From e9fd131e0024a3cfabd9fcc46a3e1cac8608d15d Mon Sep 17 00:00:00 2001
From: Alan R <alan.rominger@gmail.com>
Date: Tue, 26 May 2015 16:16:38 -0400
Subject: [PATCH 1/2] normal mode basics working

---
 .envrc                    |   1 +
 .gitignore                |   1 +
 Consumer Complaints.ipynb | 958 ++++++++++++++++++++++++++++++++++++++
 3 files changed, 960 insertions(+)
 create mode 100644 .envrc
 create mode 100644 Consumer Complaints.ipynb

diff --git a/.envrc b/.envrc
new file mode 100644
index 0000000..94840b3
--- /dev/null
+++ b/.envrc
@@ -0,0 +1 @@
+layout python3
diff --git a/.gitignore b/.gitignore
index 046e984..069cf1a 100644
--- a/.gitignore
+++ b/.gitignore
@@ -66,3 +66,4 @@ target/
 .ipynb_checkpoints/
 
 Consumer_Complaints.csv
+.direnv
diff --git a/Consumer Complaints.ipynb b/Consumer Complaints.ipynb
new file mode 100644
index 0000000..5557bde
--- /dev/null
+++ b/Consumer Complaints.ipynb	
@@ -0,0 +1,958 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 72,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "import matplotlib.pyplot as plt\n",
+    "%matplotlib inline\n",
+    "import datetime"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#Load Data, Poke Around at it"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 73,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "complaints = pd.read_csv(\"Consumer_Complaints.csv\", low_memory=False, \n",
+    "                         parse_dates=[\"Date received\", \"Date sent to company\"])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 74,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Complaint ID</th>\n",
+       "      <th>Product</th>\n",
+       "      <th>Sub-product</th>\n",
+       "      <th>Issue</th>\n",
+       "      <th>Sub-issue</th>\n",
+       "      <th>State</th>\n",
+       "      <th>ZIP code</th>\n",
+       "      <th>Submitted via</th>\n",
+       "      <th>Date received</th>\n",
+       "      <th>Date sent to company</th>\n",
+       "      <th>Company</th>\n",
+       "      <th>Company response</th>\n",
+       "      <th>Timely response?</th>\n",
+       "      <th>Consumer disputed?</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1382851</td>\n",
+       "      <td>Debt collection</td>\n",
+       "      <td>Other (phone, health club, etc.)</td>\n",
+       "      <td>False statements or representation</td>\n",
+       "      <td>Attempted to collect wrong amount</td>\n",
+       "      <td>IN</td>\n",
+       "      <td>46403</td>\n",
+       "      <td>Web</td>\n",
+       "      <td>2015-05-19</td>\n",
+       "      <td>2015-05-19</td>\n",
+       "      <td>Diversified Consultants, Inc.</td>\n",
+       "      <td>Closed with explanation</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>1383126</td>\n",
+       "      <td>Debt collection</td>\n",
+       "      <td>Other (phone, health club, etc.)</td>\n",
+       "      <td>Disclosure verification of debt</td>\n",
+       "      <td>Right to dispute notice not received</td>\n",
+       "      <td>GA</td>\n",
+       "      <td>30096</td>\n",
+       "      <td>Web</td>\n",
+       "      <td>2015-05-19</td>\n",
+       "      <td>2015-05-19</td>\n",
+       "      <td>Stellar Recovery Inc.</td>\n",
+       "      <td>Closed with explanation</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>1383251</td>\n",
+       "      <td>Debt collection</td>\n",
+       "      <td>Other (phone, health club, etc.)</td>\n",
+       "      <td>Disclosure verification of debt</td>\n",
+       "      <td>Right to dispute notice not received</td>\n",
+       "      <td>WA</td>\n",
+       "      <td>98055</td>\n",
+       "      <td>Web</td>\n",
+       "      <td>2015-05-19</td>\n",
+       "      <td>2015-05-19</td>\n",
+       "      <td>Stellar Recovery Inc.</td>\n",
+       "      <td>Closed with explanation</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   Complaint ID          Product                       Sub-product  \\\n",
+       "0       1382851  Debt collection  Other (phone, health club, etc.)   \n",
+       "1       1383126  Debt collection  Other (phone, health club, etc.)   \n",
+       "2       1383251  Debt collection  Other (phone, health club, etc.)   \n",
+       "\n",
+       "                                Issue                             Sub-issue  \\\n",
+       "0  False statements or representation     Attempted to collect wrong amount   \n",
+       "1     Disclosure verification of debt  Right to dispute notice not received   \n",
+       "2     Disclosure verification of debt  Right to dispute notice not received   \n",
+       "\n",
+       "  State  ZIP code Submitted via Date received Date sent to company  \\\n",
+       "0    IN     46403           Web    2015-05-19           2015-05-19   \n",
+       "1    GA     30096           Web    2015-05-19           2015-05-19   \n",
+       "2    WA     98055           Web    2015-05-19           2015-05-19   \n",
+       "\n",
+       "                         Company         Company response Timely response?  \\\n",
+       "0  Diversified Consultants, Inc.  Closed with explanation              Yes   \n",
+       "1          Stellar Recovery Inc.  Closed with explanation              Yes   \n",
+       "2          Stellar Recovery Inc.  Closed with explanation              Yes   \n",
+       "\n",
+       "  Consumer disputed?  \n",
+       "0                NaN  \n",
+       "1                NaN  \n",
+       "2                NaN  "
+      ]
+     },
+     "execution_count": 74,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "complaints.head(3)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 75,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "<class 'pandas.core.frame.DataFrame'>\n",
+      "Int64Index: 393491 entries, 0 to 393490\n",
+      "Data columns (total 14 columns):\n",
+      "Complaint ID            393491 non-null int64\n",
+      "Product                 393491 non-null object\n",
+      "Sub-product             270285 non-null object\n",
+      "Issue                   393485 non-null object\n",
+      "Sub-issue               121948 non-null object\n",
+      "State                   387998 non-null object\n",
+      "ZIP code                389029 non-null float64\n",
+      "Submitted via           393491 non-null object\n",
+      "Date received           393491 non-null datetime64[ns]\n",
+      "Date sent to company    393491 non-null datetime64[ns]\n",
+      "Company                 393491 non-null object\n",
+      "Company response        393491 non-null object\n",
+      "Timely response?        393491 non-null object\n",
+      "Consumer disputed?      361320 non-null object\n",
+      "dtypes: datetime64[ns](2), float64(1), int64(1), object(10)\n",
+      "memory usage: 45.0+ MB\n"
+     ]
+    }
+   ],
+   "source": [
+    "complaints.info()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 76,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Index(['Complaint ID', 'Product', 'Sub-product', 'Issue', 'Sub-issue', 'State',\n",
+       "       'ZIP code', 'Submitted via', 'Date received', 'Date sent to company',\n",
+       "       'Company', 'Company response', 'Timely response?',\n",
+       "       'Consumer disputed?'],\n",
+       "      dtype='object')"
+      ]
+     },
+     "execution_count": 76,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "complaints.columns"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 77,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Debt collection\n",
+      "<class 'str'>\n",
+      "0   2015-05-19\n",
+      "1   2015-05-19\n",
+      "Name: Date received, dtype: datetime64[ns]\n",
+      "2015-05-19 00:00:00\n",
+      "<class 'pandas.tslib.Timestamp'>\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(complaints[\"Product\"][0])\n",
+    "print(type(complaints[\"Product\"][0]))\n",
+    "print(complaints[\"Date received\"].head(2))\n",
+    "print(complaints[\"Date received\"][0])\n",
+    "print(type(complaints[\"Date received\"][0]))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#Complaints by Month"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 78,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "complaints.index = pd.to_datetime(complaints[\"Date received\"])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 79,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Date received\n",
+       "2015-05-19    Debt collection\n",
+       "2015-05-19    Debt collection\n",
+       "2015-05-19    Debt collection\n",
+       "Name: Product, dtype: object"
+      ]
+     },
+     "execution_count": 79,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "complaints.Product.head(3)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 80,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "by_month = complaints.Product.resample(\"M\", how=[\"count\"])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 81,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>count</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Date received</th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>2011-12-31</th>\n",
+       "      <td>2556</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2012-01-31</th>\n",
+       "      <td>3266</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2012-02-29</th>\n",
+       "      <td>3507</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2012-03-31</th>\n",
+       "      <td>6247</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2012-04-30</th>\n",
+       "      <td>5725</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "               count\n",
+       "Date received       \n",
+       "2011-12-31      2556\n",
+       "2012-01-31      3266\n",
+       "2012-02-29      3507\n",
+       "2012-03-31      6247\n",
+       "2012-04-30      5725"
+      ]
+     },
+     "execution_count": 81,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "by_month.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 84,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "count    3586\n",
+       "Name: 2015-05-31 00:00:00, dtype: int64"
+      ]
+     },
+     "execution_count": 84,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "by_month.ix[-1]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 85,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "by_month = by_month.drop(by_month.index[-1])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 86,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>count</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Date received</th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>2015-02-28</th>\n",
+       "      <td>12709</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2015-03-31</th>\n",
+       "      <td>14558</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2015-04-30</th>\n",
+       "      <td>13442</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "               count\n",
+       "Date received       \n",
+       "2015-02-28     12709\n",
+       "2015-03-31     14558\n",
+       "2015-04-30     13442"
+      ]
+     },
+     "execution_count": 86,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "by_month.tail(3)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 87,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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RVKo+t719G2TsGGE4gqB/ckTVPcDy1elGguFLS+s4Ktge23aJSkbRMdFBT0If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\npCe6R725AAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x106e660b8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "by_month.plot()\n",
+    "plt.title(\"Number of Complaints by Month\")\n",
+    "plt.ylabel(\"Number of Complaints\")\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "After some searching around online, this fast growth in recent years looks consistent with reality. The bureau was created not long before the start of this graph. It stands to reason that its role has not fully matured and that it will experience rapid growth in reports until it does."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#Number of Complaints by Product"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 89,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "complaints.index = complaints[\"Product\"] # did not pop the date received, so table does not need to be reloaded"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 97,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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2L1NHUp8kjWkja7IMhUkb4XQSZcAhpBlZD4UHgEZloT5pq5xuyaA0YUFVx5lH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\nN3OzTSqbYHOtNrXddiFDfL318itDfNo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tWJI2yeIUIKyqT8caVHW5qs4XkZNF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\nGGOMSVL/D01u4s7njCPvAAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x105c31b70>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "complaints[\"Product\"].value_counts().plot(kind=\"pie\")\n",
+    "plt.title(\"Complaints by Product\")\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 98,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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cmC87EPhlfn0esK+k5SStD2wAzLR9F/CIpG0liWRozi28p1XXXsAlI2lrEARB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\n0ZOiEBERPSkKERHRk6IQERE9/wIGf6Bh0Lt8wwAAAABJRU5ErkJggg==\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x107823358>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "complaints[\"Product\"].value_counts().plot(kind=\"bar\")\n",
+    "plt.title(\"Complaints by Product\")\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This info is also consistent with the news on the subject. Mortages, debt collection, and credit reporting contain an obvious conflict of interest between the consumer and the company involved. Many people have problems with mortagage affordibility and complain because of a refusal to restructure the debt or poor terms that are offered. Considering the large number of people obliged to a mortage also clearly contributes to the numbers."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#Number by Company"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 101,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Wells Fargo            32860\n",
+       "JPMorgan Chase         26088\n",
+       "Experian               20027\n",
+       "Citibank               19494\n",
+       "Equifax                19427\n",
+       "Ocwen                  16782\n",
+       "TransUnion             15219\n",
+       "Capital One            12009\n",
+       "Nationstar Mortgage     9660\n",
+       "dtype: int64"
+      ]
+     },
+     "execution_count": 101,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "complaints[\"Company\"].value_counts().ix[1:10]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 103,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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IgkrM1z5/1xie6DcIgqCbGcrnP2k8jMmL4R8gQRAEvUgPuX36stAIf2Z9GjnYkItGDjbk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\nkvwjIkYoyT8iYoT+B4Gu9SykoxK7AAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x116f48be0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "complaints[\"Company\"].value_counts()[:20].plot(kind=\"bar\")\n",
+    "plt.title(\"Complaints by Product\")\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This is also not very surprising. Some of the largest and most well-known banks come first, clearly because of the large number of customers they have. Some credit reporting agencies are thrown in there as well, notably Experian and Equifax. The subsequent companies seem to go into a wider variety of products."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#Number by Company Response"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 107,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Closed with explanation            277554\n",
+       "Closed with non-monetary relief     50213\n",
+       "Closed with monetary relief         28024\n",
+       "Closed without relief               17909\n",
+       "Closed                               9551\n",
+       "Closed with relief                   5305\n",
+       "In progress                          3107\n",
+       "Untimely response                    1828\n",
+       "dtype: int64"
+      ]
+     },
+     "execution_count": 107,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "complaints[\"Company response\"].value_counts()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Note that this only has 8 categories. It is also important to consult the original counts, and this has fully 393491 entries. That means that every entry had this field filled, and it is very clean data. It seems certain that the bureau forces this response to be one of a small list of pre-selected options."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 109,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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G/LvtrzCinJl9VPmdpOfb/i5UF7MB/1Nzpn7eChwPPEnSL4CbqQZLG8X2aZJW\nUH3DAdizaTWr2pCxaMsZzaHAwVRdmn8FfA34dK2J+tub6qzrINu3lwkG/1Zzpn5uk3Q88BLgyHLh\n6ki+xGegmWpWD1W/Ymcc4bfAAaMY6V8dkh4GrNXAmR0bllPejTu7yk/D+LfcWrUhYzdJb6Dq0lwK\nnAy8FvgH22fVGqzFJG0LPKFrltQS23fXm2qy8n98D+Aq2zeWyQY72j5vwY+dRmFCmbNMA/+B7Gf7\nVEl/w+R+WlENLXy4pmiTSPqq7T+XtJL+U3wfO/pUk7UhYy9V65J3zmguaNIZjaTP2X6dpKv7PGzb\nTxt5qBm0ZZYUjI/L/BFdPTq2f77Qx13U3UfTfdiWy/Yb82ELPLT83IA+jcLo4/Rn+8/Lz21rjjKt\nNmTsJunxwM22j5G0G/ASSb+03YTFmgHeUX6+vNYUg3sL1fTei6GaJSWpcbOkJL2N6ur7XzExvgCw\n40Ife1E3Ckz/Ydsotj9Vfh5Rc5QZzTZlrglXiLchY48vAEvLBINPAWcDpwN/VmuqwvYvys+VNUcZ\n1H227+uUtmjwLKl3Ak+0feeszxyyRd0odD5sgW/anlRPpgw2N4Kko2d4uEm1jz7MzP/BmnCFeBsy\ndnuwLDb1auBo20dLurzuUB2S7mX632cTax/1zpI6hGbOkvo55ZqPUcuYAiDpctvP6Nl3me1GVM2U\ndCATtY46xmsf2T65jlyx8CRdAnyM6qLFl9u+WdI1tp9ac7RWKhcD/h+qOmJQrer4aTfsg1DSZ4Dt\nga8ycbHqSLq0F/WZgqTnAM8FHi3p3Ux86G5AtfxnI/TWuZH0MNv/XVOcWZWZE+8Gtrb9JknbUZ0K\nf6XmaOPakLE4CHgz8IHSIDwOOLXmTH1Jej7VrJ4Ty9TZh9u+ue5cHaWr6BrbT6Ka2t1kPy+3dctt\nZOOHi/pMQdILqboL/orJVwveA3zZ9o21BJuGqnUAPg1sYHurMpX2L8vFTY0h6Syqaq77lxpNDwO+\nb/vpNUcb14aMHZLWo/rWaEZYA2cuJB0B/DGwve3tJW0JfM72c+tNNpmks4G3N7HWUT+SNgAY5fTz\nRX2mYPvbVH2MJ7VkoOyjVHOXzwawfUVp2Jrm8bb3krQPgO3/VvNq1rchI5KWUV2f0PkQ21rSAeXf\nbpO8iqr66AoA27dJeni9kfraGPiRpOVA52zbbljZb0k7Ul07tUnZ/jXVtVPXLPSxF3Wj0OV/JP1/\nwA7A+mVeksGdAAAb2ElEQVSfbf9JjZn6sv3zng+vkSy8MUf3Ser8HjvTKu+b4fl1aENGqAbGd7d9\nPUCZV/9ZquqeTXKf7Qe7ZvU8rOY80/nHugMM6Hjg3bYvhPEvB8dTdXcvqDQKlf8AzqSqM/JXwIHA\nr+sMNI2fa2K95nWBtwONuZCpyxHAucBjJJ0OPI/qd9okR9D8jFBdbXt9Z6PMq2/i/9vPSfoUsFG5\nQOwgGljmwvZY3RkG9NBOgwBV7lE1tIt6TKGjM9NI0lWdKzAlXeqG1daX9Ciq9ZpfTDXwdB5V/+jI\n5zJPp8zueB1wAfDssvsS241pZNuQsUPSiVQXL51G9Xf+eqoSJwfVGqxLudhzK+BJdM3qsX1+fan6\n09QlQ6Fa0eyHwN/Y/umII/Ul6UtUXXGnMvH3vtT2qxb82GkUQNLFtp+tapm+jwO/oBoka0yl1PLt\n8GTbjSuA10vSCttL684xkzZkBCiF0N5CdSYD8F3gWHeVqa5baRSubsM0WUn/DNwCnFF27UNVEfly\n4M22l9UUbZJSm+u9TP57P8L2bxf82GkUQNLLqX7pW1GVVN6Q6i/gnFqD9ZB0EfCiJn0g9CPpSOC/\nqLrkxqfOukHF5tqQsU0knUy1PkGjljPt1d0b0LXvCts7SbqyabPPVC32ZY+wHlsahRaRdCrVKfo5\nTJT2blKNJgCmKTZn24+rIU5fTc84TYG5Dvd+sNVN0vXAE6hmSXXP6mlazouBj1Ct9wBV1dl3l56C\nK2zvVF+6CZKeRbWwTueK8FXAwbYvXehjN3HAauRKQaw3Adsy8Ttxk/pti5+U21pAE6f7Ae0oNteC\njK8GNgVu7dm/Fc1cWOmldQcY0OuprhD/RNm+GHhDmYn21tpSTfUZ4BBPXuPlM8CCN7I5UwAk/QD4\nDtXATmcBE9v+fH2pYjGT9FXgUNtX9+x/GtXVzW2pShqroc7SO2kUmOhTrDtHRMdMs99S+2j1SdqK\najJJp+Dld4B32O49I6uVpI9SXTPVGRDfm2pJ1lNhYav5plFgfEbCD2x/te4sEQCSbrL9hLk+FjOT\n9E2q65JOK7teD7ze9kvqSzWVpDFmWDvF9oJV802jwHj534dSVSPs1JWxG1b2V9ImTbomYTqSvgCc\nAHzddhPXE0bSBe5ZbavfvrpI+izwLdvH9+x/E/Bi23vXk6zd+s0wauKsozqNZCHoprP9cNtr2X6I\n7Q3KrVENQnGxpM9J+jM1sVDPhOOovoHdJOlISU+sO1CHpPUlbUJVGXfjrtu2wJb1ppvkncAbJX1b\n0ofL7dvAweWxRpH0Gkk3Srpb0j3l1qhlbYs7Je0naW1JS1Stgf1fdYfqJekdkjZU5QRJl0kayWB+\nzhQKSY8EtgMe0tln+zv1JZqqXIn7YqoSAs8CzgJOtH1DrcGmIWkjqouD/oGqDPC/A6fVWeVT0jup\nlpDcguoixY57gONtH1NLsD5Kw78b8FSqroMf2f5Wvan6k/QT4GVu0PrR/UjaBjiGiSvZvw+8zSNY\n+3guOtdTlIbgzVQ1m07tHXxekGOnURg/JX871XS/y6n+wfygiQXxOiT9CVW/6MOAK4DDbH+/3lQT\nyrfx/YA3UH34nk41uPfUJlw1Kulttmda0S7mQNL3bD9v9mfWp2VVAa62vaOkjwNjtr/Qb0bSQsh1\nCpV3UH3z/oHt3SQ9CfiXmjNNUWofvR7YH7iDal71l4GnA/9JdZ1F7SR9keoiu1OpVgvrzKv/rKQV\n9SWb5G5J+/futH1KHWHaStJryt1LJZ0JfInJK4V9oZ5kU7la1nQbSes1vSoAsKKU3XkccKikDZmY\nLr+g0ihUfm/7d5KQ9BDb1zWpH7zL96nODvbsmUJ3qaRPTvOakSpdXJdNV7irQfWGnsXEbI71gT8B\nLqOqYR+DezkTv8ffMVEQr6MxjUJxM3CRpEZXBaAaO3o68FPb/1POvN84igOnUajcUsYUvgScL+m3\nwMp6I00maW2q1eDe1+9x20eOOFJfrmrqvwZ4f91ZZmJ70tWrZfzjzJritJbtA6G64tb2Rd2Platw\nm6a3KsDIlrmcIwNPoSrn/z6qbuKHzPiKIcmYQg9Vi1lsCJxr+/5Znj5SpW7Lc9zwvzRVCxZdDHy+\n6Vk7VK1PcY3t7evO0kb9rrYd1RW4q6OOQnNzUc78/5eqAOaTVFVNPW+6CxqHaVGfKZRfdK+rys+H\nA02rmHkFcLakzzH51Ldpp+hvBt4N/K+k35d9jbruQ9KXuzbXolp176ya4rSWpOdQrQb2R5LeTfXN\nG2ADYO3agk2jt9CcpJEVmpujXWw/Q9LlUFXvlbTOKA68qBsFqj7k6b7JmmqQp0keQtVQ9c6KalSj\nYLuxxfq6fKj8NNWSpj+3fUuNedpqXSYagA269t9NVYG0aWorNDdH95cuYwAkPZoRDTSn+ygWREuu\n+9iMiQHn5bZ/VXOk1pK0je2f1Z1jNnUWmpuLclHdXsBS4GSqBvYfbC/42WwaBcYvEno11Tz6B4GL\nbH+x3lRTqSrvezBVV8f6lLOcppX4bsN1H5L2Av4N+HbZ9QLg72x/bvpXRS9JH7P9jp7uuA7bfsXI\nQ81ANRaaG1SZwfccql6BTtmVC0Z1YWAaBUDScVRL8p1B1Se6N/AT24fUGqyHpP8Efkx1rcJ7qS4M\n+7Htt9carIeka5i47mOnznUf001TrYOkq6hqCP2qbD+a6j9e07oRGk3SUtsrygSNXrb97T77a6Op\nheYmWchCc3OhGis3L/YxhY7dgB06xdsknQRcW2ui/p5g+7WS9rR9sqTTgYtmfdXoteG6DwG/7tq+\nk4lB0hiQ7c7FiEuA79n+XZ15ZtOEq+kH9E1Jr6WGGXxpFCo3AVszcW3C1mVf03SmyN4laUfgduDR\nNeaZzq1Nv+4DOBf4RmlYO2eHX683UqvtDxxb/q6/U24XeQQLza+hapvBl+4jQNJ3qLo7llOdWu4M\n/JBqBkVj+kVLX/3ngR2Bk6imzf6j7UZczdxPU6/76BlHMvDdJo4jtY2kLagGRf8W2MJ2vni2TBoF\nxj+4eplytWNT+kUlPc72T2fbVzdJp9reb7Z9seaQtB9VA/s0qm65i6jOFBpTpDEGk0YBkLSD7Wt7\n9i2zPVZTpL6muWp0RYPqCQFTp/2V6pRX2d6hxliTlFIcRwKbMjGW0KgL7NpE0p1U5SOOo6rqeXPN\nkaYl6XlUxSM7ZzFOIcQJObWrnCXpVOBfqaarHUXVnfTsGV81IpKeTDUNdSNJr2aiXsuGjKgeyiAk\nvQc4DFhf0j1dD/0BOL7/q2rzr7Sg/n+LPIqqVs/zgQ9IegJwg+031BtrMkmnUV2UegVVGYmONApF\nGoXKLlQNwQ+o+ulPp7p0vym2p6pG+Yjys+Me4E21JOrD9geBD0o60vahdeeZxe1pEIZqA6oJGttQ\nfQvfiBFdgTtHS6lmGja6i0TSh4ETbP9o1MdOo1B5gKrs7/pU37x/6gatLWz7bKqaR89tSR/te0of\n82Ntv0/S1sBmtpfXHaxN9f9b5iLge8B3gWN6Srs3yTXA5kxeda+JfgwcX+odfQY4w/ZdozhwxhSo\nFu4GzqEqUfso4FPAfbZfV2uwHmWu/7FUH7BPkfQ04BW2/7nmaJOUCo8PAn8y6gqPsynXoHT+0U8p\nm2x7JDXrox7l4rWdqGYadhbaacwMw17lws8Dgb+ganj/3faFC3rMNApV5UTbP+zZt5/tU+vK1E+Z\nOvt3wCdLBUVRlXt+Ss3RJukMNHcPOEu60vbT687WMV39/959sWaZZqYhTZtUAuNrqLycanGdx1BV\n8d0V+B/bey/UcdN9VFnRp7vjhrpD9fFQ25dUbUH19UbSH2rO1E9tFR7n4ONAbxG0fvtiDdLED/9+\nJH2EqkH4FvCBrq7XoyRdv5DHTqNQOZbS3UHVhXQv8Amg9u6OHr8uszoAKJfB/3KG59flaOCLVDX2\nP0ip8FhvpErb6v/HcEi6lxnK5DdwKvJVVFVR/7vPY7ss5IHTKFRqW9Bijt5KNbXzSZJ+QbXe7Ovr\njTSV7dMkrWCiwuOeDZrp07b6/40m6eiuzc4Fn+PbTSnW2JI1PpC0lOr3eBXwxE6vABMX0l5me9VC\nZkijUGlDdwe2fwK8SNLDgLVs3zPba2p0A9UH7RLAkra2/fOaM1GuTv+2pBPdgvr/LdApiPdcqmtp\nzqT6AHsdMPLplGuADzHzmtELXsU1A83Uu6DFXEh6CPAaqnngazPx7eF9debqJeltwOHAr+i6QMj2\njrWFKtpW/78tJF0C7Gr7D2V7HaoyFwva1RHDlzMFGt/d0e1sYBXVt7Pfz/LcOr0TeKLtO+sO0kfn\nytUP9Xks35BW30ZUV9h3/s43KPtiNZTegHcDW9t+k6TtqP5PfWWhj51GoSiNQBMbgm5b2n5p3SEG\n8HOqrqPGaVv9/xY5ErisXAcA8ELgiNrStN+JVF/+OpUVfgH8J7DgjUK6j1pE0vFUV4teVXeWmUj6\nDFVpjq8y+WrhD9eXajJJp1DVtkr9/yGRtDlV2XmAS2zfXmeeNusUuqzjWp+cKbTL84E3SrqZyVdj\nNm0JyZ+X27rlNuXK4brZ3h8m1f//BLAF+T+xWlStK/xiuq71kbRzE0qbtNR9qtZkB0DS45n4P7+g\ncqbQIpK2LXe7yzRge2UNcWYlaQOAJs6SSv3/4eoqbbKb7Sc3qbRJG0naHfh/VDO6zgeeBxy40CUu\nII0C0K7a+pJ2ojpj6KwWdmXNkaYoS4WeAmxSdv0aOMD2NfWlmqxN9f/boA2lTdpG0qOYKN9/se3/\nGsVx1xrFQVrgX6kKy21oe4Nya2KD8A7gNKp1mTcFTpPUiIuDehwPvNv21ra3Bv6G5q2n8CjgIKqq\nuB+QtLzU2o/V04prfVpmS6qp5+sBLyhrqSy49J9W2lJb//9QXX393wCSjgQupqrZ0yQP7T7NtT1W\nptg1SVvq/7dFY0ubtJGkE6nWYv8Rk/9dLnhp90XdKLS0tv6D09xvkpsl/SNwKlV33OuBRq0jTXvq\n/7dCi671aYtdgKfUsRjQom4UqKoQdn7pvwN273m8aY3CicAlkr5A9WH7SqoFOJrmIOC9TPz+vlv2\nNUYDZ2y1Wpkdc7PtYyTtBrxE0i8Xuk7PGuyHVIPMIy8VkoFm2lVbvxTM2pWJgebLa44U0VmoailV\nV9zXqK6+f4rtP6szV1uVdR/OAW5nxNPP0ygAki6z/czZ9jWBpEdS9YUvoZzl2L6s1lA9JD0LeA/V\nB0TnbLSJ11PEkHTNPvq/wO9sH909EynmRtJPgHdRLR863k08iunni7r7qG219SW9n2ppvp8yeTxh\nwSsnztF/AH9Lzz/oWKPdL+kvgP2pumUBmlh+vi1+ZfucOg68qBsF2ldbf2/g8bbvn/WZ9fp1Xf+g\nZ9OW+v8tdBDwZqpVwm6W9DiqiQaxei6XdDrwZUY8+SXdR4CkbdpQW1/SF4E3276j7iwzKVdj7g18\nk4bN5pJ0YLnbt/6/7TfXFK31JK1HVfPKwPWdMtoxd5JOKncnfUDbfuOCH3sxNwptq61f+urPpuqW\n6R58alrO/wCeSM8c61H8gx5U6v8PVxkYPRnofLnamuoq9m/XFipWy2LvPmpbbf1TqMpxdPfVNzHn\nHwNPqmOO9Ryk/v9wfRjY3fb1AJK2Bz4LNG6yRpNJ+nvbR/V0c3aMpHtzUTcKLaytf6/tpl293M/3\nqWmO9Ryk/v9wLek0CAC2b5C0qD9fVtO15ecKJn/hG1ml4UXdfdTRltr6kj5M1W10Dl1ldBs4JfU6\n4PFAo0t8p/7/8JSyDP9LVZurcxX7WrYbddFiW0jayz3LAffbtyDHTqMwoau2/t8CW9hu1Ded8q12\nyl+Y7UZNSe0q8T1Jk0p8l/r/r6er/j+wWer/r56yfvhbqEo8Q3UV+7G2R7IGwJqm3zUeo7ruI40C\nqa2/GKX+fzSRpD8F/oxq9t5nmXzt1A62d57utcPSqG/CNfooLautL+krtl9Wd44W26VT/x/A9m/K\nDKSYA0lXz/Bw47oMW+AXVOMJe5afnUbhbqornBdcGoXKo4CnUC1e8wFJTwBusP2GemPNaMu6A7Rc\n6v8Px8tnf0oMqiyadaWk/6jrOo80CpU21ta/ou4ALZf6/8OxDrBpv4KSwC/ribRG2EXS4UytH/a4\nhT5wxhQASVcxUVv/O6mtPz9tWd5U0pOZqP9/Qer/z52krwKH2b6qZ//TqEpe5ExiNUi6HngncBnV\nrC4ARrEkZxqFFinfvmr59jAXpcLjy5r8IVvq/99m+/el/v+OwCmp/z83ki6dbnBe0jW2nzrqTGsC\nSZfUdXV9GoUWqfPbw1xI+p7t583+zPqk/v9wSLrJ9hPm+ljMrCy1uzbVQlUjvSYpYwrtssr21+sO\nMZ2WLW/6oO0HymLoR3fq/9cdqoUulfSXto/v3inpTVSzZ2L1PJvqmqTes7AFvyYpZwotUue3h0GU\nyo6df1BTLstvYEG8j1EtBvTyUu453R1zJGkzqgH7+5loBJYC6wGvsp3B5pZZ1I1C22rrt+iK5sYv\nbyrpKVT1/79v+4xS//91to+qOVrrSBLVN9inUv37/JHtb9Wbqp0k/U25666f/0V1Me1Irp9a7I3C\ngeVuausPUVuWN039/2gaSUcw9YvfJsBLgSNsn7HgGRZzo9DRltr6kjaimn30grJrDHif7btqC9Wl\na3nTd1GVUu6+RP9Vtp9eV7Zeqf8fbVLKsFwwitpHay30AVqiU1u/o6m19T9Ddbn764C9gHuAE2tN\nNFnv8qYPL7cmLm/aqf//AtsvAHYHPlJzpoi+bP9mVMfK7KNKW2rrP972q7u2jyhTKxuhfMv+tqQT\n3fzlTVP/P1qjXEszklL++U8A2D5R0rlM1Nb/+4bW1v+dpOfb/i6MX8z2PzVnGtdZ3hQ4php7nKRp\ny4aukPRpJtf/v7TeSLHYTVNg8JFUJUP2H0mGjCm0p7a+pJ2oluR8RNn1W6p+8EacLUhaantF6a/v\n5Sb116f+fzRRn7VIDNxp+96RZUij0L7a+pI2BLB9d91Z+pH0YtqxvGlE9Ej3UaUVtfXLt9vXUJVm\nWLvMD7ft99UabKr9gWMlNW5509T/j5hZGoVKW2rrnw2sorpy9Pc1Z5mW7f1h0vKmnwC2oBn/3lK1\nM2IGTfhP2gRtqa2/pe2X1h1iNn2WNz2GaonTJkj9/4gZZEyhaENtfUnHA8f01q5vGkl30tDlTVP/\nP2JmaRRoT219ST8GngDczERBvMb1g5exjs7yps+nytyI5U1T/z9iZuk+qnwBWFrWZv4UVd/96UDT\nauv/ad0BBtTk5U1nulL9ISNLEdFQaRQqraitb3tl3RkGdBETy5se07DlTVP/P2IGaRQq90v6C6qp\nlJ0+5cZNSW2LpnVn9Xgn8EVJr6dP/f/aUkU0RMYUSG39xSb1/yOml0ahSG39iIiUzgbGa+vfQHWR\n1bHAjZJeWGuoPiS9RtKNku6WdE+5NbLURUS0U84UqFYFA/btlFKWtD3w2QauFPYT4GVNvIYC2re8\naURMlTOFypTa+jRzEP72pjYIxYpyWw94JtXZ143ATlQL8EREw+VMAZB0IvC/TK6tv5btg2oNVkh6\nTbn7AmAz4EvA/WWfbX+hlmDTaMvyphExVRoFml9bX9JJTCzmLXoW9rb9xlFnmomk64Hn2r6zbG8M\n/MD2E+tNFhGzSaPQIpJ27VfIrXdf3SS9kWo507Gy64XAEbZPqilSRAxoUTcKbautL+my3sHvfvua\nQNLmTCxveklDlzeNiB5NHEwdpVZUxJT0HOC5VKW9383ErJ4NgLWnfWFNyvKmL6ZreVNJOzdtedOI\nmGqxzz5aB3iM7ZXdN+AxNOvDdl0mGoANgIeX291Uaz80zbHAc4B9y/a9ZV9ENNxi7z5qVW19SdvY\n/lndOWYj6fLO8qa2n1H2XWn76XVni4iZLfbuo037LVhj+ypJj60jUD+SPmb7HcAxVdmeSWz7FTXE\nmklbljeNiB6LvVFoS239U8rPD/V5rImnem1Z3jQieiz2RqEVtfVtd7IsAb5n+3d15pmN7dMkrWBi\nedM9G34ldkQUi31MYTOqb7T306e2vu1GLeQu6RTg2cBvge+U20W2f1trsB5tWd40IqZa1I0CtLO2\nvqQtqLpk/hbYwnajzvgkXUnVuG4LfI1qedOn2G7a8qYR0WPRNwptImk/YFfgacCvqZa9vMj292sN\n1qNr9tH/BX7XWd60MxMpIpqrUd8wY1YfBX4CHAeM2b655jzTyfKmES212C9ea5tHAQdRzYz6gKTl\nkk6rOVM/B1FdvPYB2zeX5U1PrTlTRAwg3UctImlDqu6jF5Tbo4CLbe9fa7A+srxpRDulUWgRSVcB\n36Mq7f0d27fWHKmvsrzpyUDn6uutgQNsf7u2UBExkDQKMXRtWd40IqbKmEIshLYsbxoRPfIfNRbC\nCkmfZvLyppfWGykiBpHuoxi6pi9vGhHTS6PQApKO7to0E4vsQFUl9e0jjhQRa6h0H7VDpy7Tc4Ed\ngDOpGobXAT+qK1Svti1vGhFT5UyhRSRdAuzamfMvaR2qMhe71JusImnbmR4vq9pFRIPlTKFdNgI2\nBO4s2xsw85oQo7YO1cJFF3XvlLQr0KiKsxHRX6aktsuRwGWSTpZ0MnAZ8C81Z+r2Uap1o3vdXR6L\niIZL91HLSNoc2LlsXmL79jrzdJN0qe0/nuaxa2w/ddSZImJucqbQIpLWAl4MPN322cC6knae5WWj\n1JblTSNiGmkU2uVYquqj+5bte8u+prhU0l/27mza8qYRMb10H7VI1+I14wvWSLrS9tPrzgbtW940\nIqbK7KN2uV/S2p0NSY8GHqwxzyS2b5f0XCYvb/qVpi9vGhETcqbQIpLeAOxF9e37ZKp1mv/B9lm1\nBouINUYahZaR9GTgRWXzAts/rjNPRKxZ0ii0iKTHA7fZ/r2k3YAdgVNsr6o5WkSsITL7qF2+ADwg\n6QnAp4CtgNPrjRQRa5I0Cu3yoO0HgFcDR9v+O2DzmjNFxBokjUK73C/pL4D9ga+UfevUmCci1jBp\nFNrlIKqL1z5g+2ZJjwNOrTlTRKxBMtDcMpLWA7anugbg+k4Z7YiIYUij0CKSllFdn/Czsmtr4ADb\n364tVESsUdIotIiky4B9bV9ftrcHPmv7mfUmi4g1RcYU2mVJp0EAsH0DKVUSEUOUD5R2WSHp08Bp\nVGs0vx64tN5IEbEmSfdRi0h6CPAW4Hll13eBY23fV1+qiFiTpFGIiIhx6T5qAUlXz/CwbT9tZGEi\nYo2WM4UWkLTtTI/bXjmSIBGxxsuZQjusA2xq+6LunZJ2BbKaWUQMTaaktsNHgbv77L+7PBYRMRRp\nFNphU9tX9e4s+x5bQ56IWEOlUWiHjWZ47CEjSxERa7w0Cu1wqaS/7N0p6U3AihryRMQaKrOPWkDS\nZsAXgfuZaASWAusBr7KdweaIGIo0Ci0hScBuwFOpymb/yPa36k0VEWuaNAoRETEuYwoRETEujUJE\nRIxLoxAREePSKERExLj/HwGVD9eRg3FQAAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x117171eb8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "complaints[\"Company response\"].value_counts().plot(\"bar\")\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 110,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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lUiu98koVz4POndEe3Ql6u8Qa69nTJdSan/n5taYRNUBWFvTu7W6bIGzi+yw5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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x116e92518>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "complaints[\"Company response\"].value_counts().plot(\"pie\")\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#By Day of Week"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 112,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "complaints.index = pd.to_datetime(complaints[\"Date received\"])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 114,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "dow = [\"Sunday\", \"Monday\", \"Tuesday\", \"Wednesday\", \"Thursday\", \"Friday\", \"Saturday\"]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 115,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "complaints[\"day_of_week\"] = complaints.index.to_series().map(lambda d: d.weekday())"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 118,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Date received\n",
+      "2015-05-19    1\n",
+      "2015-05-19    1\n",
+      "Name: day_of_week, dtype: int64\n",
+      "Date received\n",
+      "2011-12-01    3\n",
+      "2011-12-01    3\n",
+      "Name: day_of_week, dtype: int64\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(complaints[\"day_of_week\"].ix[:2]) # seems to be working\n",
+    "print(complaints[\"day_of_week\"].ix[-2:])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 120,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0    71313\n",
+       "1    74170\n",
+       "2    76118\n",
+       "3    72707\n",
+       "4    63863\n",
+       "5    19109\n",
+       "6    16211\n",
+       "dtype: int64"
+      ]
+     },
+     "execution_count": 120,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "complaints[\"day_of_week\"].value_counts().sort_index() # seems like a reasonable list"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 122,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "weekday_plot = complaints[\"day_of_week\"].value_counts().sort_index()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 123,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "weekday_plot.index = dow"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 124,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Sunday       71313\n",
+      "Monday       74170\n",
+      "Tuesday      76118\n",
+      "Wednesday    72707\n",
+      "Thursday     63863\n",
+      "Friday       19109\n",
+      "Saturday     16211\n",
+      "dtype: int64\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(weekday_plot)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 127,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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UagcolKr06sHfzGwMueY/eKKxqhv2vXbX/Lv14Pzd1u78c/Xgmr+ZmQ3Gg/+U\nVDtAoVQ7QIFUO0ChVDtAoVQ7QKFUO0ChVKVXD/5mZmPINf/BE41V3bDvtbvm360H5++2duefqwfX\n/M3MbDAe/Kek2gEKpdoBCqTaAQql2gEKpdoBCqXaAQqlKr168DczG0Ou+Q+eaKzqhn2v3TX/bj04\nf7e1O/9cPbjmb2Zmg5k3g7+k0yVtlrRV0ttGnyCNvsuhSrUDFEi1AxRKtQMUSrUDFEq1AxRKVXqd\nF4O/pH2BPwZOB44Hzpd03GhTbBxtd0PX5vxtzg7OX5vzD2JeDP7AS4FtETEREY8BfwGcOdoID422\nu6Frc/42Zwfnr835BzFfBv8jgQc65rfnNjMz2wPmy+A/Dw45mqgdoNBE7QAFJmoHKDRRO0ChidoB\nCk3UDlBookqv8+JQT0k/CayIiNPz/GXA9yPiHR3L1A9qZtZCMx3qOV8G/wXAPwOnAF8B1gPnR8QX\nqgYzM9tLLagdACAiHpd0KfA3wL7A1R74zcz2nHmx5W9mZqM1X3b4mpnZCI3t4J9PLGutNueXdELt\nDONM0qG1M5Ro82d/PhnbwR/YKukPJB1fO8iA2pz/vZL+UdIySQfVDtMvSW+SdEjtHAXWSfpLST8r\naY9d4GwPavNnH0l/KOlHa+cY58H/RcBW4CpJd0v6b5KeWTtUH1qbPyJeAbweeB5wj6TrJZ1WOVY/\nFgH/KOnGfE2qtg2gPwK8H/hFYJuk35f0/MqZ+tHaz372BeB9ktZL+u/VNoAiYuz/gCXADuC7wGrg\nh2tnGof8NEebnUNzeO8XaA73fV3tXD1m34fmWlR/AWwDVgI/VDvXAO/j5Pzv/zDwCeCnamfqM38r\nP/s5+7HAKuDLwHXAq0fZ/9hu+UtaIOlMSTcD7wbeCfwgcCtwW9VwPWhzfkk/JuldNAP+ycBrI+I4\n4NXAu6qG61FEfB/YCewC/h04BPiIpD+oGqwHkp4l6c2SNgC/BlwKPAv4VZpBaF5r82d/Ut5vcSxw\nHPA14LPAWyXdMLIQtb/9Kn7r/gvwAWbY0gH+qHa+vTk/zRbmLwJPm+G5X6ydr4f8bwY2AHcA5wJP\nye37AF+sna+H/FuA3wKeM8Nzy2vn6yF/az/7OeO7aH4tvg946bTn/nlUOcb2OH9JB0bEt2rnGFTb\n87eZpLcDH4iI+2d47viI2FQhVs8k7RPNL5dWavtnX9IbgBsi4jszPHdwRIzkMp/jPPgfAFxMc/+A\nA3JzRMTeaCB9AAAMtUlEQVQb6qXqXZvz552LK4EfBZ6amyMifrBeqv5J+gF25ycivlwxTs9y7v/B\nk//9T66Xqndt/uxPykeLLeaJn59PjjLD2Nb8gQ/RHLVxOs2tdJ4DfLtmoD61Of8HgT8FHqPZYbca\n+HDNQP2QdIakrcCXaEpYE8DtVUP158PAZuAYYAVN/s9UzNOvNn/2kfRG4JM0ZcO301zWZsXIg9Su\nf1Wsu23Mj5/Lj08B7q6daxzyA/fkx/umt7XhD/gczQ7Se/P8q2nKQNWz9fnv/7mOts/UztVH/tZ+\n9nPef6L5xTL5Po4F/u+oc4zzlv//y48P5zNODwYOq5inX23O/2/5aIdtki6V9J+Ap9cO1YfHIuLr\nwD6S9o2Iu4CfqB2qD5OfnZ2SXivpxTRHK7VFmz/7AP8WEd8DkPTUiNhMc+7FSM2Lq3pW8n5JC4H/\nBdwCPAP4zbqR+tLm/G8Bnga8Cfgd4JnAhVUT9eebkg4EPgV8WNK/0qKyA/B7kg6mObTzj2j+/X+l\nbqS+tPmzD/BArvnfDKyV9E0q3NFlbHf4mg1K0jOA79HsM3s9zeD54Yj4RtVg1jqSltB8ftZExP+b\nY/Hh9j1ug7+kX+2YDUB03EYyIv5w5KH60Ob8km7tmJ3MPjlNRJwx8lBjRNIfdczO9O//ppGH6kOb\nP/sA+dfKrCLiwVFlgfEs+xxI84H5EeAlND8bBbyW5g5i812b878zP54NPBv4c5rs59OcKTuvSfo2\ns99vOiJivl9fZkN+/CmawyRvoPn3/3ng87VC9aHNn32Ae9j9pfU84Ju5/RDgfpqjr0Zm7Lb8J0n6\nFPCzkU8WyTXc2yLilXWT9abN+SVtiIgT52qbryT9Ls31cP48N70eOCIiWlF3lnQ38IqIeCzPPwX4\ndEScVDdZb9r82QeQ9H6ao3tuy/P/ATg7Iv7rKHOM89E+P0BznPmkx3JbW7Q5/9Mk/dDkjKQfpNkB\n3BZnRMSfRMQj+e+9wJm1Q/XhYJo686QDc1tbtPmzD/CyyYEfICJup/k1NlLjWPaZdC2wXtJHaX6G\nnUVzslFbtDn/rwB3SfpSnj8aGOlWT6HvSPoF4Po8v5R2He2ziuZS2nfRfHZ+mhonGQ2uzZ99gK9I\n+l/sLnv+Z5ork47U2JZ9ACSdCLySpg73yYi4t3KkvrQ5v6Sn0pzcEsDmiHi0cqSeSToGuJLdW2t/\nB7w5IiaqheqTpMOBk2j+/e+OiJ2VI/Wl5Z/9hTRftpNlqk8Cbx/1Dt9xH/z3pdnxuIDdRzy04vos\n0N78ks6lObTtEUm/Cfw48LsRcU/laGNB0suBz0bEtyVdQPPvf2XMcKG6+UTSM/NnZvKomelHK410\n8ByEpAXA6oh4fe0sY1vzl/TLNEeYrAX+Cvjr/NcKLc//m/k/8SuAU2guz/unlTP1LN9C8JmSniLp\nTklfz4NoW/wp8F1JPwa8FfgiTSllvpsss91Dc+TSZ/Lf5PS8FxGPA0dJ2r92lrHd8pf0RZprabfy\nxJw255e0MSJeJGkVzfV9Pizp3oj48drZeiHpsxHxY5LOpjnM8K3ApyLihZWj9WTy31rS5cCOiLhK\n0j0R8eLa2eYiScBz2/ALdzaSPkRT8ryF5g5k0BwqPNLzFMZ5h++XgUdqhyjQ5vw7JL0PeA2wKtf/\n2/QrdPL/zWuBj0TEw5LatBX1LUm/AfwC8MpcPnxK5Uz9uA14Qe0QBb6Y//ahuTTFE05WG5VxHvy/\nRHPEyV+z+0JRI//2LdDm/OcCPwP8QUQ8lHc+/nrlTP24VdJm4N+AS/L18f+tcqZ+nEtzbsIbImKn\npOcB8/72k9B8wCVtkPTSiGjDiV1PEhErameA8S77rMiTk/8Aovlsvb1Oov7sBflfSXOz7Q9KOgw4\nMCL+pXauXuWdjg9HxL9LejpN/nl/xEze4bg2Il5dO8ugJP0z8MM0Z8VO3g0rWlR2u2uG5ogR30xn\nbAf/vUU+u5Fo0W3t8hfXicCPRMTzJR0J3BgRL6+brDd5sH8r8LyIeKOkxTTv5a8qR+uJpDuB18WI\nbhc4LJKeFxFflnQ0T7w2EQBtOdRWUuflv58KvA54PCJG+ut3bMs+8+Xbd1D5OubXAofm+a8BF0bE\nP1UN1puzaQ4v3AAQETsmv8Ra4oM02SeP8/8K8BGao67a4DvAfZLu4Ik7HOf1hd2AjwE/HhETkm6K\niNfVDjSIiJh+ZNKnJf3jqHOM7eDPE2vMU9++lbIM4n3AW/ONRCYvDfs+KpwmPoBHI+L7zYEbU1vS\nbfJDEXGupKUAEfGdyffSEh/Nf53aVgJo1f2eO027uuc+NDcCGvlFAcd28J8v374FnjY58ANERGrR\nIPqXkv4MOFjSfwXeAFxVOVM/HlVzE3EA8nWKWnOGckRcUzvDmJu8uic0G5wTNDekH6mxHfzny7dv\ngS/ls2M/RFP7fD3Qih2mEfEHkk4DvgU8n+akr7WVY/VjBbAGeI6k64CXAxfVDNSPjmsqdYqImO9b\n0y+UNLlv64COaWjHJbUnHRsRTzg6LB/uPFJju8NX0gRP/vZ9e0R8ulamfuQvr7fTDDzQ3FJwRUR8\nc/ZX2bBIehbwk3l2XTT39G2FnH3SU4FzgEPbcknqtpvphLoaJ9mN3Za/pJcCD0TE0Xn+Ipp6/wSw\nqVqwPuXrmPxy7RyD0BNvirIfzQlG327RlhvA/jQ341gAHC+JiPhk5Uw9meGL6t2S7qFd98FtnXw+\nyxE0lzR/MbtP7nomFS5pPnaDP/BnNNeTQdKrgN8HLqU5+uR9NFtB85aaWyE+6TC3LKIFt0KMiGdM\nTkvaBziD3VvR856kdwDn0Wws/HvHU60Y/PMVMSe/fCdLnvvWSzQ2TqMpDx7J7rvaQVP+/I1Rhxm7\nss/kdVny9P8BvjZ5xl3nc/NVPqRzO81Fru6ebM6PERGfqBKsB5KeMnn3qBme2xgRLxp1pkFI2gKc\n0KbLUHeSlHhyyfN/R8Q/18o0TiSdExEfqZ1jHLf89+0YhE7liTcRacO/x+E018Q5P//9NXB9RLTh\nHqx3Ay+W1Hl89j40J3x9r06kgXyRplzVysE/IpbUzjDOIuIjkl5Lcx/lp3a0//Yoc7RhsBu264FP\nSPo6zQkunwLIZ2nO+zMe8yVhbwduz5eFPZ/m/ayIiD+um25Ok79QXtvRNrnl2abbIH4P2JjPlJ38\nAmjDSVLA1JElr6O5g9q+7L40yEgHn3GVD3M+ADgZeD/w8+z+FT+6HONW9gGQ9DKam6DcERHfyW3P\nB57RhhuK5P+8/5Hm9oFH01wa9gMRMfJbwfVD0nbgD5l9f0UbLko3eZDAdBERrbiVoKS/odnQ2UDH\nPouIeOesL7KhkXRfRJwg6XMR8UJJz6C5udErRpljHLf8iYh/mKFtS40s/crXAv9Rmsva/nZE3Fc5\nUj/2pblZeKvtBSdJHRkRP1M7xBibLHF+N1/X6hs0G6MjNZaDf8u9nubaLG8G3jztsgLz/USXnW25\n6uhMJHX7om3NVSWBv5f0woj4XO0gY+pWSYfQXEZ7A83O95Gf4e7Bv2Uiok03Pdnb/Fx+XJYfO8+u\nnvckfR74Ps0vsF/KZ/p27rNoy5dXK3WcY/Q7ef4ZwH3AZuDdI88zjjV/q0PSodHC205ON9NhqW24\nDaWkbwIvYuZ9Lq25JHJbSboXOCUiHsznGN3A7nOMjo2IkZ5j5C1/G5m9YeDPJOkVk5cCkfRyZhlQ\n55mJiLi/dogxtk8+Mx+akwT/LCJuAm6S9NlRh/Hgb9a/NwAflHRQnn8I+KWKeXp1mKS30vKjrVps\nXp1j5MHfrE8RsYHmCpMH0ZRO5/35IdlecbRVi82rc4xc8zfrk6RnA79Hc8jk6ZKOB14WEVdXjtZV\nG/ZL7O3m0zlGHvzN+iRpDc2tHP9nPknnKcC9EfGCytG68uBvnXzYoFn/nhURN5DPjs013DbcAvTU\n2gFs/vDgb9a/b3feEEXSTwIPV8zTk73oaCsbApd9zHok6VeAv8uz7wJeAHweOAw4JyJGfrie2aA8\n+Jv1SNI7gZcBxwFfAHbQHLFxfUR8rWY2s3558DfrU76U9k/QfBH8VH58KCKOqxrMrA8+zt+sfwfQ\n3Hf1oPz3FcAXSbNW8Za/WY8kvZ/m7kvfAtYD/wCsi4hvVg1mNgAf7WPWu+cB+wM7aer9O2jB3d/M\nZuItf7M+SNqH5mY6k/X+E2huxrEuIn6rZjazfnjwNxuApOfSDP4vp7kn8aERcVD3V5nNHx78zXok\n6c3sPrrnceDvaY77/3vgnyLi37u83Gxe8dE+Zr07GrgR+JWI+ErlLGZFvOVvZjaGfLSPmdkY8uBv\nZjaGPPibmY0hD/5mZmPo/wPvTuRXINs+5wAAAABJRU5ErkJggg==\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x116e67438>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "weekday_plot.plot(\"bar\")\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "People apparently seem to log fewer complaints on the weekend. This seems like a reasonable conclusion. It might be because they interact with the finance companies more often during the weekdays in the first place. The reporting system seems to be online, so this is the best explination I have. People still might assume that their claim will be processed faster during the weekday, or a host of other possible reasons."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.4.3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}

From 756691f8cfdb63d66ec5e781b2d43da8a30c218d Mon Sep 17 00:00:00 2001
From: Alan R <alan.rominger@gmail.com>
Date: Wed, 27 May 2015 10:09:11 -0400
Subject: [PATCH 2/2] half of hard mode

---
 Consumer Complaints.ipynb | 673 +++++++++++++++++++++++++++++++++++---
 state_abrv.tsv            |  52 +++
 2 files changed, 678 insertions(+), 47 deletions(-)
 create mode 100644 state_abrv.tsv

diff --git a/Consumer Complaints.ipynb b/Consumer Complaints.ipynb
index 5557bde..f410b5c 100644
--- a/Consumer Complaints.ipynb	
+++ b/Consumer Complaints.ipynb	
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 72,
+   "execution_count": 118,
    "metadata": {
     "collapsed": true
    },
@@ -23,7 +23,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 73,
+   "execution_count": 119,
    "metadata": {
     "collapsed": false
    },
@@ -35,7 +35,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 74,
+   "execution_count": 120,
    "metadata": {
     "collapsed": false
    },
@@ -147,7 +147,7 @@
        "2                NaN  "
       ]
      },
-     "execution_count": 74,
+     "execution_count": 120,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -158,7 +158,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 75,
+   "execution_count": 121,
    "metadata": {
     "collapsed": false
    },
@@ -195,7 +195,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 76,
+   "execution_count": 122,
    "metadata": {
     "collapsed": false
    },
@@ -210,7 +210,7 @@
        "      dtype='object')"
       ]
      },
-     "execution_count": 76,
+     "execution_count": 122,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -221,7 +221,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 77,
+   "execution_count": 123,
    "metadata": {
     "collapsed": false
    },
@@ -257,7 +257,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 78,
+   "execution_count": 124,
    "metadata": {
     "collapsed": true
    },
@@ -268,7 +268,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 79,
+   "execution_count": 125,
    "metadata": {
     "collapsed": false
    },
@@ -283,7 +283,7 @@
        "Name: Product, dtype: object"
       ]
      },
-     "execution_count": 79,
+     "execution_count": 125,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -294,7 +294,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 80,
+   "execution_count": 126,
    "metadata": {
     "collapsed": false
    },
@@ -305,7 +305,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 81,
+   "execution_count": 127,
    "metadata": {
     "collapsed": false
    },
@@ -360,7 +360,7 @@
        "2012-04-30      5725"
       ]
      },
-     "execution_count": 81,
+     "execution_count": 127,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -371,7 +371,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 84,
+   "execution_count": 128,
    "metadata": {
     "collapsed": false
    },
@@ -383,7 +383,7 @@
        "Name: 2015-05-31 00:00:00, dtype: int64"
       ]
      },
-     "execution_count": 84,
+     "execution_count": 128,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -394,7 +394,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 85,
+   "execution_count": 129,
    "metadata": {
     "collapsed": false
    },
@@ -405,7 +405,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 86,
+   "execution_count": 130,
    "metadata": {
     "collapsed": false
    },
@@ -450,7 +450,7 @@
        "2015-04-30     13442"
       ]
      },
-     "execution_count": 86,
+     "execution_count": 130,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -461,7 +461,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 87,
+   "execution_count": 131,
    "metadata": {
     "collapsed": false
    },
@@ -470,7 +470,7 @@
      "data": {
       "image/png": 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RVKo+t719G2TsGGE4gqB/ckTVPcDy1elGguFLS+s4Ktge23aJSkbRMdFBT0If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\npCe6R725AAAAAElFTkSuQmCC\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x106e660b8>"
+       "<matplotlib.figure.Figure at 0x1068a3be0>"
       ]
      },
      "metadata": {},
@@ -500,7 +500,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 89,
+   "execution_count": 132,
    "metadata": {
     "collapsed": true
    },
@@ -511,7 +511,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 97,
+   "execution_count": 133,
    "metadata": {
     "collapsed": false
    },
@@ -520,7 +520,7 @@
      "data": {
       "image/png": 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2L1NHUp8kjWkja7IMhUkb4XQSZcAhpBlZD4UHgEZloT5pq5xuyaA0YUFVx5lH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\nGrxeVUOJjsuYqiQySX+BlxCrUvG80Eh3NNxNVdu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tWJI2yeIUIKyqT8caVHW5qs4XkZNF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\nGGOMSVL/D01u4s7njCPvAAAAAElFTkSuQmCC\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x105c31b70>"
+       "<matplotlib.figure.Figure at 0x10268cc50>"
       ]
      },
      "metadata": {},
@@ -535,7 +535,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 98,
+   "execution_count": 134,
    "metadata": {
     "collapsed": false
    },
@@ -544,7 +544,7 @@
      "data": {
       "image/png": 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cmC87EPhlfn0esK+k5SStD2wAzLR9F/CIpG0liWRozi28p1XXXsAlI2lrEARB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\n0ZOiEBERPSkKERHRk6IQERE9/wIGf6Bh0Lt8wwAAAABJRU5ErkJggg==\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x107823358>"
+       "<matplotlib.figure.Figure at 0x1047f37b8>"
       ]
      },
      "metadata": {},
@@ -573,7 +573,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 101,
+   "execution_count": 135,
    "metadata": {
     "collapsed": false
    },
@@ -593,7 +593,7 @@
        "dtype: int64"
       ]
      },
-     "execution_count": 101,
+     "execution_count": 135,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -604,7 +604,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 103,
+   "execution_count": 136,
    "metadata": {
     "collapsed": false
    },
@@ -613,7 +613,7 @@
      "data": {
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CoJ9sKn9JW0m6Q9JdkvatrtBXgxU5aORgQy4aOdiQi0YONuSikYMNuWi0Xz6L\nyl/SROBnwFbAusDOkl5dTWVWDZbkoJGDDblo5GBDLho52JCLRg425KLRfvksKn9gU+BuM5ttZi8A\nvwW2qSbxVA1m5KCRgw25aORgQy4aOdiQi0YONuSi0X75XCr/VYAHCutz0rYgCIJgFMil8q8h5Gh2\n5xJZaORgQy4aOdiQi0YONuSikYMNuWi0Xz6LUE9JmwPTzWyrtL4/8JKZHVLYZ/wNDYIg6EJahXrm\nUvlPAv4GbAk8BFwD7Gxmt4+rYUEQBD1KFjN5mdlcSZ8HzgcmAsdFxR8EQTB6ZNHyD4IgCMaWXDp8\ngyAIgjEkC7dPu0h6LT4obGFSxJCZnVhRY0Vgk1T+GjN7tG47S9gwEViBwv/DzO4fazuakbSgmf13\nDI+3MPAhYAoD58LM7MAKGisC3wNWMbOtJK0LvMHMjqtoyxRgLTO7SNIiwCQze6ZC+VcAhwFvwK+t\nK4Evmtn/jVDuiGG+NjPbq8SxJwOLN1/Lkl4GPGtm/xpJo1BmbzM7fKRtI2isaWb3Nm3bxMyuHaHc\nPsDTZnZs0/Zp+O87rKwNhbJL4Ofx2apl60DSwmb276Zty5jZEyXKTgT2MrND67Cla1v+kqYDPwWO\nAKYCPwC2rqixA3A18GFgB+AaSR+uqLGopG9IOiatry3p/RXK7wk8AlwEnFP4VLFhWotth7TadxiN\nSyWtWVjfFLiuosaHUnqOZyQ9mz6lK0zgLPx/+ALwz/R5rooNwAzgAmDltH4X8MUqApI+DZwOHJ02\nrQr8vqIdvwFOA1ZKtpwOnFKi3Ez8vM8c4lOGnwJbtNj+ZuAnJTUa7NZi2ycqavxO0qqNFUlvBY4v\nUW4XoFVj7iRgnmt+OCRtIulm4GbgFkk3Snp9RY1fS1qqsD5F0p+raABnSFqgoLESfu+PiJm9CHyk\n4vGGFezKD3AL3jl8Y1pfAbioosZNwMsK68sDN1XUOA3YF7g1rS/asKlk+XuAZTs8F38CPlpY/znw\nq4oa7wbuAD4HHATcAGxUUeMe4NWd/E9ruC6uS39vKGybVVHjRmChJo2bq15brXQ7/X0lj339MN/d\nVlJjZ+AP+BDSPxQ+fcDFFe3ZBH+grQi8N53f1do5h+1eK3ilv0Vh/c1t3Ov/g0clvg/4NHAn8IGK\nGp/CGxIT8Tfcm4B3VSh/KJ4KZwtgo8anneukm90+/zKzFyXNlbQk8CiwWkUNAY8V1h9P26rwCjPb\nQdJOAGZRyCvkAAAgAElEQVT2nFRJ4n6gSuu4FR8Ezpb0IvAe4Ekz272KgJmdL+mzwIX4OdnQzB6u\naMfD1lmU1pWS1jezmzrQ+KekZRsraQzJ0xU1/mNm/2n8H1MoctXIiD+l8SqN1v6OadsyADbEa76k\nw81sb0l/aPG1mVmZt9tFhvmu7Nv+lcDf8QbRjxi4L57FK+/SmNm1kvbCr61/Ae+0cu5VSVqx+TqU\ntALV/x9zzezygk1XSJpbRcDMjpZ0G/Bn4B94pfv3ihrHSFoIf8tdA/iMmf2lgsSG+G9vdoW+rYod\n0N0+/2slLQ0cg7cqnsMv2CqcB5wv6Tf4xb0j3oquwn+SjxXo9/X+p0L5e4FLJJ0DNPzrZmYjvp43\nKpLEJ/EL6grg22X9iAWtb+C/fwtgfeBSSfuY2R/LagDXSToVOJPBv+WMkuW3AD4h6V4GzqGZ2foV\nbNgHb6G+XNKVeOW1fYXy4L/968Aikt4J7JE0q7AjfpN+eojtLx+iXMPN8eOKxyvyqKTNzOzq4sbk\nyivVp2Vm9wH3AZu3a0SLB9hk/E3iuJRjfqQH2Q+Bc5Lvv+Hyen3aXvX8XCrpaAY/jC+VtBGAmV0/\nkoCkXYFvAh/D75FzJX3CzEbMrpZ+A/j/XnhD9UZg8/S/KuWOM7OpZfYrQ0+EeiZf9RJmVqlFIm/a\nfRB/BTTgcjOr5NuV9C7g63jH84XAm4DdzOySkuWnp8XGP0J4hfftEmVnM7gFpOK6ma3ZXGYYrcOA\n/S11BkpaAzjWzN5ZQWNG49DF7WZWykecOlmL5ZXKzy5rQ9JZAHhVWv2bebLAKuUn4j7ld6VN5+Pn\notTNImkC3slcpUVXG6mSPw3v/5iJn8eNgY8DO5nZVRW0PgQcjLtVG61/M7MlSpSdOtz3ZtZXQuM9\nwP7AemnTrcD3zaxSI01SH8PfKyO2nCWdCXy68daSzvMvzWyDEmWnD3H80vd70qkloAG6uPKXtB1w\niZk9ldaXAqaa2ZnjYMtyDLSQrjKzf4y1Db2CpA3wN4DGw7jSAz1pvImBiKG2osA6RdKsMpXCMOVf\nife9rIdHs4FXEkO9MTSXXwHvvylWmj8r6W4p6twDvL9Dd15PIWkRM3s+LY91RNx5eGf5181s/dTQ\nucHMXlNZq4sr/xvN7HVN2yrdcJJahXs9DVwL7GMjhOUljTfjHYr/TK+FGwKHp9fmMja8DPgq/ubQ\ncB+Zmb29TPmCzhsZHCJZqcIr2NFc2ZS2Q9KrgCOBFc1sPUnrA1ub2XdLlt8b7xA7A28RbQscY2Y/\nrWDDr3GXyizgxcZ2M9uzgsbNDLTKGjSui++a2eMlNH4EXAX8ruwbQ1P5vwDfwqNzPoBH2Ew0s29U\n1WrSPdXMdqxih5m9qcNjtvX2IGl5/AH2BPAr3N3zFuBu/P68u4IN36LQ0m5st2phxG8EjsXDTFdL\nDZVPm9keFTReBXyZecOZS91nkq4zs9dLusHMNkzb2mpodLPPv1Wv6sSKGofjqaQbfsCdgFfgkS6/\nwkNIR+Io4HWSXgd8Cb84TgTeWtKGk4FTgffj0QS7MbgTekSGqvBoHSY3anbg/S9fAX6R1m/Gz22p\nyh/vt9jMzJ4DkHQwXoGWrvxx98a67VS4Bc4D5uLhmsKvi0XwkNwZeGU8Ep/Br4cXJTXiuku5SxKT\nzccYKDUkpku6Huio8gfeWHH/TvtxwMOw23l7+A3+wH0lnu9rBn4tvBm/z6ZW0HqOgUp/Mn6d31bR\nnsPwCafOAjCzWfKw1SqcjtcZxzJwr1a5VusIaEhHHeWws9H64K8+P8Er67XwEKgZFTVahePNSn9L\nheWRwgHxVton0/KQoXYtyl/fbAspXLGCxu2kt7gOzmcddnQUZok/LCYX1idTPcTydGDlDs/FDUNt\nq2pPBzZciTdmfg98Hu+b+lsNug9U3H9G+hxf/FTU+EubtjbCuAXc3/RdpfDdFtoLAZdWLHNN8/VR\ntp4o7D+zQ7s3TtfG0+nvXcDr2tHq5pb/nngr6NS0fiH+iliF5yXtiFcY4FEh/a20khrPSvoa8FFg\ni9RZuMAIZYo0WlMPyweHPQQsXaE8+JiHlVLZdqnDjsckrdVYkbQ9Hi5YluOBqyUV3T6/qmjD8sBt\nkq5hcMRQlQGAE4vRMqljrxEiWTo8UNI2uJvC8IqmSsTQ3vjbxl7Ad4Al8A7bMsfdmNbXr6h2bWJm\nu1XZfwjafXt4qbGjpGZXW6f+6kWpPmHU/ak/CUkL4v+bqm8zf5D0Ody12R8VaCUj88xspqS3AOvg\n/8+/WZt9Dl3r86+DFJZ5OIXOWuALwIPAxmZ2RQmNlfBRd9eY2eWSVgfeZmYnlLThA8DleOjXEfhN\nPt3Mzq7wO/qADfBX47YqvFThX9GhHa8Afom7Fp7Ew1h3sQrROqniKkZf3VC2bCo/NS0WffZmZpdW\n0NgEfxAtljY9i0f/3Aq8z8xOK6FxMD646WQGXEfXmdn+JW3Yofk4rbYNUbaPYSpHKxHZUtDqqB8n\nacxoHLrJjmGjwCQ9DVyKn78t8PukwRZmtlTLgq21bi6sTgBeBhxoZsOl02jWWB6vL96RbLoAT7cw\nYh9QQWM2Lf43VjIyT9JN+DS3p5rZPWWP21Kr2yp/1TMIphHOd4iZfbleC8eeoULqrFwo3SFmtm/Z\niqWkPYvinZOlBq9JWsLMntHAuIX+ShvKt4qS1svxTmvDR7OO2Gk/jNZSfnir7FNNlc0G5kPyG9fb\nLDN7bcny/R16w21rw67NrVqo52Wkfhwz21CS8NG1641QtGPqCBUtaE1pFMPf3h61iiHAOZB+x454\nOhrDHwSnWRu5wLqx8t84vfq8lXk7fau28K7CY2TbPgmS3oB3Qr0a9yNOBP5pI0cy7Gtmh6h1Ii+z\nEgm86kDSLcBrcZ9/pxXLPfjb0+V4q/3WkuXOMbP3ddIqkifsOhYfBNQYdLMBHuc+reyDqKD3fgaS\nBjbsqBIZchP+Bvh4Wl8WD00edsCaPK79vfgN/lsGrvHF8Y7sTav8jhb695vZ6hX27zi6RD4IchoD\nEW2Nh3qlUejJ1bIe8KC1kYBRHYYRp4bFnswbqVM1p9hrmPfaqhyKLGlt3PW9i5lVDXbpPp9/qvgn\nAf9jZp0mOZoFnCXpdOD5gUNUimT4Gf5Kfxpe8XyMgQFGw9GINGhOnjYoFK0M7T6AEn/CXTSLtQh9\ntZIaDdYDNsPdNj+Sx6rfbGbbDlfIzN6X/k6pcKxmjsDP6U5m9hLQGGx1AP4/+lhZIflI0MnA2/EI\npg/jCQCr8H3gekmX4P/TtwL7lSj3EP7A2oaBAVqGu54qJagbgqrpSzrtxwFPxHY7Hinzbbx/bERf\nefo/HGFmt8hTuFyFt9qXlfRlM/tNWQNahBH/WlKlMGK8z+JYfLT3S2lb1Xt1On4trIcncHwP7m6t\nEpY9hYHW/4t4iHZ12uklzuGTTthCHWrMoPNIhpnpbzFKplQkAl5J/7iGczETWBsPUZ2Ix4QfXFHj\n7BrsmIT7+/fDL+yrgKMraqySNN7S+JQsd3c73w2x/83F/ynu+7+ijfOxMl6Jb437zKuUXQDv8F2n\n0/9Lk27VaJ9XABfjOXkeAv4CTKmo0Yiga5zPBYCrS5S7rbD8BeDMtLxi2Xus+D8FFi2sL0r1SLJr\najj/HSWkxBshN+Cjnl/eiS1d1/IvcC9whaSzGdxqL52y1uqJZHhOnqjpRkk/AB6mZOvKPDHdm1Is\nd0f+NzO7S9JEcx/z8ZJmUa6l2Shf6dV1CJ7Bb7Kf4OkQKo10lqeh3hFvwRfHK1xWonid/stGvvvn\nJa2CJ/xbsYqABkagn5XWl5K0rZUfgf4efFDTQsAUSRsC3y7zfxqiP6zBssN8Nw/mnYpbpn6cCdZe\nHvxGNMrT8jk4HsajskaimCPrXaSoPDN7WNWSJzZ4aYjlshyRWu7nMzhSZ8S8QAU6TUj5cTO7o8L+\nQ9LNlf896TOBgaiMStTki/xYsuHz+Gv5qviEJGWpw/XU9gNIaQSnpH8ybwVqVs3tszPuU90D+JQ8\nsdplZlYqXzmwHfAqM6uSGK/BXyV9E/hO40GaOicPAP5aUeuP8qSBP2QgodgxFTWmWyFPlJk9lSqO\nspX/dNyFdkkqf0PyOZdhuKRnPyojIGlXMztJnpDMCtsbuWiqzAtwTOrMPwA4G79fywxWezpFwz2I\nvw1OSzYsQMFfXpI6wojXA3bFM2gWHx5VMmp2mpDyYUmH4m/F4Cm2D7R2ghI6bHCOO5IWtTQitI2y\n/4v7Hneh4Iu0MepsTTbMSIuVwuCaNKbgo08XxB9ASwBHWoXh73UiaR280/IL+HwJpW5USX8Cdmin\ndZlaUcfh+c2LHb434B2+T1XVTLoLAwtXLS/pJmvq3JV0s5WP9rnazDZr6midR3O0kPQ/5imMp9O6\nE75UIrIObXgV3pe1InComc1I27fC00LvM0zxos4EfEa1f9NZGHFjvopacvmojYSU6eF1M3AC/hDb\nFVjfzD5Y+fjdWvlr3jwbr8M7gavk2ZhlZhs0bqrUorjCzDaroPFmfHTvFAZHAJRtpdVCavkXM1lW\naj3LxyfMg1UIIZP0O7zCvQd31VyO+0lLTRuYLuzX4T7m4niF0g/j1Dm5Ln6D397OA1Cei6b5xnga\n9xGXijKRdDzekf5z/Cb9HLB0WVejpF/h52E/fHTvXsACZvaZMuXrQtLLyv7mFmUbHd1PmNlN8gGV\njdw8R7b5htcWVSOUhtA4E69jHmmz/CTgRTOzdL9tCtxT5SGk1jnN5tlWhm52+zTn2bhR1fNstOuL\nLHIc3sK9nsF+6lKonkE078Pz6TRi2l+eWm7nVjDlXAYqvIWBNfFZi6rEc38f74irNElGgbPTp0il\n1kmq7Dt949kdbylektan4v/fNSUdaOXC8jodgb4nnir8P3h+pPPxkb5jzRXyENxTgTPM7MkKZX+O\nhxEvLOlvuLvnPLz1/Sv8jXtI5GHQjcF6xUF7UD0c+qIUqdRWor3E0sAdkq6l4mBKSZ8CDsFz83wH\nHztxPbChpOPN7OCSNvxL0haWJqZJjc/nRyjTmk56i8fzQz15Nj4FLIO3Tu7FE5l9pqLGiFELI5S/\nDPftNnLHiDQlZAWNv+GTjTfW16LDPDC4++S4imU+j7duG+tLA3uM97XSxm+/AFihsL5C2rZs1f9N\njTatDhw1TsfeDM+d9X/AH4FdS5a7PV3Pk/HMnJPS9sZAsZHK74antNgNn1imsbwb3vFZ5Tf8E/fT\nv4CHzT4LPFNRY2r6vDX9/Sblp8W8Ld0Pa+CV9XJp+yJlNdL+G+BTPzYm25lFm7l9xvxCqvGC/F98\n4pQbcF/3l4Hflix7UGG59PyZTRobp8/BeMfgG2hjTk3qmXP22qZ1NW9r8zdWnSd1nodvmd+C+zCL\nn5vwqfIOwP3tY31t3d7ifN7e/H8aQeNVeKfehfgbxCXAn0uUWxePI78NHzuyKp5S4D7gSx3+roPw\n+abbmjMaWA6P2X+p5P43tFquch7b3X8Ur42N0v1+H97Zumcb5+LGob6rYMeSwJKd/JZudvt8Fr8p\nVsGjAS6g/Gv1e4CvpeVDUtmq/JjBLonXN31fNgKg7UE0yTcNnjjrXLyyAB+U1Dx4bCStYufZBPwi\nf7CKBjBB0gQbGGRVNsldqxTJy+AtvSPwN7Rh0eApLefBKqSIYGBazdPwiv9DQF8Kdyzb8dtu6t7j\ngKPxMRJb4Q/DY/EoqH8PV7AE1+Jx+4fhHYUjkjrSt8NDcNfCs4xuUvJ4y0v6En4Oi8tQ3b3aFsnP\nPtlSEIE8BfKC6esbrERwQXLN7oyfg8fw/62s2pSKk+VTRgpYKC3DwJtRKSR9H09L05jEaml8boMD\nKtjiWukpMl/RFEHRcb6UDm1pOxlaihRq/APVvGzVIoamF8rPBWbj/tHSFY58ApM18P4H4fMC3G8l\nozKG0CzVUachUkM0sGpTWjYq/MYkJn+hoq9Y0kwz27js/oVyg36vpP+zMQ4eaLLnXrxf7VR8lroq\n52A6ra9PoFrEULv3qaQf43l8Dknr9+IDrRbGU5rsW0LjJdzd9XlLARCS7q14TfUx/Lko1VhsdT+0\nfW66tfJXB3k2JM3BByIJD41sLDc0ykyevg/wlDXNnSlpGh6BdFjJn9Io18kgmiyQtAg+IctU/OK+\nAB/sVbkjvKDZViRDJygluxtp2wga0/FWYqXUvZLuwLPEgl+TJ6f1xgO99ICipg5T0vLTuKvxrJIa\n/W9yY40Gjz2ZzMDgOyg5BkU+2HETS0ncGhVlesBfYSVmKZO0Ld7y3wzvsD4d7w+bUuX31IE8Z9Sm\njUaZfKzSddZGor1urvxvwl+Hb6GQZ8NKJHaro0Uin1Vpc2uK+ZUnn5pp5eO5l8NDRfvjj/FBG2Wm\nCqwtOZx8VGhzRVF8IA75UE0hst/Do2TuT+VWwwfWfM1GyJ6o1vnnl8HHXTxrFaZgTHpL4+kuiomz\nyowSbpRvlVGzdIx+2n82bSSpUw0TjRe0jsH7Hk5nwH11L35u/8/MvlBCo5ZpRscLNY2NkPQuM7sg\nLVdqWEhaDE/XsTPu1j0R+H1DbyyQtC+eLuRX+P/0E3hqlkOqanWzz//fVi0pUz9mNr2G409qrviT\n9n9Tq6Isv8Vzln8Q/2d+BH/FfkeJso3kcDMZpsIoyb14VMuvU/md8YFjvx+uUOKHeBjfmgXf6hJ4\nv8iP8IlJhqO5/8TwlAp9uEusNCmkbi/84XMDPlfDX/EkbSOV/Sw+OvkVGpz/fXHc9VOadluFFf3I\nI7E+8CZLobeSjsRzYr0Z70soQx3Te44nCyilDAcoVPxL4qkzSmNm/8TPx8mpj2l7fBzGmFX+qbF3\nE7Bl2nSgmZ3frlhXfvAOq+m0GWVTw/FvpkWyLrwCLZ0wihYRNVXKp/13KLNtBI15ppdrtW2Isnfj\nLqvm7ROpmFSthv/LLXgLtZFMbB28dVam7JK4G/EUvO9iSvq0Gx3zGjzz4scanzE+F38DliqsLwXc\nmZbLRi11PL3neH7weZTPBdYobJuCZ7P98njb18bvacyVAf5WtzU++K+yVmNqum5kPTwK5GC85dj4\njBU/BM6RNFXS4unzNjybZRU7LpC0s6QJ6bMj1VsSrWaHKjVjVIFFUucz0N+nskjJsi9ZC7+wua+/\ntL9Y0t6SlpBznKQbJL27bPnEvy2NKJa0sHkSrDIptjHPjzIHb0TcZ2az06f0TE0NkmvxCDyd9Nvw\nSczrSJ5XhR8AN0iakYIDbgB+mPqXyuZbGjS9Z4pSKTW9p6R9JH2yxfZpkkZ0OdWBef/d2cDlkp6Q\n9AQ+tuZsMyuV56hOJF1cZtswXI5HC62CD/zbFc9MXJ3xfpJ18AS8B1hwnG14D34hPZ4+lwHvqajR\nGHwyN31eouQglHT8I/DMgD9Ny0eki6FS+lk8rPB+3AV1KR7H/O6SZc+ixaCbdGGWThXNQMrfd+Pu\nptdQPR78TLxymp5ulLOBcytqnEWhpdjmtdFR6t4ar9GV8SRm29DGxPZ4GO5S+EjdPnxU6tYly17f\n6h7FQy0rvd3WdC6WwHPpjOlx07En44MEb8L7XBqfKcAdFXQag0H3BL6alisNbm18utnnfzN+k7eV\nZwMgtT6Ox1MRH4u7jvazkj40M/sT/vrYNmbWVkbSRKuJP8B/T6WJP8zsPPnkK+vgPve/Wfkwz88B\nZ0janYEsmBvjbw7bVTCjYf/7gJPMJ/GoUBxsYOKY6anzdAk8QqMKywC3yieBbyQNNKuW9rqt1L1D\ndH73Y9XSB4Of08fw/r21JK1lFTq/bWDS+afwKK4q1NUvVgtWcTa3mvkfvO9rZQbuEfBG3s+qCMkn\nb9qFlOUU2vPgdHPl33aejQK7m9lhybWwDN5SPQl/nRoTJE2zQriofFDK161ExJF5NsAbJZ1sbc5H\nKumrZvaDtPoBMzu98N1BZva1IYoW7ZgjaTO8U7Uxf+45ZlbldRZgpqQLgJcD+6dO40phhpJOMrNd\nk119jW2UHNSUaKQbHjIirATtpu5t7vxupkq0T9vzI0j61hBfGYCVm9JSklY0s4ebNq5A9fPZ1ZiH\nfh8maU+rMGl8C76Au3R/b2a3JlftJe0IdXOo59QWm82qzeF7s5m9VtJPgT4zO6PdARPtIukUvKPx\nk/gD6Hg8B/6IA6MknW5mH26KTGlgViL9r4YZ8DYO52IiKSuoef77ZYFVzOymChrNv2ES7k5at6It\nK+IjWQ13obWV2TJpVU7dWweS7gRea21kz5T0ZeatoBfFW5vLmdmiJTQ+hrd292Ggtft6vL/sZ5ZS\nNM9PSNoB+JOZPSvpG8CGwHfbeKPrmK5t+TdadQ0kbYGHJ5au/KmhpdkpZrazpJ1wX+Bz+OjeK0oW\n/6k8q19zeoTVqD7P6riT3CSPAOumSrt0i1vS1/AW0WQNnov4BaqHi+6AV1CNa+lnkr5SfCsaoXxz\n6t6N8T6qSsgzzb6a9if6vgf3r1eu/K3QGZrui73wmPLfUjKgwcxOlPQYcCAD2WFvBb6RXKajjgbS\nc7dyM5lVmzSpDr5hZqel+3ZLPBT6F3h65yGRdLiZ7a3Ws7RV9XgAXVz5A6TIg53xcLp7gd9VlNgd\nf/LeY2bPpZZm6ZQIyYaF8cEzUxg80rjMazHJz74XPhL01cBHU+u1zAQ1+wH7W1MqiHSzHkrrnDnZ\n0ombwswOAg6SdLCZlZ6+cggOwEeFPprsWh7PrT9i5a+aUveqhom+8RGxs1I0SeX5EdL98EXcv3wi\nHgVVJaVzLf1iHfIBhm9AjHXl37iu3w8cY2Z/TNfJSDT+760evG25b7qu8lcNSZaaOtUMz38P7fl2\nz8I7w2biMwVV5Ww8Z8hF8hmHvogn4CrjplihlUvEfOKMsnlH1i+0lJtbzaUTTtVE29M4SlrHPKzz\ndA0kzeqn4mt1o5O0weO0bjm24ot48rQl8JTGq5vZP+SpL67DQ5PLsD0+sc31ZvaJ5Cc/uWTZBm3P\njyDP07Qd/ta0vrU3u1qx36B59HjZfoOOsHrm6a6TByX9EngncHBqPI7YYWtmM9PfvtQYwcw6GmzX\ndT5/1Z9kaR6s2hD6W8zsNWX3b1F+SWuaf1PSK83szhJl7zaztap+lyvqbBrHY8zsU0P9byv+T3+I\nV7y/wSusHfF+g6+WKFvsQxmUPqBKH4qka81sE0kz8Y70Z/CQwFJjFjol3Wf/xd1mzZiVy6vTcb9B\nnUh6P96oKrrRRv0B1GTDonhY9U1mdpeklfB+mWHH9qToqG/hc2ZMTJtfBI4oExzSiq5r+eNpEHYG\nLpPUSLJUKWysyltCCa6UtH6VTkkYiLIxs6clfbjJn7wbAymnh+M6SZ82s0E+7eR6mDlEmZxp201h\nZp9Kf6fWYMdX8euskW/paCtMxj4CtaTuxf+3bU30XUcggJl1PAC0jn6DupB0NH7+346f0w8DV4+l\nDYll8f9noz8I4I4S5b6IZ5ndxMzuhf6BmL+Q9CUrkYyyma5r+TdQB0mW1HqO1n6qdAJJuh3Pc34v\ngyusYW+wOqJsUkTK7/EWWjG+fiFgOzPrqk5fSbu12GxmdkIFjcl4fp5ioryjrPNc+GWP30cNqXub\nNCtFC0la2cwekjSl1ffNfUSjSYt+g8Oq9hvUZEcjsq8xX/diwHlm9uYxtuMWBq6J/ulSbYSsnPLs\npO9sdvUkF9CF1sb8xN3Y8gc6TrJUZyfQeyrsWytm9rB8Ivu34aNhDfijmf15vGzqhJpC/07EXSQ/\nhf5EeSfhLb1hSf0dw0WGjOjqqOutUtLFZrZl0ry3edsINjzUkAEetoF0F5PxkcZjQh39BjXSSAf9\nvDw1wuPAimNtRLOLOL0ZlpmEalIrH7+ZPZaiyyrTtZV/EfMc6b+kZEhfnZ1AjVaUPPXtwsPvXT/m\nr25/Tp+uJkU+HcS86YOrTGayng2O6f+zpNuG3HswFwMr4VFjp5rZfRWOWwupgl4En/mqODvZEvis\ndVX4XzzxYYOX0rbmWedGiy/hb6UHAAdo8KDeUg/TGvljcqP9kIG35GPG8PgtMbPr5QMkR2K4QZxt\nDfDsicq/XZLb5Hv4QKKtJK0LvMGaJmgZQWNr3H+5Mj6Efw08ymOkyRVyirLJhePxTq2f4KkEPsFA\n51ZZrpf0BjP7K4B82r5S/R9mtq2kpXB//y9TJMZpwClWbRrITqgtDQCe/bE/vYKZ/Uc+98KYUEe/\nQY38ILn+fiefonNh2ovO6wi1P13q+k11RJG26ouu8/nLMzXW8k9LHcbH4+kU1k83xg1VonfkubXf\njvvdNpRn9tzVzHavw8b5CUnXm9lGKkyc0thWQeMO4JXAA7gLZ3U8tfFcSnZ2Jp0JeH/S4cBB7XSo\ndYI6TwOApIvwaJCz0vo2wF5lXEd1kN5iPoOHvt6Mz341dyyO3cKWea6jqtdWTXYUw1/bmi61Lrqx\n5X8lsJGkX5vZRzvUWs7MTpW0H4CZvSCp6sX5gnkc9wRJE83sEkmHd2jX/Mq/5Ske7pb0eTxxXdVw\nwK06MUDSm4CdgLfgg6q2M7PLO9GsePy3pz6bhyR9sPn7KsEIeMV7sqTGG8McquU46pQTcLfPFcB7\ncXfeSBP71EoKpVwZT1neiMIy3I1WNmV5XbZMxDvu257Tuk66sfJfSNIuwBvTzVF0JFrFm+OfKRoB\n6HcRPD3M/q14UtLieFTJyZIexdM0B9XZG78h9wK+g9+gH68iMFQfjKUxIcMh6T7gSXzmqk/hcdTW\nCNe0DvOvlIzieivefzNUUELp69vM7gY2S5EtjSCJseTVhTe4Y/HBi2PNu/FraBUGh5c+S7lw6tow\nT1/yJkmyDFwu3ej22QIPG/sw845exMxKp2eQj/Q9AvfP3wosD2xfNqQuaSyGRxJMSHYtAZxsbUwA\nMj+TWkWHmNmXO9Rp2QczUihdKtuXFlveFO2EaY4HknY1s5OSf3me6T3HyoXVbgjzKNnyITOrmv6l\nzhHF5qMAABOcSURBVONPMrO5kn6BX5unA8+nr6s2Wmuh61r+6RX8cknXmdmx7WhI+iI+J+v1+Ov9\nq/Ab405rkX98BHsarakXaXdGnfmcwo3x5hpaRd/FI1wG9cGUKVhXmGYRScvh19h9loboVyj3LQaP\nVziwZKOi4c5YnPFNndzcSVkMbBiTaJ/GgxCYIulLxa8YwwchcA3eubsw8ATzzikdlX8FTpS0N35j\ngc8y9Asrl9d+VeAwPJHaTfiD4Ercx1wpqmOIHvin8Vfcfczs/6rozac0boxZwFmSOmkVjWsfTIok\n2dd8IpqV8KkTr8UnhT/GzA4tKfVbPKtow7X5Edwd9Y6RCprZ0WnxSOsgFXWnmFnVSK3RYKgHYTt5\nvDpBkFeuoa5z+zSQdBz+8DoBP7G7AnPNbJ45Q4fRWAiPeX4D8Mb09ykze3UFje/ikSWnpE074dEN\nNwCfGY3WZK/RcAfI55ltlZeniivvInxg0feB5XDXz+vN7I01mTvS8W9tuJjkaabXMbOPpX6hKxs+\n8BI68+SMKkZBldS4E48mORU4w8ZhZG3gSJqDhzAP6qNk7N9A+unmlv8mTWF7F6ewyypMxn30S6bP\nQ/ibQBW2brLjl5Jmmdm+kqpOoj6/snx6JW+Vi6Yq2+Dx242UAksApRNfyUcirWpmD7R5/OKb5ztI\nA4nMJ++oMlfEBZJ2xitu8D6uMqPX+zGzV6YBRDsBX0+D3U5NbpD5CvmMV4fhDTzD3/S/OIZv5hPx\nt49s6ObKf658PtK7of+fWypMU9IxeNjZs7jL4UrgJ222jJ6XtCMDud63Z2DwSHe+Vo09Hd8YktbG\nU1w3JsJ5EZghnzRjKXw4f1n+hKfLaIc5kvbEB+5sSJo/WJ7Sucr99ml8yr5GRT0BeE7Sp6ngLzez\nq4GrJX0Pn+PhhILm/MRv8EFyjfDZHfG39TKja+vgYWsz++Zo0c2V/1fwofv3pvUplJ+IZXU8+dld\n+E36IJ6Tvx12wQcC/TytX4VPyDIZT78ajEwdN8Zh+ExezTyTvis1sY2ZmaSZkjY1s2vasGMaPnPV\nO4AdCw2KzfABhaUws8XaOPYg5BPHb4dXdGvhSQA36VS3S5nc9Mbza0lfGTdrMqBrff7go33xSB3D\nI3VKj5JLIzjXY8Df/1q8dXiVmX2zpEYt4YnzO3WEAKbor5Y5a1r5z0fQ+hteWd6Hp1KGCqOD60Ke\ni2ZtBo9XGHFWs0L5e/HJhk7Fr+vuvdk7RD5L3FMM9M3tCCwN/AD684ON5vGXbURqpXpjBQqN7zLj\nUGq3aT6+HgCQtBpe+b8Jn1ptWTNbskL5q/B8QPP3ieyA4o3RgUZtE9tolFIhS/qfQiTOSPt+Ch/s\nthoePLA58Fczaw4RHKr8RDyfTRajSccbSbMZ2g1rVi15YCd27ImH8D5KYarSKh35ddHNbp+2SSGi\njeieubjP/y/AccAtFeXqCE+cr6lpQFxtE9sMNUp4jNkbd9H81czeJmkdPIKpFLmNJh1vzGzKeNuQ\n+AI+Vem4DwLtqcq/woU+Bc/W+EUbyH3eLtkM2pjP+QLw+5T6Y56JbaoIDTVKmJEztQ5L2VZ/4t9m\n9i9JjWSGd8jnr65CNEwKSHoN807jeOLQJUaF+/F+qHGna90+kr5jZt8orE8ETjKzj4yjWcE4ksI0\nixPb3GptTGyjDjK1anDKXpIdjwFXWJqUpaQNvwd2x98AtsRzDk0ys/dW0JhRsGHAoArjJnoFSdPx\nvEnrAefgkzBdYWbbj7Edv8Kzzp6DJ72DcYrz7+bKfwY+/dn302Ct0/B0zNPH2I7V8FmjGtPBXQbs\nbWZzxtKOoD4kzTSzjSXdCGyUXCg3lenwTZVM8021LJ5gbLqZnTJPoZE1p+LjFc6ziulHAkc+feLr\ngOvN7HWSVsBzcI04YrpmO6anxUFTfY5HGGg3V/4T8GkcG620cysMna/TjouSHb9Om3YBdjGzd461\nLUE9jMYoYfmsXBePFNUkaVM81fi5TdvfCzxi1fIDvQo4EljRzNaTtD4+KPG71X9BdyPpWjPbRNJM\nvL54BrjDzKq60nqGrqv85Zk4G0YvAByNd9geC52n3W3DnhvN7HUjbQu6B0mL4gP1as3UWiakVdIl\nwCeaI4tSBNLxViGzqKTL8PEwv0juKwG3WIkMp72GpCOBr+MhnvvgIbw3jLULLP1/m7GyUVx10o0d\nvj9m8Gv1U3iCtkau7rFOu/u4pF3xEYTCh9L/Y4xtCOrlm2a2L4VMrSlOfN92BVO/QZkR5Iu3Cik1\ns9nyTJ9VWMTMrlaaOzcNYGtrvtdux8z2SIu/kHQ+fp6rpnKpg+LAsoWBD1EyM0HddF3lb/klStsd\nnxOg0WFzJeVHGgd58i7mrejf22LbPEhqlZ9oaeDvwMdKHHupYb6rOlfrY5L6xzdI2j7ZMd8gaSu8\nom+kX8HM7pW0vaQVzOzCsbTHzK5r2nSFpPGY5Kb73D4N0ujeD+FhmxMZ6Dg5cDztCroXSZ8F9sCz\nst5T+Gpx4C9mtksJjSlNmwx43ErOoiXpaPzN8YBG2HLq3/o2nrvo02V0UrlXAL/Ex7Q8CdyL90fN\nLqvR7Ui6EtjWmlJbS1oe+IOZbT7G9ixTWJ2AZxU+fDz6Hrq58j8fd/nMZPBIuR8PWaje4x/BQErW\nZszM9hoLO4L6SLlwlgYOxlv5jf/tM6M9/L9gw2J4/9WmeJw+eJTKdcAnzazV/BEjaS4KTGinbLfT\niNwa4rtKKbJrsmc2A27rxgTu37aBhIRjZ0sXV/6V8rWMwvFfwEcDn4angoaBysLM7IRxMSzomOQq\nmWNm/06++tcCJ5pZu8n/2rHhFXhMugG3mdk9IxQplt0auKkwUvlb+FvybDwMufR4g25HPqfBetY0\nyZOkBfDzuvb4WDb+TBhvAzrgyhS6Nl6shL9SvwufSGZB4EwzmxEVf9fzv6SU4Xg02Wp4h/6YYWb3\nmNnZZvaHKhV/4nt4eCqS3g98FO+HOhv4Rb2WZs8Z+Bwb/VlS5RPrHM0YjsKXtKl8ZrfG+sclnS3p\np02uoDGjmyv/LYCZku6UdHP6jFnvvZn9w8yOSqF3u+GTwdyWIn+C7sbMbC6e+/0IM/sK/rDvFl4y\ns0Y6hw8Cx5nZTPM5r182jnaNB98AHgFmS7pe0vV438djwAFjaMfRwH8AJL0Fdy2egI83+OUw5UaN\nrov2KfCe8TYA+scd7AS8E58EpFISsSBL/ivpI3h0TmMegAXG0Z6qKLVun8NTQxxV+G68EtWNC8nd\ns5+kA/E03QB3Fx6OY8WEQr/RjsDRZvY74HdpJPmY07UtfzObnXyazwMvFT5jgqTvpNGCX8Qn2t7E\nzKaZ2W1jZUMwauyOZ3z9XgoLfDkDI7hHFUlvLyyv2fTdB+ct0ZLD8DTQM4HbzezaVH4jBvqn5ivM\n7Hkzuyl9xrriB5iY+hnAJ/opDvYal0Z4N3f4tsy8OFajF+Xzsd7LQLbEIlYmD0wQNFMcBdw8IrjM\nCOHCvqviLp5ZZvZS2rYSsICNw8Qh8zuSvg68Dw/jXQ3Y2Mxekk8/OsPM3jTWNnWz2+e7eOtsUObF\nMTz+yxmcnCnoEeTz/n4LH0PSuEfMxmjCjzpIiQXnNG2brwZ45YSZfU/Sn4EVgQsaD2S87thzPGzq\n5sr/BTP7h6QJkiaa2SWSDh/D498HbIv7EW8ys/PH8NjB6HIcPj/A9RTGkATdSxootwuwppkdKGl1\nPOFdO/M0t4WZ/bXFtjvH6vjNdHPl/2Tq1LocOFnSo0CpUZQ1cSQ+McSVwHckbRaji3uGp8zsT+N0\n7JdLOhtvEa4p6Q+F79YcokwwMkfifYJvBw7E64oj8RG28yXd7PNfDPgXNWderHD8W4H1zXO9L4JP\nDLHRWBw7GF0kHYynDDmDFJ4HY5MxNuXuHwozs0sr6m0BrGVmx6eUBovNT4O8GjT6S5r6VObr7Ltd\n2/Iv5Ep5UdI5eP6UMYv2Af5rZi8mW55XI3Vi0AtsjvfnNLcKRz1jrJn11aUlnzhkY+BVwPH4QMRf\nA2PeuZgB/5XP9gf05/YZy/oiO7qu8pf0BnySjSfwTt8T8Qk3Jkj6+Bi+rq/TlMFxrcJ6RPt0MeOZ\nOVbStsCqZvaztH4NsHz6+qvF7JQl2A7YkDT2xMweTK7S+ZEjgN8DL5N0ELA9YzvIKzu6rvIHfgbs\nj4+o/TOwlZldJWkd4Lf4QKuxYJ0xOk4wxkhaCo/2eUva1AccaGZPj8Hhv4oPGmywIP4Gsig+t0CV\nyv8/KZwQ6E/wNt+ROnvvxZP1bZk2b2Nmt4+fVeNPN1b+E83sAgBJB5rZVQBmdoeksezAuGWY7/4j\n6W48Le9FY2VQUBu/Am4GPox3vO6Ku03KDrLqhAWb4vCvSP1Yj7dReZ+eUkQvJenT+OC1Y+sytFtI\nD8Cfm9kGwHxd4Rfpxsq/WMH/e9yMMBvy9VnSJDwj42/S36C7eIXZ/7d3N7F2lVUYx/+PNo29pBXQ\nysRoFYVEE4JFY4IYBAIDJVhMGBhiNFFqDU2Vj4AfITZGHfjBzJAYBkYlqI1NlYmkCGlQY42AqDXK\nxI8BaTRYU1NIgfZx8L6Hu3vvacmtt+fdZ+/nl5ycs/fOOV2drO6u/b5ruZvod85wC/453QPb2zuH\nG1kB21+XdA3wX+AC4C7PeHhJjzxUh9n8eDInYezmMflfJGnSl3xd5zOsfNLRGVGbgj1Ze/7H/HlO\n0nttPwovbfqaVUuA/ZK22j6h2ZekbcD+0/i9pyjPoPZKWpC0fox9/YFtwK2UBSKTm0bb3tAwpqbm\ndqlnxJki6WLKQoJX11OHgI/aPuN3/5LOA/ZQlphOlpZupjRk22L74Ap+aytwE3Cu7fMlXQDcY/uq\nl/lqjECSf8RJSNoAYPvwjP9cUTYjTYa5HLD98Gn8zpOUiWC/7qxtn/n0qr6Q9EHKQ3wD+2w/8DJf\nGbR5LPtEnBGSPmL7e5Juo/NsqSZj2757FnHUmvTP6+v/cdT20c5qnzWc+MxsNOrGvXcB91Ee4u+Q\ndKntz7WNrJ0k/4hFC/V9PcNIkvtqN8kFSVdThtOP9W73A8DFk42Zkr5DmZE82uSfsk/EEpIu85KB\n2tPO9V1d3/4JyqhRgAeBe8e42qVO+bti0v5F0muAR8a8GTPJP2KJaX3zJT0+T72baonnj7azGRGQ\n9GHK6MRHKGWfy4HP2v5B08AaStknoqqtQy4FNkq6lcU5Despjd7mhu0XJf1F0htt/711PK3Zvl/S\nPkrd38CdK1k5NURJ/hGL1rKY6Lub+A5TesHMBUkfsr0bOBc4UPsDHamXbfu6dtG1Iel6SpnnJ/X4\nbElbbO9pHFozKftELCFpk8t86LnUaV/8vmnXV7Nz6LyY1r5Z0u9qy4dRyp1/xHLPSvoGZVjPZNe4\nbV95iu/0zhiT/ClMa7k+V6W81ZbkH7HcfcAPgWuBTwIfA/7VMqAVunBJu/GusbYbf0zS3cC3KP8Q\n3ExtdT1WKftELDFZ2SPp95NEKem3tudi5F+dMvd+pt/tMs8lrdNVJ//dxWJL573Al20fOfm3hi13\n/hHLPV/fD0q6FniaJd02e+75rPA5UZ38d2frOPokyT9iua/UgS63USZAbQBuaRvSivyydQB9I+lC\n4HZgE4t5b+6e46ymlH0iYvDqDt97KJ1Sj9XTtj3aun+Sf0Ql6YsnuWQA21+aYTixiiQ9ZvuS1nH0\nSZJ/RCXpdpY3dDsL+DjwWtujnIE7BJJ2UlZs7abMSgDA9r9bxdRakn/EFLWX/w5K4v8R8E3b/2wb\n1cpJeg/L69zfbRdRG5L+xpROrbbfNPto+iEPfCM6arfHW4AbKdO8Nts+1Daq0yPp+8CbKa2Lj3Uu\njS75297UOoa+SfKPqOqu3uuBbwMXDWDW7SXA28bYwnlC0h22v1Y/32B7V+faV21/vl10baXsE1FJ\nOk5Z4//ClMtzN+xb0i7g07afbh1LK9323EtbdU9r3T0mufOPqGy/onUMq2wj8Kfa1XPykHOUXT1j\nuST/iOHaWd/NYquH/Fc/gJR9IgZN0ibgLbYfkrQArLF9uG1UsyPpGPBsPVwHPNe5vM72aG+AR/sX\njxg6SVuBmyhDXc4HXk/Z5XrVqb43JLZH3bb5VIZW44yIRTcDl1EmkWH7KeB1TSOK3kjyjxiuo7Zf\n2s1ah7qnzhtAkn/EkO2T9AVgQdLVwC7ggcYxRU/kgW/EQEl6JaU9xTX11IPAvWPe9BWLkvwjBqyu\n8HmD7T+3jiX6JWWfiIGSdB3wBPCzevwOST9tG1X0RZJ/xHDtBN4NHAKw/QSl0VtEkn/EgL1g+z9L\nzh1vEkn0TjZ5RQzXAUk3AmskvZUyn+BXjWOKnsidf8RwbQfeTmnqdj9ls9dnmkYUvZHVPhEDVDd0\n7bV9RetYop9y5x8xQLZfBI5LOrt1LNFPqflHDNcR4A+S9tbPUPr572gYU/REkn/EcO2ur67UeQNI\nzT8iYpRS848YGElbJG3vHP9G0l/r64aWsUV/JPlHDM8dQLeNw1rgncDlwKeaRBS9k5p/xPCstf2P\nzvEvbD8DPCPprFZBRb/kzj9ieM7pHtje3jncOONYoqeS/COGZ3+d33sCSduA/Q3iiR7Kap+IgZF0\nHrCH0tbh8Xp6M/AqYIvtg61ii/5I8o8YIEkCrqT09jFwwPbDbaOKPknyj4gYodT8IyJGKMk/ImKE\nkvwjIkYoyT8iYoT+B4Gu9SykoxK7AAAAAElFTkSuQmCC\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x116f48be0>"
+       "<matplotlib.figure.Figure at 0x1068e6550>"
       ]
      },
      "metadata": {},
@@ -642,7 +642,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 107,
+   "execution_count": 137,
    "metadata": {
     "collapsed": false
    },
@@ -661,7 +661,7 @@
        "dtype: int64"
       ]
      },
-     "execution_count": 107,
+     "execution_count": 137,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -679,7 +679,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 109,
+   "execution_count": 138,
    "metadata": {
     "collapsed": false
    },
@@ -688,7 +688,7 @@
      "data": {
       "image/png": 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G/LvtrzCinJl9VPmdpOfb/i5UF7MB/1Nzpn7eChwPPEnSL4CbqQZLG8X2aZJW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\nRIxLoxAREePSKERExLj/HwGVD9eRg3FQAAAAAElFTkSuQmCC\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x117171eb8>"
+       "<matplotlib.figure.Figure at 0x1068bc128>"
       ]
      },
      "metadata": {},
@@ -702,7 +702,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 110,
+   "execution_count": 139,
    "metadata": {
     "collapsed": false
    },
@@ -711,7 +711,7 @@
      "data": {
       "image/png": 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lUiu98koVz4POndEe3Ql6u8Qa69nTJdSan/n5taYRNUBWFvTu7W6bIGzi+yw5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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x116e92518>"
+       "<matplotlib.figure.Figure at 0x107636d30>"
       ]
      },
      "metadata": {},
@@ -741,7 +741,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 112,
+   "execution_count": 140,
    "metadata": {
     "collapsed": true
    },
@@ -752,7 +752,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 114,
+   "execution_count": 141,
    "metadata": {
     "collapsed": true
    },
@@ -763,7 +763,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 115,
+   "execution_count": 142,
    "metadata": {
     "collapsed": true
    },
@@ -774,7 +774,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 118,
+   "execution_count": 143,
    "metadata": {
     "collapsed": false
    },
@@ -801,7 +801,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 120,
+   "execution_count": 144,
    "metadata": {
     "collapsed": false
    },
@@ -819,7 +819,7 @@
        "dtype: int64"
       ]
      },
-     "execution_count": 120,
+     "execution_count": 144,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -830,7 +830,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 122,
+   "execution_count": 145,
    "metadata": {
     "collapsed": true
    },
@@ -841,7 +841,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 123,
+   "execution_count": 146,
    "metadata": {
     "collapsed": false
    },
@@ -852,7 +852,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 124,
+   "execution_count": 147,
    "metadata": {
     "collapsed": false
    },
@@ -878,7 +878,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 127,
+   "execution_count": 148,
    "metadata": {
     "collapsed": false
    },
@@ -887,7 +887,7 @@
      "data": {
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UagcolKr06sHfzGwMueY/eKKxqhv2vXbX/Lv14Pzd1u78c/Xgmr+ZmQ3Gg/+U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\nZjaGPPibmY0hD/5mZmPo/wPvTuRXINs+5wAAAABJRU5ErkJggg==\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x116e67438>"
+       "<matplotlib.figure.Figure at 0x10764db38>"
       ]
      },
      "metadata": {},
@@ -915,6 +915,585 @@
    "outputs": [],
    "source": []
   },
+  {
+   "cell_type": "code",
+   "execution_count": 149,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "table with row headers in column A and column headers in rows 3 through 4. (leading dots indicate sub-parts),,,,,,\n",
+      "\n",
+      "\"Table 1. Annual Estimates of the Population for the United States, Regions, States, and Puerto Rico: April 1, 2010 to July 1, 2013\",,,,,,\n",
+      "\n",
+      "Geographic Area,\"April 1, 2010\",,Population Estimate (as of July 1),,,\n",
+      "\n",
+      ",Census,Estimates Base,2010,2011,2012,2013\n",
+      "\n",
+      "United States,\"308,745,538\",\"308,747,716\",\"309,326,295\",\"311,582,564\",\"313,873,685\",\"316,128,839\"\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "with open(\"State_population.csv\") as file:\n",
+    "    for i in range(5):\n",
+    "        print(file.readline())"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 150,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "pop = pd.read_csv(\"State_population.csv\", header=3, skipfooter=7, engine=\"python\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 151,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Unnamed: 0</th>\n",
+       "      <th>Census</th>\n",
+       "      <th>Estimates Base</th>\n",
+       "      <th>2010</th>\n",
+       "      <th>2011</th>\n",
+       "      <th>2012</th>\n",
+       "      <th>2013</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>United States</td>\n",
+       "      <td>308,745,538</td>\n",
+       "      <td>308,747,716</td>\n",
+       "      <td>309,326,295</td>\n",
+       "      <td>311,582,564</td>\n",
+       "      <td>313,873,685</td>\n",
+       "      <td>316,128,839</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>Northeast</td>\n",
+       "      <td>55,317,240</td>\n",
+       "      <td>55,317,261</td>\n",
+       "      <td>55,376,322</td>\n",
+       "      <td>55,598,499</td>\n",
+       "      <td>55,771,792</td>\n",
+       "      <td>55,943,073</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>Midwest</td>\n",
+       "      <td>66,927,001</td>\n",
+       "      <td>66,927,549</td>\n",
+       "      <td>66,976,321</td>\n",
+       "      <td>67,146,663</td>\n",
+       "      <td>67,321,425</td>\n",
+       "      <td>67,547,890</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>South</td>\n",
+       "      <td>114,555,744</td>\n",
+       "      <td>114,557,273</td>\n",
+       "      <td>114,857,899</td>\n",
+       "      <td>116,032,322</td>\n",
+       "      <td>117,253,992</td>\n",
+       "      <td>118,383,453</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>West</td>\n",
+       "      <td>71,945,553</td>\n",
+       "      <td>71,945,633</td>\n",
+       "      <td>72,115,753</td>\n",
+       "      <td>72,805,080</td>\n",
+       "      <td>73,526,476</td>\n",
+       "      <td>74,254,423</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      Unnamed: 0       Census Estimates Base         2010         2011  \\\n",
+       "0  United States  308,745,538    308,747,716  309,326,295  311,582,564   \n",
+       "1      Northeast   55,317,240     55,317,261   55,376,322   55,598,499   \n",
+       "2        Midwest   66,927,001     66,927,549   66,976,321   67,146,663   \n",
+       "3          South  114,555,744    114,557,273  114,857,899  116,032,322   \n",
+       "4           West   71,945,553     71,945,633   72,115,753   72,805,080   \n",
+       "\n",
+       "          2012         2013  \n",
+       "0  313,873,685  316,128,839  \n",
+       "1   55,771,792   55,943,073  \n",
+       "2   67,321,425   67,547,890  \n",
+       "3  117,253,992  118,383,453  \n",
+       "4   73,526,476   74,254,423  "
+      ]
+     },
+     "execution_count": 151,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "pop.ix[:4]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 152,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Index(['Unnamed: 0', 'Census', 'Estimates Base', '2010', '2011', '2012',\n",
+       "       '2013'],\n",
+       "      dtype='object')"
+      ]
+     },
+     "execution_count": 152,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "pop.columns"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 153,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "pop.columns = [\"State\", \"Census\", \"Base\", 2010, 2011, 2012, 2013]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 154,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Index(['State', 'Census', 'Base', 2010, 2011, 2012, 2013], dtype='object')"
+      ]
+     },
+     "execution_count": 154,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "pop.columns"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 155,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "pop.index = pop[\"State\"]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 156,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>State</th>\n",
+       "      <th>Census</th>\n",
+       "      <th>Base</th>\n",
+       "      <th>2010</th>\n",
+       "      <th>2011</th>\n",
+       "      <th>2012</th>\n",
+       "      <th>2013</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>State</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>.Virginia</th>\n",
+       "      <td>.Virginia</td>\n",
+       "      <td>8,001,024</td>\n",
+       "      <td>8,001,031</td>\n",
+       "      <td>8,024,417</td>\n",
+       "      <td>8,105,850</td>\n",
+       "      <td>8,186,628</td>\n",
+       "      <td>8,260,405</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>.Washington</th>\n",
+       "      <td>.Washington</td>\n",
+       "      <td>6,724,540</td>\n",
+       "      <td>6,724,543</td>\n",
+       "      <td>6,742,256</td>\n",
+       "      <td>6,821,481</td>\n",
+       "      <td>6,895,318</td>\n",
+       "      <td>6,971,406</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>.West Virginia</th>\n",
+       "      <td>.West Virginia</td>\n",
+       "      <td>1,852,994</td>\n",
+       "      <td>1,852,999</td>\n",
+       "      <td>1,854,146</td>\n",
+       "      <td>1,855,184</td>\n",
+       "      <td>1,856,680</td>\n",
+       "      <td>1,854,304</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>.Wisconsin</th>\n",
+       "      <td>.Wisconsin</td>\n",
+       "      <td>5,686,986</td>\n",
+       "      <td>5,686,983</td>\n",
+       "      <td>5,689,060</td>\n",
+       "      <td>5,708,785</td>\n",
+       "      <td>5,724,554</td>\n",
+       "      <td>5,742,713</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>.Wyoming</th>\n",
+       "      <td>.Wyoming</td>\n",
+       "      <td>563,626</td>\n",
+       "      <td>563,626</td>\n",
+       "      <td>564,222</td>\n",
+       "      <td>567,329</td>\n",
+       "      <td>576,626</td>\n",
+       "      <td>582,658</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                         State     Census       Base       2010       2011  \\\n",
+       "State                                                                        \n",
+       ".Virginia            .Virginia  8,001,024  8,001,031  8,024,417  8,105,850   \n",
+       ".Washington        .Washington  6,724,540  6,724,543  6,742,256  6,821,481   \n",
+       ".West Virginia  .West Virginia  1,852,994  1,852,999  1,854,146  1,855,184   \n",
+       ".Wisconsin          .Wisconsin  5,686,986  5,686,983  5,689,060  5,708,785   \n",
+       ".Wyoming              .Wyoming    563,626    563,626    564,222    567,329   \n",
+       "\n",
+       "                     2012       2013  \n",
+       "State                                 \n",
+       ".Virginia       8,186,628  8,260,405  \n",
+       ".Washington     6,895,318  6,971,406  \n",
+       ".West Virginia  1,856,680  1,854,304  \n",
+       ".Wisconsin      5,724,554  5,742,713  \n",
+       ".Wyoming          576,626    582,658  "
+      ]
+     },
+     "execution_count": 156,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "pop.tail()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 157,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'.Arkansas'"
+      ]
+     },
+     "execution_count": 157,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "pop.index[8]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 158,
+   "metadata": {
+    "collapsed": false,
+    "scrolled": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "2959373"
+      ]
+     },
+     "execution_count": 158,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "int(pop[2013]['.Arkansas'].replace(\",\",\"\"))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 159,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "names = pd.read_csv(\"State_abrv.tsv\", sep=\"\\t\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 160,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>State</th>\n",
+       "      <th>junk1</th>\n",
+       "      <th>junk2</th>\n",
+       "      <th>code</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>Alabama</td>\n",
+       "      <td>State</td>\n",
+       "      <td>US-AL</td>\n",
+       "      <td>AL</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>Alaska</td>\n",
+       "      <td>State</td>\n",
+       "      <td>US-AK</td>\n",
+       "      <td>AK</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>Arizona</td>\n",
+       "      <td>State</td>\n",
+       "      <td>US-AZ</td>\n",
+       "      <td>AZ</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>Arkansas</td>\n",
+       "      <td>State</td>\n",
+       "      <td>US-AR</td>\n",
+       "      <td>AR</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>California</td>\n",
+       "      <td>State</td>\n",
+       "      <td>US-CA</td>\n",
+       "      <td>CA</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "        State  junk1  junk2 code\n",
+       "0     Alabama  State  US-AL   AL\n",
+       "1      Alaska  State  US-AK   AK\n",
+       "2     Arizona  State  US-AZ   AZ\n",
+       "3    Arkansas  State  US-AR   AR\n",
+       "4  California  State  US-CA   CA"
+      ]
+     },
+     "execution_count": 160,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "names.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 161,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      ".Alabama4833722 .Alaska735132 .Arizona6626624 .Arkansas2959373 .California38332521 .Colorado5268367 .Connecticut3596080 .Delaware925749 .District of Columbia646449 .Florida19552860 .Georgia9992167 .Hawaii1404054 .Idaho1612136 .Illinois12882135 .Indiana6570902 .Iowa3090416 .Kansas2893957 .Kentucky4395295 .Louisiana4625470 .Maine1328302 .Maryland5928814 .Massachusetts6692824 .Michigan9895622 .Minnesota5420380 .Mississippi2991207 .Missouri6044171 .Montana1015165 .Nebraska1868516 .Nevada2790136 .New Hampshire1323459 .New Jersey8899339 .New Mexico2085287 .New York19651127 .North Carolina9848060 .North Dakota723393 .Ohio11570808 .Oklahoma3850568 .Oregon3930065 .Pennsylvania12773801 .Rhode Island1051511 .South Carolina4774839 .South Dakota844877 .Tennessee6495978 .Texas26448193 .Utah2900872 .Vermont626630 .Virginia8260405 .Washington6971406 .West Virginia1854304 .Wisconsin5742713 "
+     ]
+    }
+   ],
+   "source": [
+    "for i in range(50):\n",
+    "    s = names[\"State\"][i]\n",
+    "    c = names[\"code\"][i]\n",
+    "    print(\".\"+s+str(int(pop[2013][\".\"+s].replace(\",\",\"\")))+\" \", end=\"\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 163,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Date received\n",
+       "2015-05-19    IN\n",
+       "2015-05-19    GA\n",
+       "2015-05-19    WA\n",
+       "2015-05-19    IA\n",
+       "2015-05-19    FL\n",
+       "Name: State, dtype: object"
+      ]
+     },
+     "execution_count": 163,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "complaints[\"State\"].head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 164,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "complaints.index = complaints[\"State\"]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": []
+  },
   {
    "cell_type": "code",
    "execution_count": null,
diff --git a/state_abrv.tsv b/state_abrv.tsv
new file mode 100644
index 0000000..358d3aa
--- /dev/null
+++ b/state_abrv.tsv
@@ -0,0 +1,52 @@
+State	junk1	junk2	code
+Alabama	State	US-AL	AL
+Alaska	State	US-AK	AK
+Arizona	State	US-AZ	AZ
+Arkansas	State	US-AR	AR
+California	State	US-CA	CA
+Colorado	State	US-CO	CO
+Connecticut	State	US-CT	CT
+Delaware	State	US-DE	DE
+District of Columbia	Federal district	US-DC	DC
+Florida	State	US-FL	FL
+Georgia	State	US-GA	GA
+Hawaii	State	US-HI	HI
+Idaho	State	US-ID	ID
+Illinois	State	US-IL	IL
+Indiana	State	US-IN	IN
+Iowa	State	US-IA	IA
+Kansas	State	US-KS	KS
+Kentucky	State (Commonwealth)	US-KY	KY
+Louisiana	State	US-LA	LA
+Maine	State	US-ME	ME
+Maryland	State	US-MD	MD
+Massachusetts	State (Commonwealth)	US-MA	MA
+Michigan	State	US-MI	MI
+Minnesota	State	US-MN	MN
+Mississippi	State	US-MS	MS
+Missouri	State	US-MO	MO
+Montana	State	US-MT	MT
+Nebraska	State	US-NE	NE
+Nevada	State	US-NV	NV
+New Hampshire	State	US-NH	NH
+New Jersey	State	US-NJ	NJ
+New Mexico	State	US-NM	NM
+New York	State	US-NY	NY
+North Carolina	State	US-NC	NC
+North Dakota	State	US-ND	ND
+Ohio	State	US-OH	OH
+Oklahoma	State	US-OK	OK
+Oregon	State	US-OR	OR
+Pennsylvania	State (Commonwealth)	US-PA	PA
+Rhode Island	State	US-RI	RI
+South Carolina	State	US-SC	SC
+South Dakota	State	US-SD	SD
+Tennessee	State	US-TN	TN
+Texas	State	US-TX	TX
+Utah	State	US-UT	UT
+Vermont	State	US-VT	VT
+Virginia	State (Commonwealth)	US-VA	VA
+Washington	State	US-WA	WA
+West Virginia	State	US-WV	WV
+Wisconsin	State	US-WI	WI
+Wyoming	State	US-WY	WY