2018/2018-07-09/Demo.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Techtalk on PANDAS\n",
    "## Gary's walk through\n",
    "\n",
    "Demonstration of loading files from various sources\n",
    "- read_html\n",
    "- read_url\n",
    "- read_csv\n",
    "- read_excel\n",
    "- read json\n",
    "- read databases\n",
    "- read nosql databasws\n",
    "- read text\n",
    "- read Gz/ziped files\n",
    "- read parquet\n",
    "- read_url\n",
    "- read apis\n",
    "\n",
    "This example will be using read_html to \"scrape\"  a Wiki Page\n",
    "ufo = pd.read_csv('http://bit.ly/uforeports')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Getting data from HTTP"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#df = pd.read_html(\"https://en.wikipedia.org/wiki/Number_of_guns_per_capita_by_country\")\n",
    "df = pd.read_html(\"https://en.wikipedia.org/wiki/Number_of_guns_per_capita_by_country\")[3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Place holder to do stuff"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
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       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Country</td>\n",
       "      <td>Civilian-heldfirearms per100 population</td>\n",
       "      <td>Notes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>United States</td>\n",
       "      <td>101[5][6]</td>\n",
       "      <td>[note 1]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Serbia</td>\n",
       "      <td>58.21[9]</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Yemen</td>\n",
       "      <td>54.8</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Cyprus</td>\n",
       "      <td>36.4[10]</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Saudi Arabia</td>\n",
       "      <td>35</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Iraq</td>\n",
       "      <td>34.2</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Uruguay</td>\n",
       "      <td>31.8</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Norway</td>\n",
       "      <td>31.3</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>France</td>\n",
       "      <td>31.2</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Canada</td>\n",
       "      <td>30.8</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Austria</td>\n",
       "      <td>30.4</td>\n",
       "      <td>[note 2]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Iceland</td>\n",
       "      <td>30.3</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Germany</td>\n",
       "      <td>30.3</td>\n",
       "      <td>[note 3]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Finland</td>\n",
       "      <td>27.3</td>\n",
       "      <td>[note 4]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Oman</td>\n",
       "      <td>25.5</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Bahrain</td>\n",
       "      <td>24.8</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Kuwait</td>\n",
       "      <td>24.8</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Switzerland</td>\n",
       "      <td>24.45</td>\n",
       "      <td>[note 5]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Republic of Macedonia</td>\n",
       "      <td>24.1</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Montenegro</td>\n",
       "      <td>23.1</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>New Zealand</td>\n",
       "      <td>22.6</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Greece</td>\n",
       "      <td>22.5</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>United Arab Emirates</td>\n",
       "      <td>22.1</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Croatia</td>\n",
       "      <td>21.7</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>Panama</td>\n",
       "      <td>21.7</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Sweden</td>\n",
       "      <td>21</td>\n",
       "      <td>[note 6]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>Lebanon</td>\n",
       "      <td>21</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>Equatorial Guinea</td>\n",
       "      <td>19.9</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>Qatar</td>\n",
       "      <td>19.2</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>146</th>\n",
       "      <td>Burkina Faso</td>\n",
       "      <td>1.1</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>147</th>\n",
       "      <td>Chad</td>\n",
       "      <td>1.1</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>148</th>\n",
       "      <td>South Korea</td>\n",
       "      <td>1.1</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>149</th>\n",
       "      <td>Mali</td>\n",
       "      <td>1.1</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>150</th>\n",
       "      <td>Central African Republic</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151</th>\n",
       "      <td>Tajikistan</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>152</th>\n",
       "      <td>Togo</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>153</th>\n",
       "      <td>Kyrgyzstan</td>\n",
       "      <td>0.9</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>154</th>\n",
       "      <td>Gambia</td>\n",
       "      <td>0.8</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>155</th>\n",
       "      <td>Madagascar</td>\n",
       "      <td>0.8</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>156</th>\n",
       "      <td>Nepal</td>\n",
       "      <td>0.8</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>157</th>\n",
       "      <td>Lithuania</td>\n",
       "      <td>0.7</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>158</th>\n",
       "      <td>Malawi</td>\n",
       "      <td>0.7</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>159</th>\n",
       "      <td>Niger</td>\n",
       "      <td>0.7</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>160</th>\n",
       "      <td>Romania</td>\n",
       "      <td>0.7</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>161</th>\n",
       "      <td>Haiti</td>\n",
       "      <td>0.6</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>162</th>\n",
       "      <td>Japan</td>\n",
       "      <td>0.6</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>163</th>\n",
       "      <td>North Korea</td>\n",
       "      <td>0.6</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>164</th>\n",
       "      <td>Rwanda</td>\n",
       "      <td>0.6</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>165</th>\n",
       "      <td>Sierra Leone</td>\n",
       "      <td>0.6</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>166</th>\n",
       "      <td>Bangladesh</td>\n",
       "      <td>0.5</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167</th>\n",
       "      <td>Eritrea</td>\n",
       "      <td>0.5</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>168</th>\n",
       "      <td>Fiji</td>\n",
       "      <td>0.5</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>169</th>\n",
       "      <td>Indonesia</td>\n",
       "      <td>0.5</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>170</th>\n",
       "      <td>Singapore</td>\n",
       "      <td>0.5</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>171</th>\n",
       "      <td>Ethiopia</td>\n",
       "      <td>0.4</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>172</th>\n",
       "      <td>Ghana</td>\n",
       "      <td>0.4</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>173</th>\n",
       "      <td>Solomon Islands</td>\n",
       "      <td>0.4</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>174</th>\n",
       "      <td>Timor-Leste</td>\n",
       "      <td>0.3</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>175</th>\n",
       "      <td>Tunisia</td>\n",
       "      <td>0.1</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>176 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                            0                                        1  \\\n",
       "0                     Country  Civilian-heldfirearms per100 population   \n",
       "1               United States                                101[5][6]   \n",
       "2                      Serbia                                 58.21[9]   \n",
       "3                       Yemen                                     54.8   \n",
       "4                      Cyprus                                 36.4[10]   \n",
       "5                Saudi Arabia                                       35   \n",
       "6                        Iraq                                     34.2   \n",
       "7                     Uruguay                                     31.8   \n",
       "8                      Norway                                     31.3   \n",
       "9                      France                                     31.2   \n",
       "10                     Canada                                     30.8   \n",
       "11                    Austria                                     30.4   \n",
       "12                    Iceland                                     30.3   \n",
       "13                    Germany                                     30.3   \n",
       "14                    Finland                                     27.3   \n",
       "15                       Oman                                     25.5   \n",
       "16                    Bahrain                                     24.8   \n",
       "17                     Kuwait                                     24.8   \n",
       "18                Switzerland                                    24.45   \n",
       "19      Republic of Macedonia                                     24.1   \n",
       "20                 Montenegro                                     23.1   \n",
       "21                New Zealand                                     22.6   \n",
       "22                     Greece                                     22.5   \n",
       "23       United Arab Emirates                                     22.1   \n",
       "24                    Croatia                                     21.7   \n",
       "25                     Panama                                     21.7   \n",
       "26                     Sweden                                       21   \n",
       "27                    Lebanon                                       21   \n",
       "28          Equatorial Guinea                                     19.9   \n",
       "29                      Qatar                                     19.2   \n",
       "..                        ...                                      ...   \n",
       "146              Burkina Faso                                      1.1   \n",
       "147                      Chad                                      1.1   \n",
       "148               South Korea                                      1.1   \n",
       "149                      Mali                                      1.1   \n",
       "150  Central African Republic                                        1   \n",
       "151                Tajikistan                                        1   \n",
       "152                      Togo                                        1   \n",
       "153                Kyrgyzstan                                      0.9   \n",
       "154                    Gambia                                      0.8   \n",
       "155                Madagascar                                      0.8   \n",
       "156                     Nepal                                      0.8   \n",
       "157                 Lithuania                                      0.7   \n",
       "158                    Malawi                                      0.7   \n",
       "159                     Niger                                      0.7   \n",
       "160                   Romania                                      0.7   \n",
       "161                     Haiti                                      0.6   \n",
       "162                     Japan                                      0.6   \n",
       "163               North Korea                                      0.6   \n",
       "164                    Rwanda                                      0.6   \n",
       "165              Sierra Leone                                      0.6   \n",
       "166                Bangladesh                                      0.5   \n",
       "167                   Eritrea                                      0.5   \n",
       "168                      Fiji                                      0.5   \n",
       "169                 Indonesia                                      0.5   \n",
       "170                 Singapore                                      0.5   \n",
       "171                  Ethiopia                                      0.4   \n",
       "172                     Ghana                                      0.4   \n",
       "173           Solomon Islands                                      0.4   \n",
       "174               Timor-Leste                                      0.3   \n",
       "175                   Tunisia                                      0.1   \n",
       "\n",
       "            2  \n",
       "0       Notes  \n",
       "1    [note 1]  \n",
       "2         NaN  \n",
       "3         NaN  \n",
       "4         NaN  \n",
       "5         NaN  \n",
       "6         NaN  \n",
       "7         NaN  \n",
       "8         NaN  \n",
       "9         NaN  \n",
       "10        NaN  \n",
       "11   [note 2]  \n",
       "12        NaN  \n",
       "13   [note 3]  \n",
       "14   [note 4]  \n",
       "15        NaN  \n",
       "16        NaN  \n",
       "17        NaN  \n",
       "18   [note 5]  \n",
       "19        NaN  \n",
       "20        NaN  \n",
       "21        NaN  \n",
       "22        NaN  \n",
       "23        NaN  \n",
       "24        NaN  \n",
       "25        NaN  \n",
       "26   [note 6]  \n",
       "27        NaN  \n",
       "28        NaN  \n",
       "29        NaN  \n",
       "..        ...  \n",
       "146       NaN  \n",
       "147       NaN  \n",
       "148       NaN  \n",
       "149       NaN  \n",
       "150       NaN  \n",
       "151       NaN  \n",
       "152       NaN  \n",
       "153       NaN  \n",
       "154       NaN  \n",
       "155       NaN  \n",
       "156       NaN  \n",
       "157       NaN  \n",
       "158       NaN  \n",
       "159       NaN  \n",
       "160       NaN  \n",
       "161       NaN  \n",
       "162       NaN  \n",
       "163       NaN  \n",
       "164       NaN  \n",
       "165       NaN  \n",
       "166       NaN  \n",
       "167       NaN  \n",
       "168       NaN  \n",
       "169       NaN  \n",
       "170       NaN  \n",
       "171       NaN  \n",
       "172       NaN  \n",
       "173       NaN  \n",
       "174       NaN  \n",
       "175       NaN  \n",
       "\n",
       "[176 rows x 3 columns]"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# placeholder\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Cleaning"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.columns=['Country','PerResident','Dummy']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Country</th>\n",
       "      <th>PerResident</th>\n",
       "      <th>Dummy</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Country</td>\n",
       "      <td>Civilian-heldfirearms per100 population</td>\n",
       "      <td>Notes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>United States</td>\n",
       "      <td>101[5][6]</td>\n",
       "      <td>[note 1]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Serbia</td>\n",
       "      <td>58.21[9]</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Yemen</td>\n",
       "      <td>54.8</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Cyprus</td>\n",
       "      <td>36.4[10]</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Saudi Arabia</td>\n",
       "      <td>35</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Iraq</td>\n",
       "      <td>34.2</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Uruguay</td>\n",
       "      <td>31.8</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Norway</td>\n",
       "      <td>31.3</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>France</td>\n",
       "      <td>31.2</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Canada</td>\n",
       "      <td>30.8</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Austria</td>\n",
       "      <td>30.4</td>\n",
       "      <td>[note 2]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Iceland</td>\n",
       "      <td>30.3</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Germany</td>\n",
       "      <td>30.3</td>\n",
       "      <td>[note 3]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Finland</td>\n",
       "      <td>27.3</td>\n",
       "      <td>[note 4]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Oman</td>\n",
       "      <td>25.5</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Bahrain</td>\n",
       "      <td>24.8</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Kuwait</td>\n",
       "      <td>24.8</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Switzerland</td>\n",
       "      <td>24.45</td>\n",
       "      <td>[note 5]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Republic of Macedonia</td>\n",
       "      <td>24.1</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Montenegro</td>\n",
       "      <td>23.1</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>New Zealand</td>\n",
       "      <td>22.6</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Greece</td>\n",
       "      <td>22.5</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>United Arab Emirates</td>\n",
       "      <td>22.1</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Croatia</td>\n",
       "      <td>21.7</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>Panama</td>\n",
       "      <td>21.7</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Sweden</td>\n",
       "      <td>21</td>\n",
       "      <td>[note 6]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>Lebanon</td>\n",
       "      <td>21</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>Equatorial Guinea</td>\n",
       "      <td>19.9</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>Qatar</td>\n",
       "      <td>19.2</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>146</th>\n",
       "      <td>Burkina Faso</td>\n",
       "      <td>1.1</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>147</th>\n",
       "      <td>Chad</td>\n",
       "      <td>1.1</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>148</th>\n",
       "      <td>South Korea</td>\n",
       "      <td>1.1</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>149</th>\n",
       "      <td>Mali</td>\n",
       "      <td>1.1</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>150</th>\n",
       "      <td>Central African Republic</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151</th>\n",
       "      <td>Tajikistan</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>152</th>\n",
       "      <td>Togo</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>153</th>\n",
       "      <td>Kyrgyzstan</td>\n",
       "      <td>0.9</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>154</th>\n",
       "      <td>Gambia</td>\n",
       "      <td>0.8</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>155</th>\n",
       "      <td>Madagascar</td>\n",
       "      <td>0.8</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>156</th>\n",
       "      <td>Nepal</td>\n",
       "      <td>0.8</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>157</th>\n",
       "      <td>Lithuania</td>\n",
       "      <td>0.7</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>158</th>\n",
       "      <td>Malawi</td>\n",
       "      <td>0.7</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>159</th>\n",
       "      <td>Niger</td>\n",
       "      <td>0.7</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>160</th>\n",
       "      <td>Romania</td>\n",
       "      <td>0.7</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>161</th>\n",
       "      <td>Haiti</td>\n",
       "      <td>0.6</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>162</th>\n",
       "      <td>Japan</td>\n",
       "      <td>0.6</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>163</th>\n",
       "      <td>North Korea</td>\n",
       "      <td>0.6</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>164</th>\n",
       "      <td>Rwanda</td>\n",
       "      <td>0.6</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>165</th>\n",
       "      <td>Sierra Leone</td>\n",
       "      <td>0.6</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>166</th>\n",
       "      <td>Bangladesh</td>\n",
       "      <td>0.5</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167</th>\n",
       "      <td>Eritrea</td>\n",
       "      <td>0.5</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>168</th>\n",
       "      <td>Fiji</td>\n",
       "      <td>0.5</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>169</th>\n",
       "      <td>Indonesia</td>\n",
       "      <td>0.5</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>170</th>\n",
       "      <td>Singapore</td>\n",
       "      <td>0.5</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>171</th>\n",
       "      <td>Ethiopia</td>\n",
       "      <td>0.4</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>172</th>\n",
       "      <td>Ghana</td>\n",
       "      <td>0.4</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>173</th>\n",
       "      <td>Solomon Islands</td>\n",
       "      <td>0.4</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>174</th>\n",
       "      <td>Timor-Leste</td>\n",
       "      <td>0.3</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>175</th>\n",
       "      <td>Tunisia</td>\n",
       "      <td>0.1</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>176 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                      Country                              PerResident  \\\n",
       "0                     Country  Civilian-heldfirearms per100 population   \n",
       "1               United States                                101[5][6]   \n",
       "2                      Serbia                                 58.21[9]   \n",
       "3                       Yemen                                     54.8   \n",
       "4                      Cyprus                                 36.4[10]   \n",
       "5                Saudi Arabia                                       35   \n",
       "6                        Iraq                                     34.2   \n",
       "7                     Uruguay                                     31.8   \n",
       "8                      Norway                                     31.3   \n",
       "9                      France                                     31.2   \n",
       "10                     Canada                                     30.8   \n",
       "11                    Austria                                     30.4   \n",
       "12                    Iceland                                     30.3   \n",
       "13                    Germany                                     30.3   \n",
       "14                    Finland                                     27.3   \n",
       "15                       Oman                                     25.5   \n",
       "16                    Bahrain                                     24.8   \n",
       "17                     Kuwait                                     24.8   \n",
       "18                Switzerland                                    24.45   \n",
       "19      Republic of Macedonia                                     24.1   \n",
       "20                 Montenegro                                     23.1   \n",
       "21                New Zealand                                     22.6   \n",
       "22                     Greece                                     22.5   \n",
       "23       United Arab Emirates                                     22.1   \n",
       "24                    Croatia                                     21.7   \n",
       "25                     Panama                                     21.7   \n",
       "26                     Sweden                                       21   \n",
       "27                    Lebanon                                       21   \n",
       "28          Equatorial Guinea                                     19.9   \n",
       "29                      Qatar                                     19.2   \n",
       "..                        ...                                      ...   \n",
       "146              Burkina Faso                                      1.1   \n",
       "147                      Chad                                      1.1   \n",
       "148               South Korea                                      1.1   \n",
       "149                      Mali                                      1.1   \n",
       "150  Central African Republic                                        1   \n",
       "151                Tajikistan                                        1   \n",
       "152                      Togo                                        1   \n",
       "153                Kyrgyzstan                                      0.9   \n",
       "154                    Gambia                                      0.8   \n",
       "155                Madagascar                                      0.8   \n",
       "156                     Nepal                                      0.8   \n",
       "157                 Lithuania                                      0.7   \n",
       "158                    Malawi                                      0.7   \n",
       "159                     Niger                                      0.7   \n",
       "160                   Romania                                      0.7   \n",
       "161                     Haiti                                      0.6   \n",
       "162                     Japan                                      0.6   \n",
       "163               North Korea                                      0.6   \n",
       "164                    Rwanda                                      0.6   \n",
       "165              Sierra Leone                                      0.6   \n",
       "166                Bangladesh                                      0.5   \n",
       "167                   Eritrea                                      0.5   \n",
       "168                      Fiji                                      0.5   \n",
       "169                 Indonesia                                      0.5   \n",
       "170                 Singapore                                      0.5   \n",
       "171                  Ethiopia                                      0.4   \n",
       "172                     Ghana                                      0.4   \n",
       "173           Solomon Islands                                      0.4   \n",
       "174               Timor-Leste                                      0.3   \n",
       "175                   Tunisia                                      0.1   \n",
       "\n",
       "        Dummy  \n",
       "0       Notes  \n",
       "1    [note 1]  \n",
       "2         NaN  \n",
       "3         NaN  \n",
       "4         NaN  \n",
       "5         NaN  \n",
       "6         NaN  \n",
       "7         NaN  \n",
       "8         NaN  \n",
       "9         NaN  \n",
       "10        NaN  \n",
       "11   [note 2]  \n",
       "12        NaN  \n",
       "13   [note 3]  \n",
       "14   [note 4]  \n",
       "15        NaN  \n",
       "16        NaN  \n",
       "17        NaN  \n",
       "18   [note 5]  \n",
       "19        NaN  \n",
       "20        NaN  \n",
       "21        NaN  \n",
       "22        NaN  \n",
       "23        NaN  \n",
       "24        NaN  \n",
       "25        NaN  \n",
       "26   [note 6]  \n",
       "27        NaN  \n",
       "28        NaN  \n",
       "29        NaN  \n",
       "..        ...  \n",
       "146       NaN  \n",
       "147       NaN  \n",
       "148       NaN  \n",
       "149       NaN  \n",
       "150       NaN  \n",
       "151       NaN  \n",
       "152       NaN  \n",
       "153       NaN  \n",
       "154       NaN  \n",
       "155       NaN  \n",
       "156       NaN  \n",
       "157       NaN  \n",
       "158       NaN  \n",
       "159       NaN  \n",
       "160       NaN  \n",
       "161       NaN  \n",
       "162       NaN  \n",
       "163       NaN  \n",
       "164       NaN  \n",
       "165       NaN  \n",
       "166       NaN  \n",
       "167       NaN  \n",
       "168       NaN  \n",
       "169       NaN  \n",
       "170       NaN  \n",
       "171       NaN  \n",
       "172       NaN  \n",
       "173       NaN  \n",
       "174       NaN  \n",
       "175       NaN  \n",
       "\n",
       "[176 rows x 3 columns]"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df = df[['Country','PerResident']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
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       "\n",
       "    .dataframe thead th {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Country</th>\n",
       "      <th>PerResident</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Country</td>\n",
       "      <td>Civilian-heldfirearms per100 population</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>United States</td>\n",
       "      <td>101[5][6]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Serbia</td>\n",
       "      <td>58.21[9]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Yemen</td>\n",
       "      <td>54.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Cyprus</td>\n",
       "      <td>36.4[10]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Saudi Arabia</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Iraq</td>\n",
       "      <td>34.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Uruguay</td>\n",
       "      <td>31.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Norway</td>\n",
       "      <td>31.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>France</td>\n",
       "      <td>31.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Canada</td>\n",
       "      <td>30.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Austria</td>\n",
       "      <td>30.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Iceland</td>\n",
       "      <td>30.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Germany</td>\n",
       "      <td>30.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Finland</td>\n",
       "      <td>27.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Oman</td>\n",
       "      <td>25.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Bahrain</td>\n",
       "      <td>24.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Kuwait</td>\n",
       "      <td>24.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Switzerland</td>\n",
       "      <td>24.45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Republic of Macedonia</td>\n",
       "      <td>24.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Montenegro</td>\n",
       "      <td>23.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>New Zealand</td>\n",
       "      <td>22.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Greece</td>\n",
       "      <td>22.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>United Arab Emirates</td>\n",
       "      <td>22.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Croatia</td>\n",
       "      <td>21.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>Panama</td>\n",
       "      <td>21.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Sweden</td>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>Lebanon</td>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>Equatorial Guinea</td>\n",
       "      <td>19.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>Qatar</td>\n",
       "      <td>19.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>146</th>\n",
       "      <td>Burkina Faso</td>\n",
       "      <td>1.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>147</th>\n",
       "      <td>Chad</td>\n",
       "      <td>1.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>148</th>\n",
       "      <td>South Korea</td>\n",
       "      <td>1.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>149</th>\n",
       "      <td>Mali</td>\n",
       "      <td>1.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>150</th>\n",
       "      <td>Central African Republic</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151</th>\n",
       "      <td>Tajikistan</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>152</th>\n",
       "      <td>Togo</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>153</th>\n",
       "      <td>Kyrgyzstan</td>\n",
       "      <td>0.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>154</th>\n",
       "      <td>Gambia</td>\n",
       "      <td>0.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>155</th>\n",
       "      <td>Madagascar</td>\n",
       "      <td>0.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>156</th>\n",
       "      <td>Nepal</td>\n",
       "      <td>0.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>157</th>\n",
       "      <td>Lithuania</td>\n",
       "      <td>0.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>158</th>\n",
       "      <td>Malawi</td>\n",
       "      <td>0.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>159</th>\n",
       "      <td>Niger</td>\n",
       "      <td>0.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>160</th>\n",
       "      <td>Romania</td>\n",
       "      <td>0.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>161</th>\n",
       "      <td>Haiti</td>\n",
       "      <td>0.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>162</th>\n",
       "      <td>Japan</td>\n",
       "      <td>0.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>163</th>\n",
       "      <td>North Korea</td>\n",
       "      <td>0.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>164</th>\n",
       "      <td>Rwanda</td>\n",
       "      <td>0.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>165</th>\n",
       "      <td>Sierra Leone</td>\n",
       "      <td>0.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>166</th>\n",
       "      <td>Bangladesh</td>\n",
       "      <td>0.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167</th>\n",
       "      <td>Eritrea</td>\n",
       "      <td>0.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>168</th>\n",
       "      <td>Fiji</td>\n",
       "      <td>0.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>169</th>\n",
       "      <td>Indonesia</td>\n",
       "      <td>0.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>170</th>\n",
       "      <td>Singapore</td>\n",
       "      <td>0.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>171</th>\n",
       "      <td>Ethiopia</td>\n",
       "      <td>0.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>172</th>\n",
       "      <td>Ghana</td>\n",
       "      <td>0.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>173</th>\n",
       "      <td>Solomon Islands</td>\n",
       "      <td>0.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>174</th>\n",
       "      <td>Timor-Leste</td>\n",
       "      <td>0.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>175</th>\n",
       "      <td>Tunisia</td>\n",
       "      <td>0.1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>176 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                      Country                              PerResident\n",
       "0                     Country  Civilian-heldfirearms per100 population\n",
       "1               United States                                101[5][6]\n",
       "2                      Serbia                                 58.21[9]\n",
       "3                       Yemen                                     54.8\n",
       "4                      Cyprus                                 36.4[10]\n",
       "5                Saudi Arabia                                       35\n",
       "6                        Iraq                                     34.2\n",
       "7                     Uruguay                                     31.8\n",
       "8                      Norway                                     31.3\n",
       "9                      France                                     31.2\n",
       "10                     Canada                                     30.8\n",
       "11                    Austria                                     30.4\n",
       "12                    Iceland                                     30.3\n",
       "13                    Germany                                     30.3\n",
       "14                    Finland                                     27.3\n",
       "15                       Oman                                     25.5\n",
       "16                    Bahrain                                     24.8\n",
       "17                     Kuwait                                     24.8\n",
       "18                Switzerland                                    24.45\n",
       "19      Republic of Macedonia                                     24.1\n",
       "20                 Montenegro                                     23.1\n",
       "21                New Zealand                                     22.6\n",
       "22                     Greece                                     22.5\n",
       "23       United Arab Emirates                                     22.1\n",
       "24                    Croatia                                     21.7\n",
       "25                     Panama                                     21.7\n",
       "26                     Sweden                                       21\n",
       "27                    Lebanon                                       21\n",
       "28          Equatorial Guinea                                     19.9\n",
       "29                      Qatar                                     19.2\n",
       "..                        ...                                      ...\n",
       "146              Burkina Faso                                      1.1\n",
       "147                      Chad                                      1.1\n",
       "148               South Korea                                      1.1\n",
       "149                      Mali                                      1.1\n",
       "150  Central African Republic                                        1\n",
       "151                Tajikistan                                        1\n",
       "152                      Togo                                        1\n",
       "153                Kyrgyzstan                                      0.9\n",
       "154                    Gambia                                      0.8\n",
       "155                Madagascar                                      0.8\n",
       "156                     Nepal                                      0.8\n",
       "157                 Lithuania                                      0.7\n",
       "158                    Malawi                                      0.7\n",
       "159                     Niger                                      0.7\n",
       "160                   Romania                                      0.7\n",
       "161                     Haiti                                      0.6\n",
       "162                     Japan                                      0.6\n",
       "163               North Korea                                      0.6\n",
       "164                    Rwanda                                      0.6\n",
       "165              Sierra Leone                                      0.6\n",
       "166                Bangladesh                                      0.5\n",
       "167                   Eritrea                                      0.5\n",
       "168                      Fiji                                      0.5\n",
       "169                 Indonesia                                      0.5\n",
       "170                 Singapore                                      0.5\n",
       "171                  Ethiopia                                      0.4\n",
       "172                     Ghana                                      0.4\n",
       "173           Solomon Islands                                      0.4\n",
       "174               Timor-Leste                                      0.3\n",
       "175                   Tunisia                                      0.1\n",
       "\n",
       "[176 rows x 2 columns]"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df = df.iloc[1:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Country</th>\n",
       "      <th>PerResident</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>United States</td>\n",
       "      <td>101[5][6]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Serbia</td>\n",
       "      <td>58.21[9]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Yemen</td>\n",
       "      <td>54.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Cyprus</td>\n",
       "      <td>36.4[10]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Saudi Arabia</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Iraq</td>\n",
       "      <td>34.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Uruguay</td>\n",
       "      <td>31.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Norway</td>\n",
       "      <td>31.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>France</td>\n",
       "      <td>31.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Canada</td>\n",
       "      <td>30.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Austria</td>\n",
       "      <td>30.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Iceland</td>\n",
       "      <td>30.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Germany</td>\n",
       "      <td>30.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Finland</td>\n",
       "      <td>27.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Oman</td>\n",
       "      <td>25.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Bahrain</td>\n",
       "      <td>24.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Kuwait</td>\n",
       "      <td>24.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Switzerland</td>\n",
       "      <td>24.45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Republic of Macedonia</td>\n",
       "      <td>24.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Montenegro</td>\n",
       "      <td>23.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>New Zealand</td>\n",
       "      <td>22.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Greece</td>\n",
       "      <td>22.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>United Arab Emirates</td>\n",
       "      <td>22.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Croatia</td>\n",
       "      <td>21.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>Panama</td>\n",
       "      <td>21.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Sweden</td>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>Lebanon</td>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>Equatorial Guinea</td>\n",
       "      <td>19.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>Qatar</td>\n",
       "      <td>19.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>Latvia</td>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>146</th>\n",
       "      <td>Burkina Faso</td>\n",
       "      <td>1.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>147</th>\n",
       "      <td>Chad</td>\n",
       "      <td>1.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>148</th>\n",
       "      <td>South Korea</td>\n",
       "      <td>1.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>149</th>\n",
       "      <td>Mali</td>\n",
       "      <td>1.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>150</th>\n",
       "      <td>Central African Republic</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151</th>\n",
       "      <td>Tajikistan</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>152</th>\n",
       "      <td>Togo</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>153</th>\n",
       "      <td>Kyrgyzstan</td>\n",
       "      <td>0.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>154</th>\n",
       "      <td>Gambia</td>\n",
       "      <td>0.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>155</th>\n",
       "      <td>Madagascar</td>\n",
       "      <td>0.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>156</th>\n",
       "      <td>Nepal</td>\n",
       "      <td>0.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>157</th>\n",
       "      <td>Lithuania</td>\n",
       "      <td>0.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>158</th>\n",
       "      <td>Malawi</td>\n",
       "      <td>0.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>159</th>\n",
       "      <td>Niger</td>\n",
       "      <td>0.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>160</th>\n",
       "      <td>Romania</td>\n",
       "      <td>0.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>161</th>\n",
       "      <td>Haiti</td>\n",
       "      <td>0.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>162</th>\n",
       "      <td>Japan</td>\n",
       "      <td>0.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>163</th>\n",
       "      <td>North Korea</td>\n",
       "      <td>0.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>164</th>\n",
       "      <td>Rwanda</td>\n",
       "      <td>0.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>165</th>\n",
       "      <td>Sierra Leone</td>\n",
       "      <td>0.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>166</th>\n",
       "      <td>Bangladesh</td>\n",
       "      <td>0.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167</th>\n",
       "      <td>Eritrea</td>\n",
       "      <td>0.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>168</th>\n",
       "      <td>Fiji</td>\n",
       "      <td>0.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>169</th>\n",
       "      <td>Indonesia</td>\n",
       "      <td>0.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>170</th>\n",
       "      <td>Singapore</td>\n",
       "      <td>0.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>171</th>\n",
       "      <td>Ethiopia</td>\n",
       "      <td>0.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>172</th>\n",
       "      <td>Ghana</td>\n",
       "      <td>0.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>173</th>\n",
       "      <td>Solomon Islands</td>\n",
       "      <td>0.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>174</th>\n",
       "      <td>Timor-Leste</td>\n",
       "      <td>0.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>175</th>\n",
       "      <td>Tunisia</td>\n",
       "      <td>0.1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>175 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                      Country PerResident\n",
       "1               United States   101[5][6]\n",
       "2                      Serbia    58.21[9]\n",
       "3                       Yemen        54.8\n",
       "4                      Cyprus    36.4[10]\n",
       "5                Saudi Arabia          35\n",
       "6                        Iraq        34.2\n",
       "7                     Uruguay        31.8\n",
       "8                      Norway        31.3\n",
       "9                      France        31.2\n",
       "10                     Canada        30.8\n",
       "11                    Austria        30.4\n",
       "12                    Iceland        30.3\n",
       "13                    Germany        30.3\n",
       "14                    Finland        27.3\n",
       "15                       Oman        25.5\n",
       "16                    Bahrain        24.8\n",
       "17                     Kuwait        24.8\n",
       "18                Switzerland       24.45\n",
       "19      Republic of Macedonia        24.1\n",
       "20                 Montenegro        23.1\n",
       "21                New Zealand        22.6\n",
       "22                     Greece        22.5\n",
       "23       United Arab Emirates        22.1\n",
       "24                    Croatia        21.7\n",
       "25                     Panama        21.7\n",
       "26                     Sweden          21\n",
       "27                    Lebanon          21\n",
       "28          Equatorial Guinea        19.9\n",
       "29                      Qatar        19.2\n",
       "30                     Latvia          19\n",
       "..                        ...         ...\n",
       "146              Burkina Faso         1.1\n",
       "147                      Chad         1.1\n",
       "148               South Korea         1.1\n",
       "149                      Mali         1.1\n",
       "150  Central African Republic           1\n",
       "151                Tajikistan           1\n",
       "152                      Togo           1\n",
       "153                Kyrgyzstan         0.9\n",
       "154                    Gambia         0.8\n",
       "155                Madagascar         0.8\n",
       "156                     Nepal         0.8\n",
       "157                 Lithuania         0.7\n",
       "158                    Malawi         0.7\n",
       "159                     Niger         0.7\n",
       "160                   Romania         0.7\n",
       "161                     Haiti         0.6\n",
       "162                     Japan         0.6\n",
       "163               North Korea         0.6\n",
       "164                    Rwanda         0.6\n",
       "165              Sierra Leone         0.6\n",
       "166                Bangladesh         0.5\n",
       "167                   Eritrea         0.5\n",
       "168                      Fiji         0.5\n",
       "169                 Indonesia         0.5\n",
       "170                 Singapore         0.5\n",
       "171                  Ethiopia         0.4\n",
       "172                     Ghana         0.4\n",
       "173           Solomon Islands         0.4\n",
       "174               Timor-Leste         0.3\n",
       "175                   Tunisia         0.1\n",
       "\n",
       "[175 rows x 2 columns]"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\gbuczma\\AppData\\Local\\Continuum\\anaconda3\\lib\\site-packages\\pandas\\core\\generic.py:3110: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self[name] = value\n"
     ]
    }
   ],
   "source": [
    "df.PerResident = df.PerResident.str.split('[').str[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>3</th>\n",
       "      <td>Yemen</td>\n",
       "      <td>54.8</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
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       "      <td>36.4</td>\n",
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       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Saudi Arabia</td>\n",
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       "      <th>7</th>\n",
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       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Norway</td>\n",
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       "      <th>9</th>\n",
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       "      <td>30.4</td>\n",
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       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Iceland</td>\n",
       "      <td>30.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Germany</td>\n",
       "      <td>30.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Finland</td>\n",
       "      <td>27.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Oman</td>\n",
       "      <td>25.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Bahrain</td>\n",
       "      <td>24.8</td>\n",
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       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Kuwait</td>\n",
       "      <td>24.8</td>\n",
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       "      <th>18</th>\n",
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       "      <th>19</th>\n",
       "      <td>Republic of Macedonia</td>\n",
       "      <td>24.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Montenegro</td>\n",
       "      <td>23.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>New Zealand</td>\n",
       "      <td>22.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Greece</td>\n",
       "      <td>22.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>United Arab Emirates</td>\n",
       "      <td>22.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Croatia</td>\n",
       "      <td>21.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>Panama</td>\n",
       "      <td>21.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Sweden</td>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>Lebanon</td>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>Equatorial Guinea</td>\n",
       "      <td>19.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>Qatar</td>\n",
       "      <td>19.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>Latvia</td>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>146</th>\n",
       "      <td>Burkina Faso</td>\n",
       "      <td>1.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>147</th>\n",
       "      <td>Chad</td>\n",
       "      <td>1.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>148</th>\n",
       "      <td>South Korea</td>\n",
       "      <td>1.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>149</th>\n",
       "      <td>Mali</td>\n",
       "      <td>1.1</td>\n",
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       "    <tr>\n",
       "      <th>150</th>\n",
       "      <td>Central African Republic</td>\n",
       "      <td>1</td>\n",
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       "      <th>151</th>\n",
       "      <td>Tajikistan</td>\n",
       "      <td>1</td>\n",
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       "      <td>1</td>\n",
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       "      <th>153</th>\n",
       "      <td>Kyrgyzstan</td>\n",
       "      <td>0.9</td>\n",
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       "      <th>154</th>\n",
       "      <td>Gambia</td>\n",
       "      <td>0.8</td>\n",
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       "    <tr>\n",
       "      <th>155</th>\n",
       "      <td>Madagascar</td>\n",
       "      <td>0.8</td>\n",
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       "    <tr>\n",
       "      <th>156</th>\n",
       "      <td>Nepal</td>\n",
       "      <td>0.8</td>\n",
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       "    <tr>\n",
       "      <th>157</th>\n",
       "      <td>Lithuania</td>\n",
       "      <td>0.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>158</th>\n",
       "      <td>Malawi</td>\n",
       "      <td>0.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>159</th>\n",
       "      <td>Niger</td>\n",
       "      <td>0.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>160</th>\n",
       "      <td>Romania</td>\n",
       "      <td>0.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>161</th>\n",
       "      <td>Haiti</td>\n",
       "      <td>0.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>162</th>\n",
       "      <td>Japan</td>\n",
       "      <td>0.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>163</th>\n",
       "      <td>North Korea</td>\n",
       "      <td>0.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>164</th>\n",
       "      <td>Rwanda</td>\n",
       "      <td>0.6</td>\n",
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       "    <tr>\n",
       "      <th>165</th>\n",
       "      <td>Sierra Leone</td>\n",
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       "      <th>166</th>\n",
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       "    <tr>\n",
       "      <th>167</th>\n",
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       "    <tr>\n",
       "      <th>168</th>\n",
       "      <td>Fiji</td>\n",
       "      <td>0.5</td>\n",
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       "    <tr>\n",
       "      <th>169</th>\n",
       "      <td>Indonesia</td>\n",
       "      <td>0.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>170</th>\n",
       "      <td>Singapore</td>\n",
       "      <td>0.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>171</th>\n",
       "      <td>Ethiopia</td>\n",
       "      <td>0.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>172</th>\n",
       "      <td>Ghana</td>\n",
       "      <td>0.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>173</th>\n",
       "      <td>Solomon Islands</td>\n",
       "      <td>0.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>174</th>\n",
       "      <td>Timor-Leste</td>\n",
       "      <td>0.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>175</th>\n",
       "      <td>Tunisia</td>\n",
       "      <td>0.1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>175 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                      Country PerResident\n",
       "1               United States         101\n",
       "2                      Serbia       58.21\n",
       "3                       Yemen        54.8\n",
       "4                      Cyprus        36.4\n",
       "5                Saudi Arabia          35\n",
       "6                        Iraq        34.2\n",
       "7                     Uruguay        31.8\n",
       "8                      Norway        31.3\n",
       "9                      France        31.2\n",
       "10                     Canada        30.8\n",
       "11                    Austria        30.4\n",
       "12                    Iceland        30.3\n",
       "13                    Germany        30.3\n",
       "14                    Finland        27.3\n",
       "15                       Oman        25.5\n",
       "16                    Bahrain        24.8\n",
       "17                     Kuwait        24.8\n",
       "18                Switzerland       24.45\n",
       "19      Republic of Macedonia        24.1\n",
       "20                 Montenegro        23.1\n",
       "21                New Zealand        22.6\n",
       "22                     Greece        22.5\n",
       "23       United Arab Emirates        22.1\n",
       "24                    Croatia        21.7\n",
       "25                     Panama        21.7\n",
       "26                     Sweden          21\n",
       "27                    Lebanon          21\n",
       "28          Equatorial Guinea        19.9\n",
       "29                      Qatar        19.2\n",
       "30                     Latvia          19\n",
       "..                        ...         ...\n",
       "146              Burkina Faso         1.1\n",
       "147                      Chad         1.1\n",
       "148               South Korea         1.1\n",
       "149                      Mali         1.1\n",
       "150  Central African Republic           1\n",
       "151                Tajikistan           1\n",
       "152                      Togo           1\n",
       "153                Kyrgyzstan         0.9\n",
       "154                    Gambia         0.8\n",
       "155                Madagascar         0.8\n",
       "156                     Nepal         0.8\n",
       "157                 Lithuania         0.7\n",
       "158                    Malawi         0.7\n",
       "159                     Niger         0.7\n",
       "160                   Romania         0.7\n",
       "161                     Haiti         0.6\n",
       "162                     Japan         0.6\n",
       "163               North Korea         0.6\n",
       "164                    Rwanda         0.6\n",
       "165              Sierra Leone         0.6\n",
       "166                Bangladesh         0.5\n",
       "167                   Eritrea         0.5\n",
       "168                      Fiji         0.5\n",
       "169                 Indonesia         0.5\n",
       "170                 Singapore         0.5\n",
       "171                  Ethiopia         0.4\n",
       "172                     Ghana         0.4\n",
       "173           Solomon Islands         0.4\n",
       "174               Timor-Leste         0.3\n",
       "175                   Tunisia         0.1\n",
       "\n",
       "[175 rows x 2 columns]"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\gbuczma\\AppData\\Local\\Continuum\\anaconda3\\lib\\site-packages\\ipykernel_launcher.py:1: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  \"\"\"Entry point for launching an IPython kernel.\n"
     ]
    }
   ],
   "source": [
    "df['PerResident'] = df['PerResident'].astype('float64')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>Yemen</td>\n",
       "      <td>54.80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Cyprus</td>\n",
       "      <td>36.40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Saudi Arabia</td>\n",
       "      <td>35.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Iraq</td>\n",
       "      <td>34.20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Uruguay</td>\n",
       "      <td>31.80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Norway</td>\n",
       "      <td>31.30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>France</td>\n",
       "      <td>31.20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Canada</td>\n",
       "      <td>30.80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Austria</td>\n",
       "      <td>30.40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Iceland</td>\n",
       "      <td>30.30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Germany</td>\n",
       "      <td>30.30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Finland</td>\n",
       "      <td>27.30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Oman</td>\n",
       "      <td>25.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Bahrain</td>\n",
       "      <td>24.80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Kuwait</td>\n",
       "      <td>24.80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Switzerland</td>\n",
       "      <td>24.45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Republic of Macedonia</td>\n",
       "      <td>24.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Montenegro</td>\n",
       "      <td>23.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>New Zealand</td>\n",
       "      <td>22.60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Greece</td>\n",
       "      <td>22.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>United Arab Emirates</td>\n",
       "      <td>22.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Croatia</td>\n",
       "      <td>21.70</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>Panama</td>\n",
       "      <td>21.70</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Sweden</td>\n",
       "      <td>21.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>Lebanon</td>\n",
       "      <td>21.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>Equatorial Guinea</td>\n",
       "      <td>19.90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>Qatar</td>\n",
       "      <td>19.20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>Latvia</td>\n",
       "      <td>19.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>146</th>\n",
       "      <td>Burkina Faso</td>\n",
       "      <td>1.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>147</th>\n",
       "      <td>Chad</td>\n",
       "      <td>1.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>148</th>\n",
       "      <td>South Korea</td>\n",
       "      <td>1.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>149</th>\n",
       "      <td>Mali</td>\n",
       "      <td>1.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>150</th>\n",
       "      <td>Central African Republic</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151</th>\n",
       "      <td>Tajikistan</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>152</th>\n",
       "      <td>Togo</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>153</th>\n",
       "      <td>Kyrgyzstan</td>\n",
       "      <td>0.90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>154</th>\n",
       "      <td>Gambia</td>\n",
       "      <td>0.80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>155</th>\n",
       "      <td>Madagascar</td>\n",
       "      <td>0.80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>156</th>\n",
       "      <td>Nepal</td>\n",
       "      <td>0.80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>157</th>\n",
       "      <td>Lithuania</td>\n",
       "      <td>0.70</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>158</th>\n",
       "      <td>Malawi</td>\n",
       "      <td>0.70</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>159</th>\n",
       "      <td>Niger</td>\n",
       "      <td>0.70</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>160</th>\n",
       "      <td>Romania</td>\n",
       "      <td>0.70</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>161</th>\n",
       "      <td>Haiti</td>\n",
       "      <td>0.60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>162</th>\n",
       "      <td>Japan</td>\n",
       "      <td>0.60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>163</th>\n",
       "      <td>North Korea</td>\n",
       "      <td>0.60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>164</th>\n",
       "      <td>Rwanda</td>\n",
       "      <td>0.60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>165</th>\n",
       "      <td>Sierra Leone</td>\n",
       "      <td>0.60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>166</th>\n",
       "      <td>Bangladesh</td>\n",
       "      <td>0.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167</th>\n",
       "      <td>Eritrea</td>\n",
       "      <td>0.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>168</th>\n",
       "      <td>Fiji</td>\n",
       "      <td>0.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>169</th>\n",
       "      <td>Indonesia</td>\n",
       "      <td>0.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>170</th>\n",
       "      <td>Singapore</td>\n",
       "      <td>0.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>171</th>\n",
       "      <td>Ethiopia</td>\n",
       "      <td>0.40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>172</th>\n",
       "      <td>Ghana</td>\n",
       "      <td>0.40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>173</th>\n",
       "      <td>Solomon Islands</td>\n",
       "      <td>0.40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>174</th>\n",
       "      <td>Timor-Leste</td>\n",
       "      <td>0.30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>175</th>\n",
       "      <td>Tunisia</td>\n",
       "      <td>0.10</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>175 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                      Country  PerResident\n",
       "1               United States       101.00\n",
       "2                      Serbia        58.21\n",
       "3                       Yemen        54.80\n",
       "4                      Cyprus        36.40\n",
       "5                Saudi Arabia        35.00\n",
       "6                        Iraq        34.20\n",
       "7                     Uruguay        31.80\n",
       "8                      Norway        31.30\n",
       "9                      France        31.20\n",
       "10                     Canada        30.80\n",
       "11                    Austria        30.40\n",
       "12                    Iceland        30.30\n",
       "13                    Germany        30.30\n",
       "14                    Finland        27.30\n",
       "15                       Oman        25.50\n",
       "16                    Bahrain        24.80\n",
       "17                     Kuwait        24.80\n",
       "18                Switzerland        24.45\n",
       "19      Republic of Macedonia        24.10\n",
       "20                 Montenegro        23.10\n",
       "21                New Zealand        22.60\n",
       "22                     Greece        22.50\n",
       "23       United Arab Emirates        22.10\n",
       "24                    Croatia        21.70\n",
       "25                     Panama        21.70\n",
       "26                     Sweden        21.00\n",
       "27                    Lebanon        21.00\n",
       "28          Equatorial Guinea        19.90\n",
       "29                      Qatar        19.20\n",
       "30                     Latvia        19.00\n",
       "..                        ...          ...\n",
       "146              Burkina Faso         1.10\n",
       "147                      Chad         1.10\n",
       "148               South Korea         1.10\n",
       "149                      Mali         1.10\n",
       "150  Central African Republic         1.00\n",
       "151                Tajikistan         1.00\n",
       "152                      Togo         1.00\n",
       "153                Kyrgyzstan         0.90\n",
       "154                    Gambia         0.80\n",
       "155                Madagascar         0.80\n",
       "156                     Nepal         0.80\n",
       "157                 Lithuania         0.70\n",
       "158                    Malawi         0.70\n",
       "159                     Niger         0.70\n",
       "160                   Romania         0.70\n",
       "161                     Haiti         0.60\n",
       "162                     Japan         0.60\n",
       "163               North Korea         0.60\n",
       "164                    Rwanda         0.60\n",
       "165              Sierra Leone         0.60\n",
       "166                Bangladesh         0.50\n",
       "167                   Eritrea         0.50\n",
       "168                      Fiji         0.50\n",
       "169                 Indonesia         0.50\n",
       "170                 Singapore         0.50\n",
       "171                  Ethiopia         0.40\n",
       "172                     Ghana         0.40\n",
       "173           Solomon Islands         0.40\n",
       "174               Timor-Leste         0.30\n",
       "175                   Tunisia         0.10\n",
       "\n",
       "[175 rows x 2 columns]"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Place holder\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "## Save Cleaned Output"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df.to_csv('GunControl.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Plotting\n",
    "Create a new Dataframe dfHigh of those greater than 20, sort it in ascending orderm and plot as a Barchart"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "\n",
    "dfHigh = df[df.PerResident >= 20.0]\n",
    "\n",
    "dfHigh = dfHigh.sort_values('PerResident')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Country</th>\n",
       "      <th>PerResident</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>Lebanon</td>\n",
       "      <td>21.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Sweden</td>\n",
       "      <td>21.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>Panama</td>\n",
       "      <td>21.70</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Croatia</td>\n",
       "      <td>21.70</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>United Arab Emirates</td>\n",
       "      <td>22.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Greece</td>\n",
       "      <td>22.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>New Zealand</td>\n",
       "      <td>22.60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Montenegro</td>\n",
       "      <td>23.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Republic of Macedonia</td>\n",
       "      <td>24.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Switzerland</td>\n",
       "      <td>24.45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Kuwait</td>\n",
       "      <td>24.80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Bahrain</td>\n",
       "      <td>24.80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Oman</td>\n",
       "      <td>25.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Finland</td>\n",
       "      <td>27.30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Iceland</td>\n",
       "      <td>30.30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Germany</td>\n",
       "      <td>30.30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Austria</td>\n",
       "      <td>30.40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Canada</td>\n",
       "      <td>30.80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>France</td>\n",
       "      <td>31.20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Norway</td>\n",
       "      <td>31.30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Uruguay</td>\n",
       "      <td>31.80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Iraq</td>\n",
       "      <td>34.20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Saudi Arabia</td>\n",
       "      <td>35.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Cyprus</td>\n",
       "      <td>36.40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Yemen</td>\n",
       "      <td>54.80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Serbia</td>\n",
       "      <td>58.21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>United States</td>\n",
       "      <td>101.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  Country  PerResident\n",
       "27                Lebanon        21.00\n",
       "26                 Sweden        21.00\n",
       "25                 Panama        21.70\n",
       "24                Croatia        21.70\n",
       "23   United Arab Emirates        22.10\n",
       "22                 Greece        22.50\n",
       "21            New Zealand        22.60\n",
       "20             Montenegro        23.10\n",
       "19  Republic of Macedonia        24.10\n",
       "18            Switzerland        24.45\n",
       "17                 Kuwait        24.80\n",
       "16                Bahrain        24.80\n",
       "15                   Oman        25.50\n",
       "14                Finland        27.30\n",
       "12                Iceland        30.30\n",
       "13                Germany        30.30\n",
       "11                Austria        30.40\n",
       "10                 Canada        30.80\n",
       "9                  France        31.20\n",
       "8                  Norway        31.30\n",
       "7                 Uruguay        31.80\n",
       "6                    Iraq        34.20\n",
       "5            Saudi Arabia        35.00\n",
       "4                  Cyprus        36.40\n",
       "3                   Yemen        54.80\n",
       "2                  Serbia        58.21\n",
       "1           United States       101.00"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfHigh"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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4hvdf2HMGuRpHkYeL0/C+wdEVcVyh3SZtW/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Y0G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1wAMGKxI2ktyiTfQyhtJDCz++46wPOqr/+R9EngSNsZcBqLlardcC/g6ZQJCJtRFo6d7XOI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\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Zp0fEx4HDaT37fz4WFpQkSZIkSXPP/Lb1jRuOv1G5rOoTzWs4viZhYUFpOBw4poHJzJMj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\nJGkOOrt2/+ERsdM4805g7AXBdwF+FRFHRcQuEbF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      "text/plain": [
       "<matplotlib.figure.Figure at 0x23be2121080>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib\n",
    "matplotlib.rc('xtick',labelsize=50)\n",
    "matplotlib.rc('ytick',labelsize=50)\n",
    "\n",
    "dfHigh.plot(kind='bar',x='Country',y='PerResident', legend = True,color='green',figsize=(90,30))\n",
    "#dfHigh.plot(kind='pie',x='Country',y='PerResident',figsize=(60,60),labels=dfHigh['Country'],legend= False)\n",
    "plt.show()  # GARY don't forget to uncomment this !!!!!"
   ]
  },
  {
   "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": "3.6.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}