class="p">,</span> <span class="n">clf</span><span class="o">.</span><span class="n">best_score_</span><span class="o">*</span><span class="mi">100</span><span class="p">)</span>
    <span class="nb">print</span><span class="p">(</span><span class="s2">&quot; &quot;</span><span class="p">)</span>


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<pre>              precision    recall  f1-score   support

         0.0       0.83      0.97      0.89       424
         1.0       0.31      0.05      0.09        91

    accuracy                           0.81       515
   macro avg       0.57      0.51      0.49       515
weighted avg       0.74      0.81      0.75       515

no_matches
best K value: {&#39;n_neighbors&#39;: 8}
Accuracy: 82.33009708737865

              precision    recall  f1-score   support

         0.0       0.48      0.44      0.46       220
         1.0       0.61      0.64      0.62       295

    accuracy                           0.56       515
   macro avg       0.54      0.54      0.54       515
weighted avg       0.55      0.56      0.55       515

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<pre>/opt/anaconda3/lib/python3.7/site-packages/sklearn/model_selection/_search.py:814: DeprecationWarning: The default of the `iid` parameter will change from True to False in version 0.22 and will be removed in 0.24. This will change numeric results when test-set sizes are unequal.
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<pre>matches1
best K value: {&#39;n_neighbors&#39;: 29}
Accuracy: 58.252427184466015

              precision    recall  f1-score   support

         0.0       0.78      0.90      0.84       404
         1.0       0.18      0.08      0.11       111

    accuracy                           0.72       515
   macro avg       0.48      0.49      0.47       515
weighted avg       0.65      0.72      0.68       515

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<pre>/opt/anaconda3/lib/python3.7/site-packages/sklearn/model_selection/_search.py:814: DeprecationWarning: The default of the `iid` parameter will change from True to False in version 0.22 and will be removed in 0.24. This will change numeric results when test-set sizes are unequal.
  DeprecationWarning)
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<pre>matches2
best K value: {&#39;n_neighbors&#39;: 20}
Accuracy: 78.44660194174757

              precision    recall  f1-score   support

         0.0       0.97      1.00      0.99       501
         1.0       0.00      0.00      0.00        14

    accuracy                           0.97       515
   macro avg       0.49      0.50      0.49       515
weighted avg       0.95      0.97      0.96       515

matches3
best K value: {&#39;n_neighbors&#39;: 4}
Accuracy: 97.28155339805825

              precision    recall  f1-score   support

         0.0       0.99      1.00      1.00       511
         1.0       0.00      0.00      0.00         4

    accuracy                           0.99       515
   macro avg       0.50      0.50      0.50       515
weighted avg       0.98      0.99      0.99       515

matches4
best K value: {&#39;n_neighbors&#39;: 2}
Accuracy: 99.22330097087378

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<h2 id="b.-Remove-last-40-records-since-the-last-two-waves-of-the-speed-dating-event-have-targeted-audience-instead-of-random-like-other-waves">b. Remove last 40 records since the last two waves of the speed dating event have targeted audience instead of random like other waves<a class="anchor-link" href="#b.-Remove-last-40-records-since-the-last-two-waves-of-the-speed-dating-event-have-targeted-audience-instead-of-random-like-other-waves">&#182;</a></h2>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#remove certain rows</span>
<span class="n">new_data</span> <span class="o">=</span> <span class="n">data</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="mi">0</span><span class="p">:</span><span class="mi">475</span><span class="p">,:]</span>

<span class="n">scaler</span> <span class="o">=</span> <span class="n">MinMaxScaler</span><span class="p">()</span>
<span class="n">scaled_data</span> <span class="o">=</span> <span class="n">scaler</span><span class="o">.</span><span class="n">fit_transform</span><span class="p">(</span><span class="n">new_data</span><span class="p">)</span>

<span class="n">d</span> <span class="o">=</span> <span class="p">{</span><span class="s1">&#39;no_matches&#39;</span><span class="p">:</span><span class="o">-</span><span class="mi">5</span><span class="p">,</span><span class="s2">&quot;matches1&quot;</span><span class="p">:</span><span class="o">-</span><span class="mi">4</span><span class="p">,</span><span class="s2">&quot;matches2&quot;</span><span class="p">:</span><span class="o">-</span><span class="mi">3</span><span class="p">,</span><span class="s2">&quot;matches3&quot;</span><span class="p">:</span><span class="o">-</span><span class="mi">2</span><span class="p">,</span><span class="s2">&quot;matches4&quot;</span><span class="p">:</span><span class="o">-</span><span class="mi">1</span><span class="p">}</span>

<span class="k">for</span> <span class="n">k</span><span class="p">,</span><span class="n">v</span> <span class="ow">in</span> <span class="n">d</span><span class="o">.</span><span class="n">items</span><span class="p">():</span>
    <span class="n">scaled_Y</span> <span class="o">=</span> <span class="n">scaled_data</span><span class="p">[:,</span><span class="n">v</span><span class="p">]</span>
    <span class="n">scaled_X</span> <span class="o">=</span> <span class="n">scaled_data</span><span class="p">[:,</span> <span class="p">:</span><span class="o">-</span><span class="mi">5</span><span class="p">]</span>

    <span class="n">neigh</span> <span class="o">=</span> <span class="n">KNeighborsClassifier</span><span class="p">(</span><span class="n">n_neighbors</span><span class="o">=</span><span class="mi">5</span><span class="p">)</span>
    <span class="n">neigh</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">scaled_X</span><span class="p">,</span> <span class="n">scaled_Y</span><span class="p">)</span>

    <span class="n">cvp</span> <span class="o">=</span> <span class="n">cross_val_predict</span><span class="p">(</span><span class="n">neigh</span><span class="p">,</span> <span class="n">scaled_X</span><span class="p">,</span> <span class="n">scaled_Y</span><span class="p">,</span> <span class="n">cv</span><span class="o">=</span><span class="mi">10</span><span class="p">)</span>
    <span class="nb">print</span><span class="p">(</span><span class="n">classification_report</span><span class="p">(</span><span class="n">scaled_Y</span><span class="p">,</span> <span class="n">cvp</span><span class="p">))</span>

    <span class="c1">#k values </span>
    <span class="n">param_grid</span> <span class="o">=</span> <span class="p">{</span><span class="s1">&#39;n_neighbors&#39;</span><span class="p">:</span> <span class="nb">list</span><span class="p">(</span><span class="nb">range</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span><span class="mi">31</span><span class="p">))}</span>

    <span class="c1">#to obtain the best k value, use accuracy</span>
    <span class="n">clf</span> <span class="o">=</span> <span class="n">GridSearchCV</span><span class="p">(</span><span class="n">neigh</span><span class="p">,</span> <span class="n">param_grid</span><span class="p">,</span> <span class="n">cv</span><span class="o">=</span><span class="mi">10</span><span class="p">,</span> <span class="n">scoring</span><span class="o">=</span><span class="s1">&#39;accuracy&#39;</span><span class="p">)</span>
    <span class="n">clf</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">new_data</span><span class="p">,</span> <span class="n">scaled_Y</span><span class="p">)</span>

    <span class="nb">print</span><span class="p">(</span><span class="n">k</span><span class="p">)</span>
    <span class="c1">#best k value</span>
    <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;best K value:&quot;</span><span class="p">,</span> <span class="n">clf</span><span class="o">.</span><span class="n">best_params_</span><span class="p">)</span>

    <span class="c1">#accuracy test</span>
    <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Accuracy:&quot;</span><span class="p">,</span> <span class="n">clf</span><span class="o">.</span><span class="n">best_score_</span><span class="o">*</span><span class="mi">100</span><span class="p">)</span>
    <span class="nb">print</span><span class="p">(</span><span class="s2">&quot; &quot;</span><span class="p">)</span>
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<pre>              precision    recall  f1-score   support

         0.0       0.82      0.97      0.89       392
         1.0       0.00      0.00      0.00        83

    accuracy                           0.80       475
   macro avg       0.41      0.49      0.45       475
weighted avg       0.68      0.80      0.74       475

no_matches
best K value: {&#39;n_neighbors&#39;: 14}
Accuracy: 82.52631578947368

              precision    recall  f1-score   support

         0.0       0.46      0.33      0.39       204
         1.0       0.58      0.70      0.64       271

    accuracy                           0.55       475
   macro avg       0.52      0.52      0.51       475
weighted avg       0.53      0.55      0.53       475

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<pre>/opt/anaconda3/lib/python3.7/site-packages/sklearn/model_selection/_search.py:814: DeprecationWarning: The default of the `iid` parameter will change from True to False in version 0.22 and will be removed in 0.24. This will change numeric results when test-set sizes are unequal.
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<pre>matches1
best K value: {&#39;n_neighbors&#39;: 22}
Accuracy: 64.63157894736841

              precision    recall  f1-score   support

         0.0       0.77      0.91      0.84       371
         1.0       0.13      0.05      0.07       104

    accuracy                           0.72       475
   macro avg       0.45      0.48      0.45       475
weighted avg       0.63      0.72      0.67       475

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<pre>/opt/anaconda3/lib/python3.7/site-packages/sklearn/model_selection/_search.py:814: DeprecationWarning: The default of the `iid` parameter will change from True to False in version 0.22 and will be removed in 0.24. This will change numeric results when test-set sizes are unequal.
  DeprecationWarning)
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<pre>matches2
best K value: {&#39;n_neighbors&#39;: 10}
Accuracy: 78.52631578947368

              precision    recall  f1-score   support

         0.0       0.97      1.00      0.99       462
         1.0       0.00      0.00      0.00        13

    accuracy                           0.97       475
   macro avg       0.49      0.50      0.49       475
weighted avg       0.95      0.97      0.96       475

matches3
best K value: {&#39;n_neighbors&#39;: 2}
Accuracy: 97.26315789473684

              precision    recall  f1-score   support

         0.0       0.99      1.00      1.00       471
         1.0       0.00      0.00      0.00         4

    accuracy                           0.99       475
   macro avg       0.50      0.50      0.50       475
weighted avg       0.98      0.99      0.99       475

matches4
best K value: {&#39;n_neighbors&#39;: 2}
Accuracy: 99.1578947368421

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<h4 id="No-significant-changes">No significant changes<a class="anchor-link" href="#No-significant-changes">&#182;</a></h4>
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<h2 id="c.-Check-for-outliers">c. Check for outliers<a class="anchor-link" href="#c.-Check-for-outliers">&#182;</a></h2>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Two columns with outliers are age and goal</span>
<span class="c1"># Check &quot;Age&quot;</span>
<span class="n">data</span><span class="p">[</span><span class="s1">&#39;age&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">kind</span><span class="o">=</span><span class="s1">&#39;box&#39;</span><span class="p">)</span>
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<pre>&lt;matplotlib.axes._subplots.AxesSubplot at 0x1a1f9c5050&gt;</pre>
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<div class="prompt input_prompt">In&nbsp;[13]:</div>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Check goal</span>
<span class="n">data</span><span class="p">[</span><span class="s1">&#39;goal&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">kind</span><span class="o">=</span><span class="s1">&#39;box&#39;</span><span class="p">)</span>
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<pre>&lt;matplotlib.axes._subplots.AxesSubplot at 0x1a1ffad110&gt;</pre>
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<img src="data:image/png;base64,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<div class="prompt input_prompt">In&nbsp;[14]:</div>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># remove outliers</span>
<span class="kn">from</span> <span class="nn">scipy</span> <span class="k">import</span> <span class="n">stats</span>
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="n">z</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">abs</span><span class="p">(</span><span class="n">stats</span><span class="o">.</span><span class="n">zscore</span><span class="p">(</span><span class="n">data</span><span class="o">.</span><span class="n">iloc</span><span class="p">[:,</span> <span class="p">:</span><span class="o">-</span><span class="mi">5</span><span class="p">]))</span>

<span class="n">out</span> <span class="o">=</span> <span class="nb">list</span><span class="p">(</span><span class="nb">set</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">where</span><span class="p">(</span><span class="n">z</span> <span class="o">&gt;</span> <span class="mi">3</span><span class="p">)[</span><span class="mi">0</span><span class="p">]))</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Outliers index&quot;</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="n">out</span><span class="p">)</span>

<span class="n">no_outlier_data</span> <span class="o">=</span> <span class="n">data</span><span class="o">.</span><span class="n">drop</span><span class="p">(</span><span class="n">out</span><span class="p">,</span> <span class="n">axis</span> <span class="o">=</span> <span class="mi">0</span><span class="p">)</span>
<span class="n">no_outlier_data</span><span class="p">[</span><span class="s1">&#39;age&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">kind</span><span class="o">=</span><span class="s1">&#39;box&#39;</span><span class="p">)</span>
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<pre>Outliers index
[130, 136, 396, 272, 403, 278, 406, 419, 420, 38, 424, 42, 301, 49, 323, 332, 341, 86, 471, 477, 94, 223, 233, 490, 239, 240, 496, 506, 246, 376, 122, 125]
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<pre>&lt;matplotlib.axes._subplots.AxesSubplot at 0x1a20067dd0&gt;</pre>
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gd9ktOAO4BPVNWLY9rXMzq9c9s4Q5dX1fnA+xmd9nlfr05VtbGqhqpqaHBwsPUHkCRNrFXQJxlgNORvq6o7x7RfDvwa8E+rqnqNrao9zfNe4C5g2XSLliS11+aqmwCbgF1V9YUx7WuATwEfqKq/GGfsW5KcfmgbuAh4YiYKlyS10+aMfjlwGbCyuURyZ5KLgS8BpwNbm7YvAyR5W5L7mrFvBbYneQx4GLi3qu6f+Y8hSRpP3zVjq2o7kB6H7uvRdmiq5uJm+1ng3OkUKEmaHu+MlaSOM+glqeMMeknqOINekjrOoJekjjPoJanjDHpJ6jiDXpI6zqCXpI4z6CWp4wx6Seo4g16SOs6gl6SOM+glqeMMeknqOINekjrOoJekjmuzZuzCJNuS7EryZJKPN+1nJdma5Jnm+cxxxl/e9HmmWUxcknQUtTmjPwB8sqoWAxcAVyd5D3AN8K2qehfwrWb/TZKcBVwH/CqwDLhuvD8IkqQjo2/QV9XzVfVos/0SsAuYD3wQuLXpdivwoR7DVwNbq+qFqvopsBVYMxOFS5LamdQcfZJFwHnAQ8Bbq+p5GP1jAPxijyHzgR+N2d/dtPV67bVJhpMMj4yMTKYsSdIEWgd9ktOAO4BPVNWLbYf1aKteHatqY1UNVdXQ4OBg27IkSX20CvokA4yG/G1VdWfT/OMk5zTHzwH29hi6G1g4Zn8BsGfq5UqSJqvNVTcBNgG7quoLYw7dDRy6iuZy4Bs9hj8AXJTkzOZL2IuaNknSUdLmjH45cBmwMsnO5nExcAOwKskzwKpmnyRDSb4CUFUvAJ8FHmken2naJElHyUn9OlTVdnrPtQP8gx79h4Erx+zfAtwy1QIlSdPjnbGS1HEGvSR1nEEvSR1n0EtSxxn0ktRxBr0kdZxBL0kdZ9BLUscZ9JLUcQa9JHWcQS9JHWfQS1LHGfSS1HEGvSR1nEEvSR3X9/fopa4aXTxtCuM+N/kxVT2XSpaOCoNeJyzDVyeKvkGf5Bbg14C9VbWkabsdeHfTZR6wr6qW9hj7HPAScBA4UFVDM1S3JKmlNmf0vw98CfiDQw1V9ZuHtpN8Htg/wfgVVfWTqRYoSZqeNmvGfjvJol7HMjrJ+RvAypktS5I0U6Z71c17gR9X1TPjHC9gS5IdSdZO9EJJ1iYZTjI8MjIyzbIkSYdMN+gvBTZPcHx5VZ0PvB+4Osn7xutYVRuraqiqhgYHB6dZliTpkCkHfZKTgF8Hbh+vT1XtaZ73AncBy6b6fpKkqZnOGf2FwNNVtbvXwSRvSXL6oW3gIuCJabyfJGkK+gZ9ks3AnwLvTrI7yRXNoUs4bNomyduS3NfsvhXYnuQx4GHg3qq6f+ZKlyS1kWPxppEkI8APZ7sOqYezAS8X1rHol6qq5xecx2TQS8eqJMPe+KfjjT9qJkkdZ9BLUscZ9NLkbJztAqTJco5ekjrOM3pJ6jiDXpI6zqCXpI4z6CWp4wx6aYwkX29+VvvJQz+tneSKJH+W5MEkv5fkS037YJI7kjzSPJbPbvVSb151I42R5KyqeiHJqcAjwGrgfwLnM7os5h8Dj1XVR5P8IXBTVW1P8nbggapaPGvFS+NwcXDpzX47yYeb7YXAZcD/qKoXAJL8N+BvNMcvBN4zutAaAH81yelV9dLRLFjqx6CXGkn+PqPh/Xer6i+SPAh8DxjvLH1O0/eVo1OhNDXO0Us/dwbw0ybkfxm4APgrwN9Lcmaz2M4/GtN/C/DRQztJlh7VaqWWDHrp5+4HTkryOPBZ4DvAnwP/HngI+O/AU8D+pv9vA0NJHk/yFLDu6Jcs9eeXsVIfSU6rqpebM/q7gFuq6q7ZrktqyzN6qb/fSbKT0aUwfwB8fZbrkSbFM3pJ6jjP6CWp4wx6Seo4g16SOs6gl6SOM+glqeP+P4+uVZ9TvC8fAAAAAElFTkSuQmCC
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Test with KNN</span>
<span class="c1">#normalize the data&#39;s features</span>
<span class="n">scaler</span> <span class="o">=</span> <span class="n">MinMaxScaler</span><span class="p">()</span>
<span class="n">scaled_data</span> <span class="o">=</span> <span class="n">scaler</span><span class="o">.</span><span class="n">fit_transform</span><span class="p">(</span><span class="n">no_outlier_data</span><span class="p">)</span>

<span class="c1"># l = [&#39;no_matches&#39;, &#39;matches1&#39;, &#39;matches2&#39;, &#39;matches3&#39;, &#39;matches4&#39;]</span>
<span class="n">d</span> <span class="o">=</span> <span class="p">{</span><span class="s1">&#39;no_matches&#39;</span><span class="p">:</span><span class="o">-</span><span class="mi">5</span><span class="p">,</span><span class="s2">&quot;matches1&quot;</span><span class="p">:</span><span class="o">-</span><span class="mi">4</span><span class="p">,</span><span class="s2">&quot;matches2&quot;</span><span class="p">:</span><span class="o">-</span><span class="mi">3</span><span class="p">,</span><span class="s2">&quot;matches3&quot;</span><span class="p">:</span><span class="o">-</span><span class="mi">2</span><span class="p">,</span><span class="s2">&quot;matches4&quot;</span><span class="p">:</span><span class="o">-</span><span class="mi">1</span><span class="p">}</span>

<span class="k">for</span> <span class="n">k</span><span class="p">,</span><span class="n">v</span> <span class="ow">in</span> <span class="n">d</span><span class="o">.</span><span class="n">items</span><span class="p">():</span>
    <span class="n">scaled_Y</span> <span class="o">=</span> <span class="n">scaled_data</span><span class="p">[:,</span><span class="n">v</span><span class="p">]</span>
    <span class="n">scaled_X</span> <span class="o">=</span> <span class="n">scaled_data</span><span class="p">[:,</span> <span class="p">:</span><span class="o">-</span><span class="mi">5</span><span class="p">]</span>

    <span class="n">neigh</span> <span class="o">=</span> <span class="n">KNeighborsClassifier</span><span class="p">(</span><span class="n">n_neighbors</span><span class="o">=</span><span class="mi">5</span><span class="p">)</span>
    <span class="n">neigh</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">scaled_X</span><span class="p">,</span> <span class="n">scaled_Y</span><span class="p">)</span>

    <span class="n">cvp</span> <span class="o">=</span> <span class="n">cross_val_predict</span><span class="p">(</span><span class="n">neigh</span><span class="p">,</span> <span class="n">scaled_X</span><span class="p">,</span> <span class="n">scaled_Y</span><span class="p">,</span> <span class="n">cv</span><span class="o">=</span><span class="mi">10</span><span class="p">)</span>
    <span class="nb">print</span><span class="p">(</span><span class="n">classification_report</span><span class="p">(</span><span class="n">scaled_Y</span><span class="p">,</span> <span class="n">cvp</span><span class="p">))</span>

    <span class="c1">#k values </span>
    <span class="n">param_grid</span> <span class="o">=</span> <span class="p">{</span><span class="s1">&#39;n_neighbors&#39;</span><span class="p">:</span> <span class="nb">list</span><span class="p">(</span><span class="nb">range</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span><span class="mi">31</span><span class="p">))}</span>

    <span class="c1">#to obtain the best k value, use accuracy</span>
    <span class="n">clf</span> <span class="o">=</span> <span class="n">GridSearchCV</span><span class="p">(</span><span class="n">neigh</span><span class="p">,</span> <span class="n">param_grid</span><span class="p">,</span> <span class="n">cv</span><span class="o">=</span><span class="mi">10</span><span class="p">,</span> <span class="n">scoring</span><span class="o">=</span><span class="s1">&#39;accuracy&#39;</span><span class="p">)</span>
    <span class="n">clf</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">scaled_X</span><span class="p">,</span> <span class="n">scaled_Y</span><span class="p">)</span>

    <span class="nb">print</span><span class="p">(</span><span class="n">k</span><span class="p">)</span>
    <span class="c1">#best k value</span>
    <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;best K value:&quot;</span><span class="p">,</span> <span class="n">clf</span><span class="o">.</span><span class="n">best_params_</span><span class="p">)</span>

    <span class="c1">#accuracy test</span>
    <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Accuracy:&quot;</span><span class="p">,</span> <span class="n">clf</span><span class="o">.</span><span class="n">best_score_</span><span class="o">*</span><span class="mi">100</span><span class="p">)</span>
    <span class="nb">print</span><span class="p">(</span><span class="s2">&quot; &quot;</span><span class="p">)</span>
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<pre>              precision    recall  f1-score   support

         0.0       0.82      0.98      0.89       397
         1.0       0.00      0.00      0.00        86

    accuracy                           0.81       483
   macro avg       0.41      0.49      0.45       483
weighted avg       0.67      0.81      0.73       483

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<pre>/opt/anaconda3/lib/python3.7/site-packages/sklearn/model_selection/_search.py:814: DeprecationWarning: The default of the `iid` parameter will change from True to False in version 0.22 and will be removed in 0.24. This will change numeric results when test-set sizes are unequal.
  DeprecationWarning)
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<pre>no_matches
best K value: {&#39;n_neighbors&#39;: 14}
Accuracy: 82.19461697722568

              precision    recall  f1-score   support

         0.0       0.46      0.34      0.39       208
         1.0       0.58      0.70      0.64       275

    accuracy                           0.54       483
   macro avg       0.52      0.52      0.51       483
weighted avg       0.53      0.54      0.53       483

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<pre>/opt/anaconda3/lib/python3.7/site-packages/sklearn/model_selection/_search.py:814: DeprecationWarning: The default of the `iid` parameter will change from True to False in version 0.22 and will be removed in 0.24. This will change numeric results when test-set sizes are unequal.
  DeprecationWarning)
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<pre>matches1
best K value: {&#39;n_neighbors&#39;: 13}
Accuracy: 56.10766045548654

              precision    recall  f1-score   support

         0.0       0.78      0.93      0.85       379
         1.0       0.19      0.06      0.09       104

    accuracy                           0.75       483
   macro avg       0.49      0.50      0.47       483
weighted avg       0.66      0.75      0.69       483

matches2
best K value: {&#39;n_neighbors&#39;: 14}
Accuracy: 78.4679089026915

              precision    recall  f1-score   support

         0.0       0.97      1.00      0.99       469
         1.0       0.00      0.00      0.00        14

    accuracy                           0.97       483
   macro avg       0.49      0.50      0.49       483
weighted avg       0.94      0.97      0.96       483

matches3
best K value: {&#39;n_neighbors&#39;: 4}
Accuracy: 97.10144927536231

              precision    recall  f1-score   support

         0.0       0.99      1.00      1.00       479
         1.0       0.00      0.00      0.00         4

    accuracy                           0.99       483
   macro avg       0.50      0.50      0.50       483
weighted avg       0.98      0.99      0.99       483

matches4
best K value: {&#39;n_neighbors&#39;: 2}
Accuracy: 99.17184265010351

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<h3 id="No-improvement">No improvement<a class="anchor-link" href="#No-improvement">&#182;</a></h3>
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<h2 id="d.-Change-bin-range-(3-bins-instead-of-5)">d. Change bin range (3 bins instead of 5)<a class="anchor-link" href="#d.-Change-bin-range-(3-bins-instead-of-5)">&#182;</a></h2>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#read the CSV</span>
<span class="n">test_data</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">read_csv</span><span class="p">(</span><span class="s2">&quot;speed_dating_data.csv&quot;</span><span class="p">)</span>
<span class="n">missing_values</span> <span class="o">=</span> <span class="p">[</span><span class="s1">&#39;&#39;</span><span class="p">,</span> <span class="s1">&#39; &#39;</span><span class="p">]</span>


<span class="c1">#create new columns</span>

<span class="n">test_data</span><span class="p">[</span><span class="s2">&quot;no_matches&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="n">test_data</span><span class="p">[</span><span class="s2">&quot;match&quot;</span><span class="p">]</span>

<span class="n">test_data</span><span class="p">[</span><span class="s2">&quot;matches1&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="n">test_data</span><span class="p">[</span><span class="s2">&quot;match&quot;</span><span class="p">]</span>

<span class="n">test_data</span><span class="p">[</span><span class="s2">&quot;matches2&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="n">test_data</span><span class="p">[</span><span class="s2">&quot;match&quot;</span><span class="p">]</span>


<span class="c1">#hot encode based on match rates</span>
<span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">test_data</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">0</span><span class="p">]):</span>
    <span class="c1">#bin them into three separate columns</span>
    <span class="c1"># bin 0 to .1 match %</span>
    <span class="k">if</span> <span class="p">(</span><span class="n">test_data</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">i</span><span class="p">,</span> <span class="s2">&quot;match&quot;</span><span class="p">])</span> <span class="o">&lt;=</span> <span class="mf">0.1</span><span class="p">:</span>
        <span class="n">test_data</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">i</span><span class="p">,</span><span class="s2">&quot;no_matches&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="mi">1</span>
    <span class="k">else</span><span class="p">:</span>
        <span class="n">test_data</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">i</span><span class="p">,</span><span class="s2">&quot;no_matches&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="mi">0</span>

<span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">test_data</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">0</span><span class="p">]):</span>
    <span class="c1">#bin 0.01 to 0.5 match %</span>
    <span class="k">if</span> <span class="p">(</span><span class="n">test_data</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">i</span><span class="p">,</span> <span class="s2">&quot;match&quot;</span><span class="p">])</span> <span class="o">&gt;</span> <span class="mf">0.1</span> <span class="ow">and</span> <span class="p">(</span><span class="n">test_data</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">i</span><span class="p">,</span> <span class="s2">&quot;match&quot;</span><span class="p">])</span> <span class="o">&lt;</span> <span class="mf">0.5</span><span class="p">:</span>
        <span class="n">test_data</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">i</span><span class="p">,</span><span class="s2">&quot;matches1&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="mi">1</span>
    <span class="k">else</span><span class="p">:</span>
        <span class="n">test_data</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">i</span><span class="p">,</span><span class="s2">&quot;matches1&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="mi">0</span>


<span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">test_data</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">0</span><span class="p">]):</span>
    <span class="c1">#bin .5 to 1 match %</span>
    <span class="k">if</span> <span class="p">(</span><span class="n">test_data</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">i</span><span class="p">,</span> <span class="s2">&quot;match&quot;</span><span class="p">])</span> <span class="o">&gt;=</span> <span class="mf">0.5</span><span class="p">:</span>
        <span class="n">test_data</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">i</span><span class="p">,</span><span class="s2">&quot;matches2&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="mi">1</span>
    <span class="k">else</span><span class="p">:</span>
        <span class="n">test_data</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">i</span><span class="p">,</span><span class="s2">&quot;matches2&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="mi">0</span>


<span class="n">test_data</span> <span class="o">=</span> <span class="n">test_data</span><span class="o">.</span><span class="n">drop</span><span class="p">([</span><span class="s1">&#39;iid&#39;</span><span class="p">,</span> <span class="s1">&#39;round&#39;</span><span class="p">,</span> <span class="s1">&#39;wave&#39;</span><span class="p">,</span> <span class="s1">&#39;match&#39;</span><span class="p">,</span> <span class="s1">&#39;match_es&#39;</span><span class="p">,],</span>  <span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
<span class="n">test_data</span><span class="o">.</span><span class="n">head</span><span class="p">(</span><span class="mi">10</span><span class="p">)</span>
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<style scoped>
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        text-align: right;
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</style>
<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>gender</th>
      <th>age</th>
      <th>race</th>
      <th>imprace</th>
      <th>imprelig</th>
      <th>goal</th>
      <th>date</th>
      <th>go_out</th>
      <th>career_c</th>
      <th>sports</th>
      <th>...</th>
      <th>tv</th>
      <th>theater</th>
      <th>movies</th>
      <th>concerts</th>
      <th>music</th>
      <th>shopping</th>
      <th>yoga</th>
      <th>no_matches</th>
      <th>matches1</th>
      <th>matches2</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <td>0</td>
      <td>0</td>
      <td>21</td>
      <td>4</td>
      <td>2</td>
      <td>4</td>
      <td>2</td>
      <td>7</td>
      <td>1</td>
      <td>1</td>
      <td>9</td>
      <td>...</td>
      <td>9</td>
      <td>1</td>
      <td>10</td>
      <td>10</td>
      <td>9</td>
      <td>8</td>
      <td>1</td>
      <td>0.0</td>
      <td>1.0</td>
      <td>0.0</td>
    </tr>
    <tr>
      <td>1</td>
      <td>0</td>
      <td>24</td>
      <td>2</td>
      <td>2</td>
      <td>5</td>
      <td>1</td>
      <td>5</td>
      <td>1</td>
      <td>1</td>
      <td>3</td>
      <td>...</td>
      <td>1</td>
      <td>9</td>
      <td>8</td>
      <td>7</td>
      <td>8</td>
      <td>3</td>
      <td>1</td>
      <td>0.0</td>
      <td>1.0</td>
      <td>0.0</td>
    </tr>
    <tr>
      <td>2</td>
      <td>0</td>
      <td>25</td>
      <td>2</td>
      <td>8</td>
      <td>4</td>
      <td>6</td>
      <td>3</td>
      <td>1</td>
      <td>7</td>
      <td>3</td>
      <td>...</td>
      <td>8</td>
      <td>7</td>
      <td>7</td>
      <td>7</td>
      <td>5</td>
      <td>8</td>
      <td>7</td>
      <td>1.0</td>
      <td>0.0</td>
      <td>0.0</td>
    </tr>
    <tr>
      <td>3</td>
      <td>0</td>
      <td>23</td>
      <td>2</td>
      <td>1</td>
      <td>1</td>
      <td>1</td>
      <td>5</td>
      <td>1</td>
      <td>1</td>
      <td>1</td>
      <td>...</td>
      <td>7</td>
      <td>9</td>
      <td>7</td>
      <td>8</td>
      <td>7</td>
      <td>1</td>
      <td>8</td>
      <td>0.0</td>
      <td>1.0</td>
      <td>0.0</td>
    </tr>
    <tr>
      <td>4</td>
      <td>0</td>
      <td>21</td>
      <td>2</td>
      <td>8</td>
      <td>1</td>
      <td>2</td>
      <td>4</td>
      <td>1</td>
      <td>1</td>
      <td>7</td>
      <td>...</td>
      <td>8</td>
      <td>6</td>
      <td>6</td>
      <td>3</td>
      <td>7</td>
      <td>8</td>
      <td>3</td>
      <td>0.0</td>
      <td>1.0</td>
      <td>0.0</td>
    </tr>
    <tr>
      <td>5</td>
      <td>0</td>
      <td>23</td>
      <td>4</td>
      <td>1</td>
      <td>1</td>
      <td>1</td>
      <td>3</td>
      <td>1</td>
      <td>1</td>
      <td>10</td>
      <td>...</td>
      <td>2</td>
      <td>5</td>
      <td>6</td>
      <td>6</td>
      <td>4</td>
      <td>1</td>
      <td>1</td>
      <td>0.0</td>
      <td>1.0</td>
      <td>0.0</td>
    </tr>
    <tr>
      <td>6</td>
      <td>0</td>
      <td>22</td>
      <td>4</td>
      <td>2</td>
      <td>4</td>
      <td>1</td>
      <td>5</td>
      <td>1</td>
      <td>1</td>
      <td>5</td>
      <td>...</td>
      <td>8</td>
      <td>10</td>
      <td>10</td>
      <td>10</td>
      <td>10</td>
      <td>10</td>
      <td>10</td>
      <td>0.0</td>
      <td>1.0</td>
      <td>0.0</td>
    </tr>
    <tr>
      <td>7</td>
      <td>0</td>
      <td>25</td>
      <td>2</td>
      <td>1</td>
      <td>1</td>
      <td>1</td>
      <td>5</td>
      <td>1</td>
      <td>6</td>
      <td>2</td>
      <td>...</td>
      <td>10</td>
      <td>9</td>
      <td>9</td>
      <td>6</td>
      <td>6</td>
      <td>8</td>
      <td>6</td>
      <td>0.0</td>
      <td>0.0</td>
      <td>1.0</td>
    </tr>
    <tr>
      <td>8</td>
      <td>0</td>
      <td>26</td>
      <td>6</td>
      <td>1</td>
      <td>1</td>
      <td>1</td>
      <td>4</td>
      <td>1</td>
      <td>9</td>
      <td>4</td>
      <td>...</td>
      <td>8</td>
      <td>10</td>
      <td>10</td>
      <td>9</td>
      <td>9</td>
      <td>8</td>
      <td>3</td>
      <td>0.0</td>
      <td>0.0</td>
      <td>1.0</td>
    </tr>
    <tr>
      <td>9</td>
      <td>0</td>
      <td>26</td>
      <td>2</td>
      <td>4</td>
      <td>4</td>
      <td>2</td>
      <td>6</td>
      <td>1</td>
      <td>9</td>
      <td>9</td>
      <td>...</td>
      <td>5</td>
      <td>6</td>
      <td>7</td>
      <td>7</td>
      <td>8</td>
      <td>7</td>
      <td>7</td>
      <td>0.0</td>
      <td>1.0</td>
      <td>0.0</td>
    </tr>
  </tbody>
</table>
<p>10 rows × 29 columns</p>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Gaussian</span>
<span class="kn">from</span> <span class="nn">sklearn.naive_bayes</span> <span class="k">import</span> <span class="n">GaussianNB</span>
<span class="kn">from</span> <span class="nn">sklearn.model_selection</span> <span class="k">import</span> <span class="n">cross_val_score</span>
<span class="kn">from</span> <span class="nn">sklearn.model_selection</span> <span class="k">import</span> <span class="n">cross_val_predict</span>
<span class="kn">from</span> <span class="nn">sklearn.metrics</span> <span class="k">import</span> <span class="n">confusion_matrix</span>
<span class="kn">from</span> <span class="nn">sklearn.metrics</span> <span class="k">import</span> <span class="n">classification_report</span>

<span class="n">gnb</span> <span class="o">=</span> <span class="n">GaussianNB</span><span class="p">()</span>

<span class="c1">#split class labels from predictor labels</span>
<span class="n">l</span> <span class="o">=</span> <span class="p">[</span><span class="s1">&#39;no_matches&#39;</span><span class="p">,</span> <span class="s1">&#39;matches1&#39;</span><span class="p">,</span> <span class="s1">&#39;matches2&#39;</span><span class="p">]</span>
<span class="n">res</span> <span class="o">=</span> <span class="p">{}</span>

<span class="k">for</span> <span class="n">d</span> <span class="ow">in</span> <span class="n">l</span><span class="p">:</span>
    <span class="n">test_data_Y</span> <span class="o">=</span> <span class="n">test_data</span><span class="p">[</span><span class="n">d</span><span class="p">]</span>
    <span class="n">test_data_X</span> <span class="o">=</span> <span class="n">test_data</span><span class="o">.</span><span class="n">drop</span><span class="p">([</span><span class="s1">&#39;no_matches&#39;</span><span class="p">,</span> <span class="s1">&#39;matches1&#39;</span><span class="p">,</span> <span class="s1">&#39;matches2&#39;</span><span class="p">],</span>  <span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>

    <span class="c1"># data_Y.head(10)</span>
    <span class="c1"># data_X.head(10)</span>

    <span class="n">cvs</span> <span class="o">=</span> <span class="n">cross_val_score</span><span class="p">(</span><span class="n">gnb</span><span class="p">,</span> <span class="n">test_data_X</span><span class="p">,</span> <span class="n">test_data_Y</span><span class="p">,</span> <span class="n">cv</span><span class="o">=</span><span class="mi">10</span><span class="p">)</span>
    <span class="n">a</span> <span class="o">=</span> <span class="n">cvs</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span><span class="o">*</span><span class="mi">100</span>

    <span class="n">cvp</span> <span class="o">=</span> <span class="n">cross_val_predict</span><span class="p">(</span><span class="n">gnb</span><span class="p">,</span> <span class="n">test_data_X</span><span class="p">,</span> <span class="n">test_data_Y</span><span class="p">,</span> <span class="n">cv</span><span class="o">=</span><span class="mi">10</span><span class="p">)</span>
    <span class="nb">print</span><span class="p">(</span><span class="n">classification_report</span><span class="p">(</span><span class="n">test_data_Y</span><span class="p">,</span> <span class="n">cvp</span><span class="p">))</span>

    <span class="n">res</span><span class="p">[</span><span class="n">d</span><span class="p">]</span> <span class="o">=</span> <span class="n">a</span>

<span class="c1">#print accuracy of every bin</span>
<span class="k">for</span> <span class="n">v</span> <span class="ow">in</span> <span class="n">res</span><span class="p">:</span>
    <span class="nb">print</span><span class="p">(</span><span class="n">v</span><span class="p">,</span> <span class="n">res</span><span class="p">[</span><span class="n">v</span><span class="p">])</span>
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<pre>              precision    recall  f1-score   support

         0.0       0.63      0.70      0.66       314
         1.0       0.43      0.35      0.38       201

    accuracy                           0.56       515
   macro avg       0.53      0.52      0.52       515
weighted avg       0.55      0.56      0.55       515

              precision    recall  f1-score   support

         0.0       0.42      0.31      0.36       219
         1.0       0.57      0.68      0.62       296

    accuracy                           0.52       515
   macro avg       0.50      0.50      0.49       515
weighted avg       0.51      0.52      0.51       515

              precision    recall  f1-score   support

         0.0       0.97      0.95      0.96       497
         1.0       0.11      0.17      0.13        18

    accuracy                           0.92       515
   macro avg       0.54      0.56      0.55       515
weighted avg       0.94      0.92      0.93       515

no_matches 56.27586157830331
matches1 52.413574660633486
matches2 92.41960784313726
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># KNN</span>
<span class="c1">#normalize the data&#39;s features</span>
<span class="n">scaler</span> <span class="o">=</span> <span class="n">MinMaxScaler</span><span class="p">()</span>
<span class="n">scaled_data</span> <span class="o">=</span> <span class="n">scaler</span><span class="o">.</span><span class="n">fit_transform</span><span class="p">(</span><span class="n">test_data</span><span class="p">)</span>


<span class="n">d</span> <span class="o">=</span> <span class="p">{</span><span class="s1">&#39;no_matches&#39;</span><span class="p">:</span><span class="o">-</span><span class="mi">3</span><span class="p">,</span><span class="s2">&quot;matches1&quot;</span><span class="p">:</span><span class="o">-</span><span class="mi">2</span><span class="p">,</span><span class="s2">&quot;matches2&quot;</span><span class="p">:</span><span class="o">-</span><span class="mi">1</span><span class="p">,}</span>

<span class="k">for</span> <span class="n">k</span><span class="p">,</span><span class="n">v</span> <span class="ow">in</span> <span class="n">d</span><span class="o">.</span><span class="n">items</span><span class="p">():</span>
    <span class="n">scaled_Y</span> <span class="o">=</span> <span class="n">scaled_data</span><span class="p">[:,</span><span class="n">v</span><span class="p">]</span>
    <span class="n">scaled_X</span> <span class="o">=</span> <span class="n">scaled_data</span><span class="p">[:,</span> <span class="p">:</span><span class="o">-</span><span class="mi">3</span><span class="p">]</span>

    <span class="n">neigh</span> <span class="o">=</span> <span class="n">KNeighborsClassifier</span><span class="p">(</span><span class="n">n_neighbors</span><span class="o">=</span><span class="mi">5</span><span class="p">)</span>
    <span class="n">neigh</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">scaled_X</span><span class="p">,</span> <span class="n">scaled_Y</span><span class="p">)</span>

    <span class="n">cvp</span> <span class="o">=</span> <span class="n">cross_val_predict</span><span class="p">(</span><span class="n">neigh</span><span class="p">,</span> <span class="n">scaled_X</span><span class="p">,</span> <span class="n">scaled_Y</span><span class="p">,</span> <span class="n">cv</span><span class="o">=</span><span class="mi">10</span><span class="p">)</span>
    <span class="nb">print</span><span class="p">(</span><span class="n">classification_report</span><span class="p">(</span><span class="n">scaled_Y</span><span class="p">,</span> <span class="n">cvp</span><span class="p">))</span>

    <span class="c1">#k values </span>
    <span class="n">param_grid</span> <span class="o">=</span> <span class="p">{</span><span class="s1">&#39;n_neighbors&#39;</span><span class="p">:</span> <span class="nb">list</span><span class="p">(</span><span class="nb">range</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span><span class="mi">31</span><span class="p">))}</span>

    <span class="c1">#to obtain the best k value, use accuracy</span>
    <span class="n">clf</span> <span class="o">=</span> <span class="n">GridSearchCV</span><span class="p">(</span><span class="n">neigh</span><span class="p">,</span> <span class="n">param_grid</span><span class="p">,</span> <span class="n">cv</span><span class="o">=</span><span class="mi">10</span><span class="p">,</span> <span class="n">scoring</span><span class="o">=</span><span class="s1">&#39;accuracy&#39;</span><span class="p">)</span>
    <span class="n">clf</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">scaled_X</span><span class="p">,</span> <span class="n">scaled_Y</span><span class="p">)</span>

    <span class="nb">print</span><span class="p">(</span><span class="n">k</span><span class="p">)</span>
    <span class="c1">#best k value</span>
    <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;best K value:&quot;</span><span class="p">,</span> <span class="n">clf</span><span class="o">.</span><span class="n">best_params_</span><span class="p">)</span>

    <span class="c1">#accuracy test</span>
    <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Accuracy:&quot;</span><span class="p">,</span> <span class="n">clf</span><span class="o">.</span><span class="n">best_score_</span><span class="o">*</span><span class="mi">100</span><span class="p">)</span>
    <span class="nb">print</span><span class="p">(</span><span class="s2">&quot; &quot;</span><span class="p">)</span>
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<pre>              precision    recall  f1-score   support

         0.0       0.62      0.72      0.66       314
         1.0       0.40      0.29      0.34       201

    accuracy                           0.56       515
   macro avg       0.51      0.51      0.50       515
weighted avg       0.53      0.56      0.54       515

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<pre>/opt/anaconda3/lib/python3.7/site-packages/sklearn/model_selection/_search.py:814: DeprecationWarning: The default of the `iid` parameter will change from True to False in version 0.22 and will be removed in 0.24. This will change numeric results when test-set sizes are unequal.
  DeprecationWarning)
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<pre>no_matches
best K value: {&#39;n_neighbors&#39;: 10}
Accuracy: 61.55339805825243

              precision    recall  f1-score   support

         0.0       0.44      0.33      0.38       219
         1.0       0.58      0.69      0.63       296

    accuracy                           0.54       515
   macro avg       0.51      0.51      0.50       515
weighted avg       0.52      0.54      0.52       515

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<pre>/opt/anaconda3/lib/python3.7/site-packages/sklearn/model_selection/_search.py:814: DeprecationWarning: The default of the `iid` parameter will change from True to False in version 0.22 and will be removed in 0.24. This will change numeric results when test-set sizes are unequal.
  DeprecationWarning)
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<pre>matches1
best K value: {&#39;n_neighbors&#39;: 9}
Accuracy: 55.72815533980583

              precision    recall  f1-score   support

         0.0       0.97      1.00      0.98       497
         1.0       0.00      0.00      0.00        18

    accuracy                           0.97       515
   macro avg       0.48      0.50      0.49       515
weighted avg       0.93      0.97      0.95       515

matches2
best K value: {&#39;n_neighbors&#39;: 4}
Accuracy: 96.50485436893203

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<h3 id="Improvement-on-precision-and-recall-but-last-bin-still-suffer.-Therefore,-we-need-to-add-more-data-for-last-bin-by-duplicating-records-with-result-in-last-bin.-Overally,-the-precision-and-recall-of-the-classifiers-would-heavily-benefit-if-we-have-more-data-in-general.">Improvement on precision and recall but last bin still suffer. Therefore, we need to add more data for last bin by duplicating records with result in last bin. Overally, the precision and recall of the classifiers would heavily benefit if we have more data in general.<a class="anchor-link" href="#Improvement-on-precision-and-recall-but-last-bin-still-suffer.-Therefore,-we-need-to-add-more-data-for-last-bin-by-duplicating-records-with-result-in-last-bin.-Overally,-the-precision-and-recall-of-the-classifiers-would-heavily-benefit-if-we-have-more-data-in-general.">&#182;</a></h3>
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<h1 id="7.-Voting">7. Voting<a class="anchor-link" href="#7.-Voting">&#182;</a></h1>
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<h3 id="Choose-KNN-method-for-the-whole-dataset,-save-prediction-in-an-array,-use-k-value-from-best-k-value-above">Choose KNN method for the whole dataset, save prediction in an array, use k value from best k value above<a class="anchor-link" href="#Choose-KNN-method-for-the-whole-dataset,-save-prediction-in-an-array,-use-k-value-from-best-k-value-above">&#182;</a></h3>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">from</span> <span class="nn">sklearn.metrics</span> <span class="k">import</span> <span class="n">accuracy_score</span>

<span class="n">prediction</span> <span class="o">=</span> <span class="p">[]</span>

<span class="n">scaler</span> <span class="o">=</span> <span class="n">MinMaxScaler</span><span class="p">()</span>
<span class="n">scaled_data</span> <span class="o">=</span> <span class="n">scaler</span><span class="o">.</span><span class="n">fit_transform</span><span class="p">(</span><span class="n">test_data</span><span class="p">)</span>


<span class="n">d</span> <span class="o">=</span> <span class="p">{</span><span class="s1">&#39;no_matches&#39;</span><span class="p">:</span><span class="o">-</span><span class="mi">3</span><span class="p">,</span><span class="s2">&quot;matches1&quot;</span><span class="p">:</span><span class="o">-</span><span class="mi">2</span><span class="p">,</span><span class="s2">&quot;matches2&quot;</span><span class="p">:</span><span class="o">-</span><span class="mi">1</span><span class="p">,}</span>
<span class="n">k_val</span> <span class="o">=</span> <span class="p">{</span><span class="s1">&#39;no_matches&#39;</span><span class="p">:</span><span class="mi">10</span><span class="p">,</span><span class="s2">&quot;matches1&quot;</span><span class="p">:</span><span class="mi">29</span><span class="p">,</span><span class="s2">&quot;matches2&quot;</span><span class="p">:</span><span class="mi">2</span><span class="p">,}</span> <span class="c1"># Obtained from the run aboved</span>

<span class="c1"># KNN with the whole dataset</span>
<span class="k">for</span> <span class="n">k</span><span class="p">,</span><span class="n">v</span> <span class="ow">in</span> <span class="n">d</span><span class="o">.</span><span class="n">items</span><span class="p">():</span>
    <span class="n">scaled_Y</span> <span class="o">=</span> <span class="n">scaled_data</span><span class="p">[:,</span><span class="n">v</span><span class="p">]</span>
    <span class="n">scaled_X</span> <span class="o">=</span> <span class="n">scaled_data</span><span class="p">[:,</span> <span class="p">:</span><span class="o">-</span><span class="mi">3</span><span class="p">]</span>

    <span class="n">neigh</span> <span class="o">=</span> <span class="n">KNeighborsClassifier</span><span class="p">(</span><span class="n">n_neighbors</span><span class="o">=</span><span class="n">k_val</span><span class="p">[</span><span class="n">k</span><span class="p">])</span>
    <span class="n">neigh</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">scaled_X</span><span class="p">,</span> <span class="n">scaled_Y</span><span class="p">)</span>

    <span class="n">cvp</span> <span class="o">=</span> <span class="n">cross_val_predict</span><span class="p">(</span><span class="n">neigh</span><span class="p">,</span> <span class="n">scaled_X</span><span class="p">,</span> <span class="n">scaled_Y</span><span class="p">)</span>
    <span class="nb">print</span><span class="p">(</span><span class="n">classification_report</span><span class="p">(</span><span class="n">scaled_Y</span><span class="p">,</span> <span class="n">cvp</span><span class="p">))</span>
    <span class="n">prediction</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">cvp</span><span class="p">)</span>

<span class="nb">print</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">prediction</span><span class="p">))</span>
<span class="nb">print</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">prediction</span><span class="p">[</span><span class="mi">0</span><span class="p">]))</span>
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<pre>              precision    recall  f1-score   support

         0.0       0.62      0.87      0.72       314
         1.0       0.45      0.16      0.24       201

    accuracy                           0.60       515
   macro avg       0.54      0.52      0.48       515
weighted avg       0.55      0.60      0.54       515

              precision    recall  f1-score   support

         0.0       0.43      0.12      0.19       219
         1.0       0.57      0.88      0.70       296

    accuracy                           0.56       515
   macro avg       0.50      0.50      0.44       515
weighted avg       0.51      0.56      0.48       515

              precision    recall  f1-score   support

         0.0       0.97      1.00      0.98       497
         1.0       0.00      0.00      0.00        18

    accuracy                           0.97       515
   macro avg       0.48      0.50      0.49       515
weighted avg       0.93      0.97      0.95       515

3
515
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<h3 id="Begin-voting-based-on-the-result-of-each-bin.-For-example,-for-bin-&quot;no_match&quot;,-if-&quot;no_match&quot;-predicts-Yes-or-other-bin-predicts-No,-bin-&quot;no_match&quot;-gets-one-vote.-If-&quot;no_match&quot;-predicts-No-or-other-bin-predicts-Yes,-bin-&quot;no_match&quot;-doesn't-get-a-vote.">Begin voting based on the result of each bin. For example, for bin "no_match", if "no_match" predicts Yes or other bin predicts No, bin "no_match" gets one vote. If "no_match" predicts No or other bin predicts Yes, bin "no_match" doesn't get a vote.<a class="anchor-link" href="#Begin-voting-based-on-the-result-of-each-bin.-For-example,-for-bin-&quot;no_match&quot;,-if-&quot;no_match&quot;-predicts-Yes-or-other-bin-predicts-No,-bin-&quot;no_match&quot;-gets-one-vote.-If-&quot;no_match&quot;-predicts-No-or-other-bin-predicts-Yes,-bin-&quot;no_match&quot;-doesn't-get-a-vote.">&#182;</a></h3>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">voting_result</span> <span class="o">=</span> <span class="p">[]</span>

<span class="c1"># no_match voting</span>
<span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">prediction</span><span class="p">[</span><span class="mi">0</span><span class="p">])):</span>
    <span class="n">vote</span> <span class="o">=</span> <span class="mi">0</span>
    <span class="k">for</span> <span class="n">j</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">prediction</span><span class="p">)):</span>
        <span class="k">if</span> <span class="n">j</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span>
            <span class="k">if</span> <span class="n">prediction</span><span class="p">[</span><span class="n">j</span><span class="p">][</span><span class="n">i</span><span class="p">]</span> <span class="o">==</span> <span class="mi">1</span><span class="p">:</span>
                <span class="n">vote</span> <span class="o">+=</span> <span class="mi">1</span>
        <span class="k">else</span><span class="p">:</span>
            <span class="k">if</span> <span class="n">prediction</span><span class="p">[</span><span class="n">j</span><span class="p">][</span><span class="n">i</span><span class="p">]</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span>
                <span class="n">vote</span> <span class="o">+=</span> <span class="mi">1</span>
    <span class="n">voting_result</span><span class="o">.</span><span class="n">append</span><span class="p">([</span><span class="n">vote</span><span class="p">])</span>

<span class="c1"># matches1 voting</span>
<span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">prediction</span><span class="p">[</span><span class="mi">0</span><span class="p">])):</span>
    <span class="n">vote</span> <span class="o">=</span> <span class="mi">0</span>
    <span class="k">for</span> <span class="n">j</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">prediction</span><span class="p">)):</span>
        <span class="k">if</span> <span class="n">j</span> <span class="o">==</span> <span class="mi">1</span><span class="p">:</span>
            <span class="k">if</span> <span class="n">prediction</span><span class="p">[</span><span class="n">j</span><span class="p">][</span><span class="n">i</span><span class="p">]</span> <span class="o">==</span> <span class="mi">1</span><span class="p">:</span>
                <span class="n">vote</span> <span class="o">+=</span> <span class="mi">1</span>
        <span class="k">else</span><span class="p">:</span>
            <span class="k">if</span> <span class="n">prediction</span><span class="p">[</span><span class="n">j</span><span class="p">][</span><span class="n">i</span><span class="p">]</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span>
                <span class="n">vote</span> <span class="o">+=</span> <span class="mi">1</span>
    <span class="n">voting_result</span><span class="p">[</span><span class="n">i</span><span class="p">]</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">vote</span><span class="p">)</span>


<span class="c1"># matches2 voting</span>
<span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">prediction</span><span class="p">[</span><span class="mi">0</span><span class="p">])):</span>
    <span class="n">vote</span> <span class="o">=</span> <span class="mi">0</span>
    <span class="k">for</span> <span class="n">j</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">prediction</span><span class="p">)):</span>
        <span class="k">if</span> <span class="n">j</span> <span class="o">==</span> <span class="mi">2</span><span class="p">:</span>
            <span class="k">if</span> <span class="n">prediction</span><span class="p">[</span><span class="n">j</span><span class="p">][</span><span class="n">i</span><span class="p">]</span> <span class="o">==</span> <span class="mi">1</span><span class="p">:</span>
                <span class="n">vote</span> <span class="o">+=</span> <span class="mi">1</span>
        <span class="k">else</span><span class="p">:</span>
            <span class="k">if</span> <span class="n">prediction</span><span class="p">[</span><span class="n">j</span><span class="p">][</span><span class="n">i</span><span class="p">]</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span>
                <span class="n">vote</span> <span class="o">+=</span> <span class="mi">1</span>
    <span class="n">voting_result</span><span class="p">[</span><span class="n">i</span><span class="p">]</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">vote</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Voting Results of first 10:&quot;</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="n">voting_result</span><span class="p">[</span><span class="mi">0</span><span class="p">:</span><span class="mi">10</span><span class="p">])</span>
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<pre>Voting Results of first 10:
[[1, 3, 1], [1, 3, 1], [1, 3, 1], [1, 3, 1], [1, 3, 1], [1, 3, 1], [1, 3, 1], [1, 3, 1], [1, 3, 1], [1, 3, 1]]
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Compile y_true</span>
<span class="n">y_true</span> <span class="o">=</span> <span class="p">[]</span>

<span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">ori_data</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">0</span><span class="p">]):</span>
    <span class="k">if</span> <span class="p">(</span><span class="n">ori_data</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">i</span><span class="p">,</span> <span class="s2">&quot;match&quot;</span><span class="p">])</span> <span class="o">&lt;=</span> <span class="mf">0.1</span><span class="p">:</span>
        <span class="n">y_true</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span>
    <span class="k">elif</span> <span class="p">(</span><span class="n">ori_data</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">i</span><span class="p">,</span> <span class="s2">&quot;match&quot;</span><span class="p">])</span> <span class="o">&gt;</span> <span class="mf">0.1</span> <span class="ow">and</span> <span class="p">(</span><span class="n">ori_data</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">i</span><span class="p">,</span> <span class="s2">&quot;match&quot;</span><span class="p">])</span> <span class="o">&lt;</span> <span class="mf">0.5</span><span class="p">:</span>
        <span class="n">y_true</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mi">1</span><span class="p">)</span>
    <span class="k">else</span><span class="p">:</span>
        <span class="n">y_true</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mi">2</span><span class="p">)</span>

<span class="c1"># Compile y_predict</span>
<span class="kn">from</span> <span class="nn">sklearn.metrics</span> <span class="k">import</span> <span class="n">accuracy_score</span>
<span class="n">y_predict</span> <span class="o">=</span> <span class="p">[]</span>
<span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">voting_result</span><span class="p">)):</span>
    <span class="k">if</span> <span class="n">voting_result</span><span class="p">[</span><span class="n">i</span><span class="p">]</span><span class="o">.</span><span class="n">count</span><span class="p">(</span><span class="nb">max</span><span class="p">(</span><span class="n">voting_result</span><span class="p">[</span><span class="n">i</span><span class="p">]))</span> <span class="o">==</span> <span class="mi">1</span><span class="p">:</span>
        <span class="n">y_predict</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">voting_result</span><span class="p">[</span><span class="n">i</span><span class="p">]</span><span class="o">.</span><span class="n">index</span><span class="p">(</span><span class="nb">max</span><span class="p">(</span><span class="n">voting_result</span><span class="p">[</span><span class="n">i</span><span class="p">])))</span>
    <span class="k">else</span><span class="p">:</span>
        <span class="n">y_predict</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="s2">&quot;N/A&quot;</span><span class="p">)</span>

<span class="n">count</span> <span class="o">=</span> <span class="mi">0</span>
<span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">y_true</span><span class="p">)):</span>
    <span class="k">if</span> <span class="n">y_true</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="o">==</span> <span class="n">y_predict</span><span class="p">[</span><span class="n">i</span><span class="p">]:</span>
        <span class="n">count</span> <span class="o">+=</span> <span class="mi">1</span>

<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Final accuracy of binning:&quot;</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="n">count</span><span class="o">/</span><span class="nb">len</span><span class="p">(</span><span class="n">y_true</span><span class="p">)</span><span class="o">*</span><span class="mi">100</span><span class="p">)</span>
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<pre>Final accuracy of binning:
48.54368932038835
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<h1 id="8.-Duplicate-bin-3-records-to-improve-f-score-of-model">8. Duplicate bin 3 records to improve f-score of model<a class="anchor-link" href="#8.-Duplicate-bin-3-records-to-improve-f-score-of-model">&#182;</a></h1>
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<h3 id="Create-a-second-csv-file-with-duplicated-records-called-duplicated_vals---Speed-Dating-Data.csv.-Repeat-the-same-steps-as-before">Create a second csv file with duplicated records called duplicated_vals - Speed Dating Data.csv. Repeat the same steps as before<a class="anchor-link" href="#Create-a-second-csv-file-with-duplicated-records-called-duplicated_vals---Speed-Dating-Data.csv.-Repeat-the-same-steps-as-before">&#182;</a></h3>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">dup_data</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">read_csv</span><span class="p">(</span><span class="s2">&quot;duplicated_vals - Speed Dating Data.csv&quot;</span><span class="p">)</span>
<span class="n">missing_values</span> <span class="o">=</span> <span class="p">[</span><span class="s1">&#39;&#39;</span><span class="p">,</span> <span class="s1">&#39; &#39;</span><span class="p">]</span>


<span class="n">test_data</span><span class="p">[</span><span class="s2">&quot;no_matches&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="n">dup_data</span><span class="p">[</span><span class="s2">&quot;match&quot;</span><span class="p">]</span>

<span class="n">dup_data</span><span class="p">[</span><span class="s2">&quot;matches1&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="n">dup_data</span><span class="p">[</span><span class="s2">&quot;match&quot;</span><span class="p">]</span>

<span class="n">dup_data</span><span class="p">[</span><span class="s2">&quot;matches2&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="n">dup_data</span><span class="p">[</span><span class="s2">&quot;match&quot;</span><span class="p">]</span>


<span class="c1">#hot encode based on match rates</span>
<span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">dup_data</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">0</span><span class="p">]):</span>
    <span class="c1">#bin them into three separate columns</span>
    <span class="c1">#no match bin</span>
    <span class="k">if</span> <span class="p">(</span><span class="n">dup_data</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">i</span><span class="p">,</span> <span class="s2">&quot;match&quot;</span><span class="p">])</span> <span class="o">&lt;=</span> <span class="mf">0.1</span><span class="p">:</span>
        <span class="n">dup_data</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">i</span><span class="p">,</span><span class="s2">&quot;no_matches&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="mi">1</span>
    <span class="k">else</span><span class="p">:</span>
        <span class="n">dup_data</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">i</span><span class="p">,</span><span class="s2">&quot;no_matches&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="mi">0</span>

<span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">dup_data</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">0</span><span class="p">]):</span>
    <span class="c1">#bin 0.01=0.25</span>
    <span class="k">if</span> <span class="p">(</span><span class="n">dup_data</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">i</span><span class="p">,</span> <span class="s2">&quot;match&quot;</span><span class="p">])</span> <span class="o">&gt;</span> <span class="mf">0.1</span> <span class="ow">and</span> <span class="p">(</span><span class="n">dup_data</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">i</span><span class="p">,</span> <span class="s2">&quot;match&quot;</span><span class="p">])</span> <span class="o">&lt;</span> <span class="mf">0.5</span><span class="p">:</span>
        <span class="n">dup_data</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">i</span><span class="p">,</span><span class="s2">&quot;matches1&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="mi">1</span>
    <span class="k">else</span><span class="p">:</span>
        <span class="n">dup_data</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">i</span><span class="p">,</span><span class="s2">&quot;matches1&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="mi">0</span>


<span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">dup_data</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">0</span><span class="p">]):</span>
    <span class="k">if</span> <span class="p">(</span><span class="n">dup_data</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">i</span><span class="p">,</span> <span class="s2">&quot;match&quot;</span><span class="p">])</span> <span class="o">&gt;=</span> <span class="mf">0.5</span><span class="p">:</span>
        <span class="n">dup_data</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">i</span><span class="p">,</span><span class="s2">&quot;matches2&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="mi">1</span>
    <span class="k">else</span><span class="p">:</span>
        <span class="n">dup_data</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">i</span><span class="p">,</span><span class="s2">&quot;matches2&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="mi">0</span>

<span class="n">ori_dup_data</span> <span class="o">=</span> <span class="n">dup_data</span>
<span class="n">dup_data</span> <span class="o">=</span> <span class="n">dup_data</span><span class="o">.</span><span class="n">drop</span><span class="p">([</span><span class="s1">&#39;iid&#39;</span><span class="p">,</span> <span class="s1">&#39;round&#39;</span><span class="p">,</span> <span class="s1">&#39;wave&#39;</span><span class="p">,</span> <span class="s1">&#39;match&#39;</span><span class="p">,</span> <span class="s1">&#39;match_es&#39;</span><span class="p">,],</span>  <span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
<span class="n">dup_data</span><span class="o">.</span><span class="n">head</span><span class="p">(</span><span class="mi">10</span><span class="p">)</span>
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<style scoped>
    .dataframe tbody tr th:only-of-type {
        vertical-align: middle;
    }

    .dataframe tbody tr th {
        vertical-align: top;
    }

    .dataframe thead th {
        text-align: right;
    }
</style>
<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>gender</th>
      <th>age</th>
      <th>race</th>
      <th>imprace</th>
      <th>imprelig</th>
      <th>goal</th>
      <th>date</th>
      <th>go_out</th>
      <th>career_c</th>
      <th>sports</th>
      <th>...</th>
      <th>tv</th>
      <th>theater</th>
      <th>movies</th>
      <th>concerts</th>
      <th>music</th>
      <th>shopping</th>
      <th>yoga</th>
      <th>matches1</th>
      <th>matches2</th>
      <th>no_matches</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <td>0</td>
      <td>0</td>
      <td>21</td>
      <td>4</td>
      <td>2</td>
      <td>4</td>
      <td>2</td>
      <td>7</td>
      <td>1</td>
      <td>1</td>
      <td>9</td>
      <td>...</td>
      <td>9</td>
      <td>1</td>
      <td>10</td>
      <td>10</td>
      <td>9</td>
      <td>8</td>
      <td>1</td>
      <td>1.0</td>
      <td>0.0</td>
      <td>0.0</td>
    </tr>
    <tr>
      <td>1</td>
      <td>0</td>
      <td>24</td>
      <td>2</td>
      <td>2</td>
      <td>5</td>
      <td>1</td>
      <td>5</td>
      <td>1</td>
      <td>1</td>
      <td>3</td>
      <td>...</td>
      <td>1</td>
      <td>9</td>
      <td>8</td>
      <td>7</td>
      <td>8</td>
      <td>3</td>
      <td>1</td>
      <td>1.0</td>
      <td>0.0</td>
      <td>0.0</td>
    </tr>
    <tr>
      <td>2</td>
      <td>0</td>
      <td>25</td>
      <td>2</td>
      <td>8</td>
      <td>4</td>
      <td>6</td>
      <td>3</td>
      <td>1</td>
      <td>7</td>
      <td>3</td>
      <td>...</td>
      <td>8</td>
      <td>7</td>
      <td>7</td>
      <td>7</td>
      <td>5</td>
      <td>8</td>
      <td>7</td>
      <td>0.0</td>
      <td>0.0</td>
      <td>1.0</td>
    </tr>
    <tr>
      <td>3</td>
      <td>0</td>
      <td>23</td>
      <td>2</td>
      <td>1</td>
      <td>1</td>
      <td>1</td>
      <td>5</td>
      <td>1</td>
      <td>1</td>
      <td>1</td>
      <td>...</td>
      <td>7</td>
      <td>9</td>
      <td>7</td>
      <td>8</td>
      <td>7</td>
      <td>1</td>
      <td>8</td>
      <td>1.0</td>
      <td>0.0</td>
      <td>0.0</td>
    </tr>
    <tr>
      <td>4</td>
      <td>0</td>
      <td>21</td>
      <td>2</td>
      <td>8</td>
      <td>1</td>
      <td>2</td>
      <td>4</td>
      <td>1</td>
      <td>1</td>
      <td>7</td>
      <td>...</td>
      <td>8</td>
      <td>6</td>
      <td>6</td>
      <td>3</td>
      <td>7</td>
      <td>8</td>
      <td>3</td>
      <td>1.0</td>
      <td>0.0</td>
      <td>0.0</td>
    </tr>
    <tr>
      <td>5</td>
      <td>0</td>
      <td>23</td>
      <td>4</td>
      <td>1</td>
      <td>1</td>
      <td>1</td>
      <td>3</td>
      <td>1</td>
      <td>1</td>
      <td>10</td>
      <td>...</td>
      <td>2</td>
      <td>5</td>
      <td>6</td>
      <td>6</td>
      <td>4</td>
      <td>1</td>
      <td>1</td>
      <td>1.0</td>
      <td>0.0</td>
      <td>0.0</td>
    </tr>
    <tr>
      <td>6</td>
      <td>0</td>
      <td>22</td>
      <td>4</td>
      <td>2</td>
      <td>4</td>
      <td>1</td>
      <td>5</td>
      <td>1</td>
      <td>1</td>
      <td>5</td>
      <td>...</td>
      <td>8</td>
      <td>10</td>
      <td>10</td>
      <td>10</td>
      <td>10</td>
      <td>10</td>
      <td>10</td>
      <td>1.0</td>
      <td>0.0</td>
      <td>0.0</td>
    </tr>
    <tr>
      <td>7</td>
      <td>0</td>
      <td>25</td>
      <td>2</td>
      <td>1</td>
      <td>1</td>
      <td>1</td>
      <td>5</td>
      <td>1</td>
      <td>6</td>
      <td>2</td>
      <td>...</td>
      <td>10</td>
      <td>9</td>
      <td>9</td>
      <td>6</td>
      <td>6</td>
      <td>8</td>
      <td>6</td>
      <td>0.0</td>
      <td>1.0</td>
      <td>0.0</td>
    </tr>
    <tr>
      <td>8</td>
      <td>0</td>
      <td>26</td>
      <td>6</td>
      <td>1</td>
      <td>1</td>
      <td>1</td>
      <td>4</td>
      <td>1</td>
      <td>9</td>
      <td>4</td>
      <td>...</td>
      <td>8</td>
      <td>10</td>
      <td>10</td>
      <td>9</td>
      <td>9</td>
      <td>8</td>
      <td>3</td>
      <td>0.0</td>
      <td>1.0</td>
      <td>0.0</td>
    </tr>
    <tr>
      <td>9</td>
      <td>0</td>
      <td>26</td>
      <td>2</td>
      <td>4</td>
      <td>4</td>
      <td>2</td>
      <td>6</td>
      <td>1</td>
      <td>9</td>
      <td>9</td>
      <td>...</td>
      <td>5</td>
      <td>6</td>
      <td>7</td>
      <td>7</td>
      <td>8</td>
      <td>7</td>
      <td>7</td>
      <td>1.0</td>
      <td>0.0</td>
      <td>0.0</td>
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<p>10 rows × 29 columns</p>
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<h2 id="a.-KNN-with-duplicated-dataset">a. KNN with duplicated dataset<a class="anchor-link" href="#a.-KNN-with-duplicated-dataset">&#182;</a></h2>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">from</span> <span class="nn">sklearn.naive_bayes</span> <span class="k">import</span> <span class="n">GaussianNB</span>
<span class="kn">from</span> <span class="nn">sklearn.model_selection</span> <span class="k">import</span> <span class="n">cross_val_score</span>
<span class="kn">from</span> <span class="nn">sklearn.model_selection</span> <span class="k">import</span> <span class="n">cross_val_predict</span>
<span class="kn">from</span> <span class="nn">sklearn.metrics</span> <span class="k">import</span> <span class="n">confusion_matrix</span>
<span class="kn">from</span> <span class="nn">sklearn.metrics</span> <span class="k">import</span> <span class="n">classification_report</span>

<span class="n">gnb</span> <span class="o">=</span> <span class="n">GaussianNB</span><span class="p">()</span>

<span class="c1">#split class labels from predictor labels</span>
<span class="n">l</span> <span class="o">=</span> <span class="p">[</span><span class="s1">&#39;no_matches&#39;</span><span class="p">,</span> <span class="s1">&#39;matches1&#39;</span><span class="p">,</span> <span class="s1">&#39;matches2&#39;</span><span class="p">]</span>
<span class="n">res</span> <span class="o">=</span> <span class="p">{}</span>

<span class="k">for</span> <span class="n">d</span> <span class="ow">in</span> <span class="n">l</span><span class="p">:</span>
    <span class="n">dup_data_Y</span> <span class="o">=</span> <span class="n">dup_data</span><span class="p">[</span><span class="n">d</span><span class="p">]</span>
    <span class="n">dup_data_X</span> <span class="o">=</span> <span class="n">dup_data</span><span class="o">.</span><span class="n">drop</span><span class="p">([</span><span class="s1">&#39;no_matches&#39;</span><span class="p">,</span> <span class="s1">&#39;matches1&#39;</span><span class="p">,</span> <span class="s1">&#39;matches2&#39;</span><span class="p">],</span>  <span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>

    <span class="c1"># data_Y.head(10)</span>
    <span class="c1"># data_X.head(10)</span>

    <span class="n">cvs</span> <span class="o">=</span> <span class="n">cross_val_score</span><span class="p">(</span><span class="n">gnb</span><span class="p">,</span> <span class="n">dup_data_X</span><span class="p">,</span> <span class="n">dup_data_Y</span><span class="p">,</span> <span class="n">cv</span><span class="o">=</span><span class="mi">10</span><span class="p">)</span>
    <span class="n">a</span> <span class="o">=</span> <span class="n">cvs</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span><span class="o">*</span><span class="mi">100</span>

    <span class="n">cvp</span> <span class="o">=</span> <span class="n">cross_val_predict</span><span class="p">(</span><span class="n">gnb</span><span class="p">,</span> <span class="n">dup_data_X</span><span class="p">,</span> <span class="n">dup_data_Y</span><span class="p">,</span> <span class="n">cv</span><span class="o">=</span><span class="mi">10</span><span class="p">)</span>
    <span class="nb">print</span><span class="p">(</span><span class="n">classification_report</span><span class="p">(</span><span class="n">dup_data_Y</span><span class="p">,</span> <span class="n">cvp</span><span class="p">))</span>

    <span class="n">res</span><span class="p">[</span><span class="n">d</span><span class="p">]</span> <span class="o">=</span> <span class="n">a</span>

<span class="c1">#print accuracy of every bin</span>
<span class="k">for</span> <span class="n">v</span> <span class="ow">in</span> <span class="n">res</span><span class="p">:</span>
    <span class="nb">print</span><span class="p">(</span><span class="n">v</span><span class="p">,</span> <span class="n">res</span><span class="p">[</span><span class="n">v</span><span class="p">])</span>
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<pre>              precision    recall  f1-score   support

         0.0       0.69      0.73      0.71       362
         1.0       0.46      0.41      0.43       201

    accuracy                           0.61       563
   macro avg       0.57      0.57      0.57       563
weighted avg       0.61      0.61      0.61       563

              precision    recall  f1-score   support

         0.0       0.49      0.37      0.42       267
         1.0       0.53      0.65      0.59       296

    accuracy                           0.52       563
   macro avg       0.51      0.51      0.50       563
weighted avg       0.51      0.52      0.51       563

              precision    recall  f1-score   support

         0.0       0.95      0.90      0.92       497
         1.0       0.45      0.62      0.52        66

    accuracy                           0.87       563
   macro avg       0.70      0.76      0.72       563
weighted avg       0.89      0.87      0.88       563

no_matches 61.43613343704089
matches1 51.724139895192536
matches2 86.64792663476874
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">scaler</span> <span class="o">=</span> <span class="n">MinMaxScaler</span><span class="p">()</span>
<span class="n">scaled_data</span> <span class="o">=</span> <span class="n">scaler</span><span class="o">.</span><span class="n">fit_transform</span><span class="p">(</span><span class="n">dup_data</span><span class="p">)</span>


<span class="n">d</span> <span class="o">=</span> <span class="p">{</span><span class="s1">&#39;no_matches&#39;</span><span class="p">:</span><span class="o">-</span><span class="mi">3</span><span class="p">,</span><span class="s2">&quot;matches1&quot;</span><span class="p">:</span><span class="o">-</span><span class="mi">2</span><span class="p">,</span><span class="s2">&quot;matches2&quot;</span><span class="p">:</span><span class="o">-</span><span class="mi">1</span><span class="p">,}</span>

<span class="k">for</span> <span class="n">k</span><span class="p">,</span><span class="n">v</span> <span class="ow">in</span> <span class="n">d</span><span class="o">.</span><span class="n">items</span><span class="p">():</span>
    <span class="n">scaled_Y</span> <span class="o">=</span> <span class="n">scaled_data</span><span class="p">[:,</span><span class="n">v</span><span class="p">]</span>
    <span class="n">scaled_X</span> <span class="o">=</span> <span class="n">scaled_data</span><span class="p">[:,</span> <span class="p">:</span><span class="o">-</span><span class="mi">3</span><span class="p">]</span>

    <span class="n">neigh</span> <span class="o">=</span> <span class="n">KNeighborsClassifier</span><span class="p">(</span><span class="n">n_neighbors</span><span class="o">=</span><span class="mi">5</span><span class="p">)</span>
    <span class="n">neigh</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">scaled_X</span><span class="p">,</span> <span class="n">scaled_Y</span><span class="p">)</span>

    <span class="n">cvp</span> <span class="o">=</span> <span class="n">cross_val_predict</span><span class="p">(</span><span class="n">neigh</span><span class="p">,</span> <span class="n">scaled_X</span><span class="p">,</span> <span class="n">scaled_Y</span><span class="p">,</span> <span class="n">cv</span><span class="o">=</span><span class="mi">10</span><span class="p">)</span>
    <span class="nb">print</span><span class="p">(</span><span class="n">classification_report</span><span class="p">(</span><span class="n">scaled_Y</span><span class="p">,</span> <span class="n">cvp</span><span class="p">))</span>

    <span class="c1">#k values </span>
    <span class="n">param_grid</span> <span class="o">=</span> <span class="p">{</span><span class="s1">&#39;n_neighbors&#39;</span><span class="p">:</span> <span class="nb">list</span><span class="p">(</span><span class="nb">range</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span><span class="mi">31</span><span class="p">))}</span>

    <span class="c1">#to obtain the best k value, use accuracy</span>
    <span class="n">clf</span> <span class="o">=</span> <span class="n">GridSearchCV</span><span class="p">(</span><span class="n">neigh</span><span class="p">,</span> <span class="n">param_grid</span><span class="p">,</span> <span class="n">cv</span><span class="o">=</span><span class="mi">10</span><span class="p">,</span> <span class="n">scoring</span><span class="o">=</span><span class="s1">&#39;accuracy&#39;</span><span class="p">)</span>
    <span class="n">clf</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">scaled_X</span><span class="p">,</span> <span class="n">scaled_Y</span><span class="p">)</span>

    <span class="nb">print</span><span class="p">(</span><span class="n">k</span><span class="p">)</span>
    <span class="c1">#best k value</span>
    <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;best K value:&quot;</span><span class="p">,</span> <span class="n">clf</span><span class="o">.</span><span class="n">best_params_</span><span class="p">)</span>

    <span class="c1">#accuracy test</span>
    <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Accuracy:&quot;</span><span class="p">,</span> <span class="n">clf</span><span class="o">.</span><span class="n">best_score_</span><span class="o">*</span><span class="mi">100</span><span class="p">)</span>
    <span class="nb">print</span><span class="p">(</span><span class="s2">&quot; &quot;</span><span class="p">)</span>
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<pre>              precision    recall  f1-score   support

         0.0       0.54      0.49      0.51       267
         1.0       0.58      0.63      0.60       296

    accuracy                           0.56       563
   macro avg       0.56      0.56      0.56       563
weighted avg       0.56      0.56      0.56       563

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<pre>/opt/anaconda3/lib/python3.7/site-packages/sklearn/model_selection/_search.py:814: DeprecationWarning: The default of the `iid` parameter will change from True to False in version 0.22 and will be removed in 0.24. This will change numeric results when test-set sizes are unequal.
  DeprecationWarning)
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<pre>no_matches
best K value: {&#39;n_neighbors&#39;: 1}
Accuracy: 59.32504440497336

              precision    recall  f1-score   support

         0.0       1.00      0.93      0.96       497
         1.0       0.66      0.97      0.79        66

    accuracy                           0.94       563
   macro avg       0.83      0.95      0.87       563
weighted avg       0.96      0.94      0.94       563

matches1
best K value: {&#39;n_neighbors&#39;: 2}
Accuracy: 97.86856127886323

              precision    recall  f1-score   support

         0.0       0.66      0.78      0.72       362
         1.0       0.42      0.29      0.34       201

    accuracy                           0.61       563
   macro avg       0.54      0.54      0.53       563
weighted avg       0.58      0.61      0.58       563

matches2
best K value: {&#39;n_neighbors&#39;: 10}
Accuracy: 64.83126110124334

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<pre>/opt/anaconda3/lib/python3.7/site-packages/sklearn/model_selection/_search.py:814: DeprecationWarning: The default of the `iid` parameter will change from True to False in version 0.22 and will be removed in 0.24. This will change numeric results when test-set sizes are unequal.
  DeprecationWarning)
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<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">from</span> <span class="nn">sklearn.metrics</span> <span class="k">import</span> <span class="n">accuracy_score</span>

<span class="n">prediction</span> <span class="o">=</span> <span class="p">[]</span>

<span class="n">scaler</span> <span class="o">=</span> <span class="n">MinMaxScaler</span><span class="p">()</span>
<span class="n">scaled_data</span> <span class="o">=</span> <span class="n">scaler</span><span class="o">.</span><span class="n">fit_transform</span><span class="p">(</span><span class="n">dup_data</span><span class="p">)</span>


<span class="n">d</span> <span class="o">=</span> <span class="p">{</span><span class="s1">&#39;no_matches&#39;</span><span class="p">:</span><span class="o">-</span><span class="mi">3</span><span class="p">,</span><span class="s2">&quot;matches1&quot;</span><span class="p">:</span><span class="o">-</span><span class="mi">2</span><span class="p">,</span><span class="s2">&quot;matches2&quot;</span><span class="p">:</span><span class="o">-</span><span class="mi">1</span><span class="p">,}</span>
<span class="n">k_val</span> <span class="o">=</span> <span class="p">{</span><span class="s1">&#39;no_matches&#39;</span><span class="p">:</span><span class="mi">10</span><span class="p">,</span><span class="s2">&quot;matches1&quot;</span><span class="p">:</span><span class="mi">29</span><span class="p">,</span><span class="s2">&quot;matches2&quot;</span><span class="p">:</span><span class="mi">2</span><span class="p">,}</span> <span class="c1"># Obtained from the run aboved</span>

<span class="c1"># KNN with the whole dataset</span>
<span class="k">for</span> <span class="n">k</span><span class="p">,</span><span class="n">v</span> <span class="ow">in</span> <span class="n">d</span><span class="o">.</span><span class="n">items</span><span class="p">():</span>
    <span class="n">scaled_Y</span> <span class="o">=</span> <span class="n">scaled_data</span><span class="p">[:,</span><span class="n">v</span><span class="p">]</span>
    <span class="n">scaled_X</span> <span class="o">=</span> <span class="n">scaled_data</span><span class="p">[:,</span> <span class="p">:</span><span class="o">-</span><span class="mi">3</span><span class="p">]</span>

    <span class="n">neigh</span> <span class="o">=</span> <span class="n">KNeighborsClassifier</span><span class="p">(</span><span class="n">n_neighbors</span><span class="o">=</span><span class="n">k_val</span><span class="p">[</span><span class="n">k</span><span class="p">])</span>
    <span class="n">neigh</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">scaled_X</span><span class="p">,</span> <span class="n">scaled_Y</span><span class="p">)</span>

    <span class="n">cvp</span> <span class="o">=</span> <span class="n">cross_val_predict</span><span class="p">(</span><span class="n">neigh</span><span class="p">,</span> <span class="n">scaled_X</span><span class="p">,</span> <span class="n">scaled_Y</span><span class="p">)</span>
    <span class="nb">print</span><span class="p">(</span><span class="n">classification_report</span><span class="p">(</span><span class="n">scaled_Y</span><span class="p">,</span> <span class="n">cvp</span><span class="p">))</span>
    <span class="n">prediction</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">cvp</span><span class="p">)</span>

<span class="nb">print</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">prediction</span><span class="p">))</span>
<span class="nb">print</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">prediction</span><span class="p">[</span><span class="mi">0</span><span class="p">]))</span>
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<pre>              precision    recall  f1-score   support

         0.0       0.48      0.48      0.48       267
         1.0       0.53      0.54      0.54       296

    accuracy                           0.51       563
   macro avg       0.51      0.51      0.51       563
weighted avg       0.51      0.51      0.51       563

              precision    recall  f1-score   support

         0.0       0.88      1.00      0.94       497
         1.0       0.00      0.00      0.00        66

    accuracy                           0.88       563
   macro avg       0.44      0.50      0.47       563
weighted avg       0.78      0.88      0.83       563

              precision    recall  f1-score   support

         0.0       0.65      0.88      0.75       362
         1.0       0.42      0.16      0.24       201

    accuracy                           0.62       563
   macro avg       0.54      0.52      0.49       563
weighted avg       0.57      0.62      0.57       563

3
563
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">voting_result</span> <span class="o">=</span> <span class="p">[]</span>

<span class="c1"># no_match voting</span>
<span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">prediction</span><span class="p">[</span><span class="mi">0</span><span class="p">])):</span>
    <span class="n">vote</span> <span class="o">=</span> <span class="mi">0</span>
    <span class="k">for</span> <span class="n">j</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">prediction</span><span class="p">)):</span>
        <span class="k">if</span> <span class="n">j</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span>
            <span class="k">if</span> <span class="n">prediction</span><span class="p">[</span><span class="n">j</span><span class="p">][</span><span class="n">i</span><span class="p">]</span> <span class="o">==</span> <span class="mi">1</span><span class="p">:</span>
                <span class="n">vote</span> <span class="o">+=</span> <span class="mi">1</span>
        <span class="k">else</span><span class="p">:</span>
            <span class="k">if</span> <span class="n">prediction</span><span class="p">[</span><span class="n">j</span><span class="p">][</span><span class="n">i</span><span class="p">]</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span>
                <span class="n">vote</span> <span class="o">+=</span> <span class="mi">1</span>
    <span class="n">voting_result</span><span class="o">.</span><span class="n">append</span><span class="p">([</span><span class="n">vote</span><span class="p">])</span>

<span class="c1"># matches1 voting</span>
<span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">prediction</span><span class="p">[</span><span class="mi">0</span><span class="p">])):</span>
    <span class="n">vote</span> <span class="o">=</span> <span class="mi">0</span>
    <span class="k">for</span> <span class="n">j</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">prediction</span><span class="p">)):</span>
        <span class="k">if</span> <span class="n">j</span> <span class="o">==</span> <span class="mi">1</span><span class="p">:</span>
            <span class="k">if</span> <span class="n">prediction</span><span class="p">[</span><span class="n">j</span><span class="p">][</span><span class="n">i</span><span class="p">]</span> <span class="o">==</span> <span class="mi">1</span><span class="p">:</span>
                <span class="n">vote</span> <span class="o">+=</span> <span class="mi">1</span>
        <span class="k">else</span><span class="p">:</span>
            <span class="k">if</span> <span class="n">prediction</span><span class="p">[</span><span class="n">j</span><span class="p">][</span><span class="n">i</span><span class="p">]</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span>
                <span class="n">vote</span> <span class="o">+=</span> <span class="mi">1</span>
    <span class="n">voting_result</span><span class="p">[</span><span class="n">i</span><span class="p">]</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">vote</span><span class="p">)</span>


<span class="c1"># matches2 voting</span>
<span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">prediction</span><span class="p">[</span><span class="mi">0</span><span class="p">])):</span>
    <span class="n">vote</span> <span class="o">=</span> <span class="mi">0</span>
    <span class="k">for</span> <span class="n">j</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">prediction</span><span class="p">)):</span>
        <span class="k">if</span> <span class="n">j</span> <span class="o">==</span> <span class="mi">2</span><span class="p">:</span>
            <span class="k">if</span> <span class="n">prediction</span><span class="p">[</span><span class="n">j</span><span class="p">][</span><span class="n">i</span><span class="p">]</span> <span class="o">==</span> <span class="mi">1</span><span class="p">:</span>
                <span class="n">vote</span> <span class="o">+=</span> <span class="mi">1</span>
        <span class="k">else</span><span class="p">:</span>
            <span class="k">if</span> <span class="n">prediction</span><span class="p">[</span><span class="n">j</span><span class="p">][</span><span class="n">i</span><span class="p">]</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span>
                <span class="n">vote</span> <span class="o">+=</span> <span class="mi">1</span>
    <span class="n">voting_result</span><span class="p">[</span><span class="n">i</span><span class="p">]</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">vote</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Voting Results of first 10:&quot;</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="n">voting_result</span><span class="p">[</span><span class="mi">0</span><span class="p">:</span><span class="mi">10</span><span class="p">])</span>
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<pre>Voting Results of first 10:
[[3, 1, 1], [3, 1, 1], [3, 1, 1], [3, 1, 1], [3, 1, 1], [2, 2, 2], [1, 1, 3], [2, 2, 2], [2, 2, 2], [3, 1, 1]]
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Compile y_true</span>
<span class="n">y_true</span> <span class="o">=</span> <span class="p">[]</span>

<span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">ori_dup_data</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">0</span><span class="p">]):</span>
    <span class="k">if</span> <span class="p">(</span><span class="n">ori_dup_data</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">i</span><span class="p">,</span> <span class="s2">&quot;match&quot;</span><span class="p">])</span> <span class="o">&lt;=</span> <span class="mf">0.1</span><span class="p">:</span>
        <span class="n">y_true</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span>
    <span class="k">elif</span> <span class="p">(</span><span class="n">ori_dup_data</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">i</span><span class="p">,</span> <span class="s2">&quot;match&quot;</span><span class="p">])</span> <span class="o">&gt;</span> <span class="mf">0.1</span> <span class="ow">and</span> <span class="p">(</span><span class="n">ori_dup_data</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">i</span><span class="p">,</span> <span class="s2">&quot;match&quot;</span><span class="p">])</span> <span class="o">&lt;</span> <span class="mf">0.5</span><span class="p">:</span>
        <span class="n">y_true</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mi">1</span><span class="p">)</span>
    <span class="k">else</span><span class="p">:</span>
        <span class="n">y_true</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mi">2</span><span class="p">)</span>

<span class="c1"># Compile y_predict</span>
<span class="kn">from</span> <span class="nn">sklearn.metrics</span> <span class="k">import</span> <span class="n">accuracy_score</span>
<span class="n">y_predict</span> <span class="o">=</span> <span class="p">[]</span>
<span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">voting_result</span><span class="p">)):</span>
    <span class="k">if</span> <span class="n">voting_result</span><span class="p">[</span><span class="n">i</span><span class="p">]</span><span class="o">.</span><span class="n">count</span><span class="p">(</span><span class="nb">max</span><span class="p">(</span><span class="n">voting_result</span><span class="p">[</span><span class="n">i</span><span class="p">]))</span> <span class="o">==</span> <span class="mi">1</span><span class="p">:</span>
        <span class="n">y_predict</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">voting_result</span><span class="p">[</span><span class="n">i</span><span class="p">]</span><span class="o">.</span><span class="n">index</span><span class="p">(</span><span class="nb">max</span><span class="p">(</span><span class="n">voting_result</span><span class="p">[</span><span class="n">i</span><span class="p">])))</span>
    <span class="k">else</span><span class="p">:</span>
        <span class="n">y_predict</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="s2">&quot;N/A&quot;</span><span class="p">)</span>

<span class="n">count</span> <span class="o">=</span> <span class="mi">0</span>
<span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">y_true</span><span class="p">)):</span>
    <span class="k">if</span> <span class="n">y_true</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="o">==</span> <span class="n">y_predict</span><span class="p">[</span><span class="n">i</span><span class="p">]:</span>
        <span class="n">count</span> <span class="o">+=</span> <span class="mi">1</span>
<span class="nb">print</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">y_predict</span><span class="p">))</span>
<span class="nb">print</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">y_true</span><span class="p">))</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Final accuracy of binning:&quot;</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="n">count</span><span class="o">/</span><span class="nb">len</span><span class="p">(</span><span class="n">y_true</span><span class="p">)</span><span class="o">*</span><span class="mi">100</span><span class="p">)</span>
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<pre>563
563
Final accuracy of binning:
19.182948490230906
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<h3 id="Even-though-duplicating-records-in-bin-3-significantly-improves-f-score-for-bins-and-individual-prediction,-the-final-accuracy-of-prediction-percentage-of-match-decreases-heavily.">Even though duplicating records in bin 3 significantly improves f-score for bins and individual prediction, the final accuracy of prediction percentage of match decreases heavily.<a class="anchor-link" href="#Even-though-duplicating-records-in-bin-3-significantly-improves-f-score-for-bins-and-individual-prediction,-the-final-accuracy-of-prediction-percentage-of-match-decreases-heavily.">&#182;</a></h3>
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<h2 id="b.-Gaussian">b. Gaussian<a class="anchor-link" href="#b.-Gaussian">&#182;</a></h2>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">gnb</span> <span class="o">=</span> <span class="n">GaussianNB</span><span class="p">()</span>

<span class="c1">#split class labels from predictor labels</span>
<span class="n">l</span> <span class="o">=</span> <span class="p">[</span><span class="s1">&#39;no_matches&#39;</span><span class="p">,</span> <span class="s1">&#39;matches1&#39;</span><span class="p">,</span> <span class="s1">&#39;matches2&#39;</span><span class="p">]</span>

<span class="n">prediction</span> <span class="o">=</span> <span class="p">[]</span>
<span class="k">for</span> <span class="n">d</span> <span class="ow">in</span> <span class="n">l</span><span class="p">:</span>
    <span class="n">dup_data_Y</span> <span class="o">=</span> <span class="n">dup_data</span><span class="p">[</span><span class="n">d</span><span class="p">]</span>
    <span class="n">dup_data_X</span> <span class="o">=</span> <span class="n">dup_data</span><span class="o">.</span><span class="n">drop</span><span class="p">([</span><span class="s1">&#39;no_matches&#39;</span><span class="p">,</span> <span class="s1">&#39;matches1&#39;</span><span class="p">,</span> <span class="s1">&#39;matches2&#39;</span><span class="p">],</span>  <span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>

    <span class="n">cvp</span> <span class="o">=</span> <span class="n">cross_val_predict</span><span class="p">(</span><span class="n">gnb</span><span class="p">,</span> <span class="n">dup_data_X</span><span class="p">,</span> <span class="n">dup_data_Y</span><span class="p">)</span>
    <span class="n">a</span> <span class="o">=</span> <span class="n">cvs</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span><span class="o">*</span><span class="mi">100</span>

    <span class="n">prediction</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">cvp</span><span class="p">)</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">voting_result</span> <span class="o">=</span> <span class="p">[]</span>

<span class="c1"># no_match voting</span>
<span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">prediction</span><span class="p">[</span><span class="mi">0</span><span class="p">])):</span>
    <span class="n">vote</span> <span class="o">=</span> <span class="mi">0</span>
    <span class="k">for</span> <span class="n">j</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">prediction</span><span class="p">)):</span>
        <span class="k">if</span> <span class="n">j</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span>
            <span class="k">if</span> <span class="n">prediction</span><span class="p">[</span><span class="n">j</span><span class="p">][</span><span class="n">i</span><span class="p">]</span> <span class="o">==</span> <span class="mi">1</span><span class="p">:</span>
                <span class="n">vote</span> <span class="o">+=</span> <span class="mi">1</span>
        <span class="k">else</span><span class="p">:</span>
            <span class="k">if</span> <span class="n">prediction</span><span class="p">[</span><span class="n">j</span><span class="p">][</span><span class="n">i</span><span class="p">]</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span>
                <span class="n">vote</span> <span class="o">+=</span> <span class="mi">1</span>
    <span class="n">voting_result</span><span class="o">.</span><span class="n">append</span><span class="p">([</span><span class="n">vote</span><span class="p">])</span>

<span class="c1"># matches1 voting</span>
<span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">prediction</span><span class="p">[</span><span class="mi">0</span><span class="p">])):</span>
    <span class="n">vote</span> <span class="o">=</span> <span class="mi">0</span>
    <span class="k">for</span> <span class="n">j</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">prediction</span><span class="p">)):</span>
        <span class="k">if</span> <span class="n">j</span> <span class="o">==</span> <span class="mi">1</span><span class="p">:</span>
            <span class="k">if</span> <span class="n">prediction</span><span class="p">[</span><span class="n">j</span><span class="p">][</span><span class="n">i</span><span class="p">]</span> <span class="o">==</span> <span class="mi">1</span><span class="p">:</span>
                <span class="n">vote</span> <span class="o">+=</span> <span class="mi">1</span>
        <span class="k">else</span><span class="p">:</span>
            <span class="k">if</span> <span class="n">prediction</span><span class="p">[</span><span class="n">j</span><span class="p">][</span><span class="n">i</span><span class="p">]</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span>
                <span class="n">vote</span> <span class="o">+=</span> <span class="mi">1</span>
    <span class="n">voting_result</span><span class="p">[</span><span class="n">i</span><span class="p">]</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">vote</span><span class="p">)</span>


<span class="c1"># matches2 voting</span>
<span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">prediction</span><span class="p">[</span><span class="mi">0</span><span class="p">])):</span>
    <span class="n">vote</span> <span class="o">=</span> <span class="mi">0</span>
    <span class="k">for</span> <span class="n">j</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">prediction</span><span class="p">)):</span>
        <span class="k">if</span> <span class="n">j</span> <span class="o">==</span> <span class="mi">2</span><span class="p">:</span>
            <span class="k">if</span> <span class="n">prediction</span><span class="p">[</span><span class="n">j</span><span class="p">][</span><span class="n">i</span><span class="p">]</span> <span class="o">==</span> <span class="mi">1</span><span class="p">:</span>
                <span class="n">vote</span> <span class="o">+=</span> <span class="mi">1</span>
        <span class="k">else</span><span class="p">:</span>
            <span class="k">if</span> <span class="n">prediction</span><span class="p">[</span><span class="n">j</span><span class="p">][</span><span class="n">i</span><span class="p">]</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span>
                <span class="n">vote</span> <span class="o">+=</span> <span class="mi">1</span>
    <span class="n">voting_result</span><span class="p">[</span><span class="n">i</span><span class="p">]</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">vote</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Voting Results of first 10:&quot;</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="n">voting_result</span><span class="p">[</span><span class="mi">0</span><span class="p">:</span><span class="mi">10</span><span class="p">])</span>
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<pre>Voting Results of first 10:
[[3, 1, 1], [2, 2, 2], [1, 3, 1], [2, 2, 2], [1, 3, 1], [1, 3, 1], [1, 1, 3], [2, 2, 2], [1, 1, 3], [1, 3, 1]]
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Compile y_true</span>
<span class="n">y_true</span> <span class="o">=</span> <span class="p">[]</span>

<span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">ori_dup_data</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">0</span><span class="p">]):</span>
    <span class="k">if</span> <span class="p">(</span><span class="n">ori_dup_data</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">i</span><span class="p">,</span> <span class="s2">&quot;match&quot;</span><span class="p">])</span> <span class="o">&lt;=</span> <span class="mf">0.1</span><span class="p">:</span>
        <span class="n">y_true</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span>
    <span class="k">elif</span> <span class="p">(</span><span class="n">ori_dup_data</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">i</span><span class="p">,</span> <span class="s2">&quot;match&quot;</span><span class="p">])</span> <span class="o">&gt;</span> <span class="mf">0.1</span> <span class="ow">and</span> <span class="p">(</span><span class="n">ori_dup_data</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">i</span><span class="p">,</span> <span class="s2">&quot;match&quot;</span><span class="p">])</span> <span class="o">&lt;</span> <span class="mf">0.5</span><span class="p">:</span>
        <span class="n">y_true</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mi">1</span><span class="p">)</span>
    <span class="k">else</span><span class="p">:</span>
        <span class="n">y_true</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mi">2</span><span class="p">)</span>

<span class="c1"># Compile y_predict</span>
<span class="kn">from</span> <span class="nn">sklearn.metrics</span> <span class="k">import</span> <span class="n">accuracy_score</span>
<span class="n">y_predict</span> <span class="o">=</span> <span class="p">[]</span>
<span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">voting_result</span><span class="p">)):</span>
    <span class="k">if</span> <span class="n">voting_result</span><span class="p">[</span><span class="n">i</span><span class="p">]</span><span class="o">.</span><span class="n">count</span><span class="p">(</span><span class="nb">max</span><span class="p">(</span><span class="n">voting_result</span><span class="p">[</span><span class="n">i</span><span class="p">]))</span> <span class="o">==</span> <span class="mi">1</span><span class="p">:</span>
        <span class="n">y_predict</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">voting_result</span><span class="p">[</span><span class="n">i</span><span class="p">]</span><span class="o">.</span><span class="n">index</span><span class="p">(</span><span class="nb">max</span><span class="p">(</span><span class="n">voting_result</span><span class="p">[</span><span class="n">i</span><span class="p">])))</span>
    <span class="k">else</span><span class="p">:</span>
        <span class="n">y_predict</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="s2">&quot;N/A&quot;</span><span class="p">)</span>

<span class="n">count</span> <span class="o">=</span> <span class="mi">0</span>
<span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">y_true</span><span class="p">)):</span>
    <span class="k">if</span> <span class="n">y_true</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="o">==</span> <span class="n">y_predict</span><span class="p">[</span><span class="n">i</span><span class="p">]:</span>
        <span class="n">count</span> <span class="o">+=</span> <span class="mi">1</span>
<span class="nb">print</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">y_predict</span><span class="p">))</span>
<span class="nb">print</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">y_true</span><span class="p">))</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Final accuracy of binning:&quot;</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="n">count</span><span class="o">/</span><span class="nb">len</span><span class="p">(</span><span class="n">y_true</span><span class="p">)</span><span class="o">*</span><span class="mi">100</span><span class="p">)</span>
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<pre>563
563
Final accuracy of binning:
27.53108348134991
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<h3 id="Same-result-as-KNN.-Final-and-overall-accuracy-significantly-decreased.">Same result as KNN. Final and overall accuracy significantly decreased.<a class="anchor-link" href="#Same-result-as-KNN.-Final-and-overall-accuracy-significantly-decreased.">&#182;</a></h3>
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<h1 id="9.-Conclusion">9. Conclusion<a class="anchor-link" href="#9.-Conclusion">&#182;</a></h1>
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<ul>
<li>Based on the techniques we implemented, we discovered changes that improved our overall results. When running our data through the Naive Bayes classifier, our accuracies were 77.11%, 53.17%, 75.15%, 89.69%, and 98.06% for each of the five bins respectively. When implementing K Nearest Neighbors (KNN), we found that by changing our number of bins from 5 to 3 improved our results, with accuracies of 61.2%, 56.1%, and 96.5% for each bin respectively. When implementing Gaussian, we achieved accuracies of 56.3%, 53.4%, and 92.6% for each respective bin. We also checked for outliers in both columns for age and goal of speed dating columns. After removing 32 outliers, there was no significant improvement or changes in the results. to determine the effects it had on the results. After binning and voting, our final accuracy was 48.35%. Due to the F-score being very bad for bin 3, we decided to duplicate all of the data for values inside that specific bin. Using KNN, this drastically improved our F-score, but also demisoned the accuracy to 17.76% so we do not recommend going this route. After, we tried using Gaussian with the duplicated values, and it only improved the final accuracy to 28.42. </li>
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