whos_running_for_what.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "linear-brazil",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "from nltk.metrics import edit_distance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "killing-stewart",
   "metadata": {},
   "outputs": [],
   "source": [
    "# reading csv of all candidates declared as rep or dem\n",
    "candidate_df = pd.read_csv(\"candidatelist.csv\", header=2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "downtown-airline",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>First Name</th>\n",
       "      <th>Last Name</th>\n",
       "      <th>Address 1</th>\n",
       "      <th>Address 2</th>\n",
       "      <th>City</th>\n",
       "      <th>Zip</th>\n",
       "      <th>DO</th>\n",
       "      <th>Office Title</th>\n",
       "      <th>Pseudo</th>\n",
       "      <th>District</th>\n",
       "      <th>...</th>\n",
       "      <th>Need to File</th>\n",
       "      <th>Muni</th>\n",
       "      <th>Ward</th>\n",
       "      <th>District.1</th>\n",
       "      <th>Term</th>\n",
       "      <th>Vote For</th>\n",
       "      <th>District Type</th>\n",
       "      <th>District ID</th>\n",
       "      <th>Unnamed: 20</th>\n",
       "      <th>Office ID</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Maria</td>\n",
       "      <td>McLaughlin</td>\n",
       "      <td>Philadelphia County</td>\n",
       "      <td>1901 John F Kennedy Blvd</td>\n",
       "      <td>Philadelphia</td>\n",
       "      <td>19103</td>\n",
       "      <td>1</td>\n",
       "      <td>Justice of the Supreme Court</td>\n",
       "      <td>1</td>\n",
       "      <td>COUNTYWIDE</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>101</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>10</td>\n",
       "      <td>1</td>\n",
       "      <td>COUNTYWIDE</td>\n",
       "      <td>COUNTY</td>\n",
       "      <td>NaN</td>\n",
       "      <td>130</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Paula</td>\n",
       "      <td>Patrick</td>\n",
       "      <td>Philadelphia County</td>\n",
       "      <td>7017 Sherwood Rd</td>\n",
       "      <td>Philadelphia</td>\n",
       "      <td>19151</td>\n",
       "      <td>1</td>\n",
       "      <td>Justice of the Supreme Court</td>\n",
       "      <td>1</td>\n",
       "      <td>COUNTYWIDE</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>101</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>10</td>\n",
       "      <td>1</td>\n",
       "      <td>COUNTYWIDE</td>\n",
       "      <td>COUNTY</td>\n",
       "      <td>NaN</td>\n",
       "      <td>130</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Kevin</td>\n",
       "      <td>Brobson</td>\n",
       "      <td>Dauphin County</td>\n",
       "      <td>3400 Hickory Hollow Rd</td>\n",
       "      <td>Harrisburg</td>\n",
       "      <td>17112</td>\n",
       "      <td>2</td>\n",
       "      <td>Justice of the Supreme Court</td>\n",
       "      <td>1</td>\n",
       "      <td>COUNTYWIDE</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>101</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>10</td>\n",
       "      <td>1</td>\n",
       "      <td>COUNTYWIDE</td>\n",
       "      <td>COUNTY</td>\n",
       "      <td>NaN</td>\n",
       "      <td>130</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Patricia A.</td>\n",
       "      <td>McCullough</td>\n",
       "      <td>Allegheny County</td>\n",
       "      <td>2701 Bingham Drive</td>\n",
       "      <td>Pittsburgh</td>\n",
       "      <td>15241</td>\n",
       "      <td>3</td>\n",
       "      <td>Justice of the Supreme Court</td>\n",
       "      <td>1223</td>\n",
       "      <td>COUNTYWIDE</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>215</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>10</td>\n",
       "      <td>1</td>\n",
       "      <td>COUNTYWIDE</td>\n",
       "      <td>COUNTY</td>\n",
       "      <td>NaN</td>\n",
       "      <td>130</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Jill</td>\n",
       "      <td>Beck</td>\n",
       "      <td>Allegheny County</td>\n",
       "      <td>5342 Pocusset Street</td>\n",
       "      <td>Pittsburgh</td>\n",
       "      <td>15217</td>\n",
       "      <td>1</td>\n",
       "      <td>Judge of the Superior Court</td>\n",
       "      <td>781</td>\n",
       "      <td>COUNTYWIDE</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>188</td>\n",
       "      <td>14</td>\n",
       "      <td>37</td>\n",
       "      <td>10</td>\n",
       "      <td>1</td>\n",
       "      <td>COUNTYWIDE</td>\n",
       "      <td>COUNTY</td>\n",
       "      <td>NaN</td>\n",
       "      <td>140</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    First Name   Last Name            Address 1                 Address 2  \\\n",
       "0        Maria  McLaughlin  Philadelphia County  1901 John F Kennedy Blvd   \n",
       "1        Paula     Patrick  Philadelphia County          7017 Sherwood Rd   \n",
       "2        Kevin     Brobson       Dauphin County    3400 Hickory Hollow Rd   \n",
       "3  Patricia A.  McCullough     Allegheny County        2701 Bingham Drive   \n",
       "4         Jill        Beck     Allegheny County      5342 Pocusset Street   \n",
       "\n",
       "           City    Zip  DO                  Office Title  Pseudo    District  \\\n",
       "0  Philadelphia  19103   1  Justice of the Supreme Court       1  COUNTYWIDE   \n",
       "1  Philadelphia  19151   1  Justice of the Supreme Court       1  COUNTYWIDE   \n",
       "2    Harrisburg  17112   2  Justice of the Supreme Court       1  COUNTYWIDE   \n",
       "3    Pittsburgh  15241   3  Justice of the Supreme Court    1223  COUNTYWIDE   \n",
       "4    Pittsburgh  15217   1   Judge of the Superior Court     781  COUNTYWIDE   \n",
       "\n",
       "   ... Need to File  Muni  Ward  District.1  Term  Vote For  District Type  \\\n",
       "0  ...        False   101     0           1    10         1     COUNTYWIDE   \n",
       "1  ...        False   101     0           1    10         1     COUNTYWIDE   \n",
       "2  ...        False   101     0           1    10         1     COUNTYWIDE   \n",
       "3  ...        False   215     4           4    10         1     COUNTYWIDE   \n",
       "4  ...        False   188    14          37    10         1     COUNTYWIDE   \n",
       "\n",
       "   District ID Unnamed: 20 Office ID  \n",
       "0      COUNTY          NaN       130  \n",
       "1      COUNTY          NaN       130  \n",
       "2      COUNTY          NaN       130  \n",
       "3      COUNTY          NaN       130  \n",
       "4      COUNTY          NaN       140  \n",
       "\n",
       "[5 rows x 22 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "candidate_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "consistent-johns",
   "metadata": {},
   "outputs": [],
   "source": [
    "pgh_districts = [x for x in candidate_df[\"District\"].unique() if \"PITTSBURGH\" in x and \"EAST\" not in x and \"E\" not in x]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "surgical-doubt",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "School Director                       504\n",
       "Member of Council                     466\n",
       "Judge of Election                     243\n",
       "Inspector of Election                 181\n",
       "Mayor                                 116\n",
       "Constable                             116\n",
       "Tax Collector                          96\n",
       "Commissioner                           79\n",
       "Magisterial District Judge             72\n",
       "Judge of the Court of Common Pleas     67\n",
       "Supervisor                             36\n",
       "School Director At-Large               14\n",
       "Member of County Council               11\n",
       "Auditor                                 7\n",
       "Judge of the Commonwealth Court         6\n",
       "Member of Council At-Large              6\n",
       "Judge of the Superior Court             4\n",
       "Justice of the Supreme Court            4\n",
       "Commissioner At-Large                   4\n",
       "Sheriff                                 2\n",
       "Controller                              2\n",
       "Treasurer                               1\n",
       "Name: Office Title, dtype: int64"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "candidate_df[\"Office Title\"].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "hired-landscape",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>First Name</th>\n",
       "      <th>Last Name</th>\n",
       "      <th>Address 1</th>\n",
       "      <th>Address 2</th>\n",
       "      <th>City</th>\n",
       "      <th>Zip</th>\n",
       "      <th>DO</th>\n",
       "      <th>Office Title</th>\n",
       "      <th>Pseudo</th>\n",
       "      <th>District</th>\n",
       "      <th>...</th>\n",
       "      <th>Need to File</th>\n",
       "      <th>Muni</th>\n",
       "      <th>Ward</th>\n",
       "      <th>District.1</th>\n",
       "      <th>Term</th>\n",
       "      <th>Vote For</th>\n",
       "      <th>District Type</th>\n",
       "      <th>District ID</th>\n",
       "      <th>Unnamed: 20</th>\n",
       "      <th>Office ID</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>104</th>\n",
       "      <td>Carlos A.</td>\n",
       "      <td>Thomas</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7152 Upland St.</td>\n",
       "      <td>Pittsburgh</td>\n",
       "      <td>15208</td>\n",
       "      <td>1</td>\n",
       "      <td>School Director</td>\n",
       "      <td>729</td>\n",
       "      <td>DISTRICT 1</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>188</td>\n",
       "      <td>13</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>CITY SCHOOLS</td>\n",
       "      <td>PGHSCH1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>710</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>105</th>\n",
       "      <td>Sylvia C.</td>\n",
       "      <td>Wilson</td>\n",
       "      <td>NaN</td>\n",
       "      <td>P.O.Box 4812</td>\n",
       "      <td>Pittsburgh</td>\n",
       "      <td>15206</td>\n",
       "      <td>2</td>\n",
       "      <td>School Director</td>\n",
       "      <td>714</td>\n",
       "      <td>DISTRICT 1</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>188</td>\n",
       "      <td>12</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>CITY SCHOOLS</td>\n",
       "      <td>PGHSCH1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>710</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>106</th>\n",
       "      <td>Grace</td>\n",
       "      <td>Higginbotham</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7103 Kedron St.</td>\n",
       "      <td>Pittsburgh</td>\n",
       "      <td>15208</td>\n",
       "      <td>3</td>\n",
       "      <td>School Director</td>\n",
       "      <td>726</td>\n",
       "      <td>DISTRICT 1</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>188</td>\n",
       "      <td>13</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>CITY SCHOOLS</td>\n",
       "      <td>PGHSCH1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>710</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>107</th>\n",
       "      <td>Sylvia C.</td>\n",
       "      <td>Wilson</td>\n",
       "      <td>NaN</td>\n",
       "      <td>P.O.Box 4812</td>\n",
       "      <td>Pittsburgh</td>\n",
       "      <td>15206</td>\n",
       "      <td>1</td>\n",
       "      <td>School Director</td>\n",
       "      <td>714</td>\n",
       "      <td>DISTRICT 1</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>188</td>\n",
       "      <td>12</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>CITY SCHOOLS</td>\n",
       "      <td>PGHSCH1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>710</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>108</th>\n",
       "      <td>Lamont</td>\n",
       "      <td>Frazier, Jr.</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5161 Hillcrest St.</td>\n",
       "      <td>Pittsburgh</td>\n",
       "      <td>15224</td>\n",
       "      <td>1</td>\n",
       "      <td>School Director</td>\n",
       "      <td>691</td>\n",
       "      <td>DISTRICT 3</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>188</td>\n",
       "      <td>10</td>\n",
       "      <td>19</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>CITY SCHOOLS</td>\n",
       "      <td>PGHSCH3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>710</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>689</th>\n",
       "      <td>Todd</td>\n",
       "      <td>Kosenina</td>\n",
       "      <td>NaN</td>\n",
       "      <td>47 Trotter Ln.</td>\n",
       "      <td>Clinton</td>\n",
       "      <td>15026</td>\n",
       "      <td>2</td>\n",
       "      <td>School Director</td>\n",
       "      <td>204</td>\n",
       "      <td>WEST ALLEGHENY REGION 3</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>141</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>SCH/REGION</td>\n",
       "      <td>SCH0070</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>690</th>\n",
       "      <td>Steven Russell</td>\n",
       "      <td>Pettit</td>\n",
       "      <td>NaN</td>\n",
       "      <td>420 Colt Cir</td>\n",
       "      <td>Clinton</td>\n",
       "      <td>15026</td>\n",
       "      <td>1</td>\n",
       "      <td>School Director</td>\n",
       "      <td>206</td>\n",
       "      <td>WEST ALLEGHENY REGION 3</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>141</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>SCH/REGION</td>\n",
       "      <td>SCH0070</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>691</th>\n",
       "      <td>Todd</td>\n",
       "      <td>Kosenina</td>\n",
       "      <td>NaN</td>\n",
       "      <td>47 Trotter Ln.</td>\n",
       "      <td>Clinton</td>\n",
       "      <td>15026</td>\n",
       "      <td>2</td>\n",
       "      <td>School Director</td>\n",
       "      <td>204</td>\n",
       "      <td>WEST ALLEGHENY REGION 3</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>141</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>SCH/REGION</td>\n",
       "      <td>SCH0070</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>692</th>\n",
       "      <td>Charles B.</td>\n",
       "      <td>Wade</td>\n",
       "      <td>NaN</td>\n",
       "      <td>531 Park Ave,</td>\n",
       "      <td>Clariton</td>\n",
       "      <td>15025</td>\n",
       "      <td>1</td>\n",
       "      <td>School Director</td>\n",
       "      <td>126</td>\n",
       "      <td>CLAIRTON REGION 4</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>123</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>SCH/REGION</td>\n",
       "      <td>SCH0012</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>693</th>\n",
       "      <td>Tisha</td>\n",
       "      <td>Thomas</td>\n",
       "      <td></td>\n",
       "      <td>903 Derby Ln.</td>\n",
       "      <td>N. Versailles</td>\n",
       "      <td>15137</td>\n",
       "      <td>1</td>\n",
       "      <td>School Director</td>\n",
       "      <td>502</td>\n",
       "      <td>EAST ALLEGHENY REGION 1</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>179</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>SCH/REGION</td>\n",
       "      <td>SCH0016</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1040</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>518 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         First Name     Last Name Address 1           Address 2  \\\n",
       "104       Carlos A.        Thomas       NaN     7152 Upland St.   \n",
       "105       Sylvia C.        Wilson       NaN        P.O.Box 4812   \n",
       "106           Grace  Higginbotham       NaN     7103 Kedron St.   \n",
       "107       Sylvia C.        Wilson       NaN        P.O.Box 4812   \n",
       "108          Lamont  Frazier, Jr.       NaN  5161 Hillcrest St.   \n",
       "..              ...           ...       ...                 ...   \n",
       "689            Todd      Kosenina       NaN      47 Trotter Ln.   \n",
       "690  Steven Russell        Pettit       NaN        420 Colt Cir   \n",
       "691            Todd      Kosenina       NaN      47 Trotter Ln.   \n",
       "692      Charles B.          Wade       NaN       531 Park Ave,   \n",
       "693           Tisha        Thomas                 903 Derby Ln.   \n",
       "\n",
       "              City    Zip  DO     Office Title  Pseudo  \\\n",
       "104     Pittsburgh  15208   1  School Director     729   \n",
       "105     Pittsburgh  15206   2  School Director     714   \n",
       "106     Pittsburgh  15208   3  School Director     726   \n",
       "107     Pittsburgh  15206   1  School Director     714   \n",
       "108     Pittsburgh  15224   1  School Director     691   \n",
       "..             ...    ...  ..              ...     ...   \n",
       "689        Clinton  15026   2  School Director     204   \n",
       "690        Clinton  15026   1  School Director     206   \n",
       "691        Clinton  15026   2  School Director     204   \n",
       "692       Clariton  15025   1  School Director     126   \n",
       "693  N. Versailles  15137   1  School Director     502   \n",
       "\n",
       "                    District  ... Need to File  Muni  Ward  District.1  Term  \\\n",
       "104               DISTRICT 1  ...        False   188    13           4     4   \n",
       "105               DISTRICT 1  ...        False   188    12           5     4   \n",
       "106               DISTRICT 1  ...        False   188    13           1     4   \n",
       "107               DISTRICT 1  ...        False   188    12           5     4   \n",
       "108               DISTRICT 3  ...        False   188    10          19     4   \n",
       "..                       ...  ...          ...   ...   ...         ...   ...   \n",
       "689  WEST ALLEGHENY REGION 3  ...        False   141     0           1     4   \n",
       "690  WEST ALLEGHENY REGION 3  ...        False   141     0           3     4   \n",
       "691  WEST ALLEGHENY REGION 3  ...        False   141     0           1     4   \n",
       "692        CLAIRTON REGION 4  ...        False   123     4           2     4   \n",
       "693  EAST ALLEGHENY REGION 1  ...        False   179     7           0     4   \n",
       "\n",
       "     Vote For  District Type  District ID Unnamed: 20 Office ID  \n",
       "104         1   CITY SCHOOLS      PGHSCH1         NaN       710  \n",
       "105         1   CITY SCHOOLS      PGHSCH1         NaN       710  \n",
       "106         1   CITY SCHOOLS      PGHSCH1         NaN       710  \n",
       "107         1   CITY SCHOOLS      PGHSCH1         NaN       710  \n",
       "108         1   CITY SCHOOLS      PGHSCH3         NaN       710  \n",
       "..        ...            ...          ...         ...       ...  \n",
       "689         1     SCH/REGION      SCH0070         NaN      1000  \n",
       "690         1     SCH/REGION      SCH0070         NaN      1000  \n",
       "691         1     SCH/REGION      SCH0070         NaN      1000  \n",
       "692         1     SCH/REGION      SCH0012         NaN      1010  \n",
       "693         1     SCH/REGION      SCH0016         NaN      1040  \n",
       "\n",
       "[518 rows x 22 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "candidate_df[candidate_df[\"Office Title\"].isin([\"School Director\",\"School Director At-Large\"])]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "transsexual-valve",
   "metadata": {},
   "source": [
    "# Taking a look at School Directors\n",
    "## Data Cleaning"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "suited-saturn",
   "metadata": {},
   "outputs": [],
   "source": [
    "school_df = candidate_df[candidate_df[\"Office Title\"].isin([\"School Director\",\"School Director At-Large\"])]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "revolutionary-bridge",
   "metadata": {},
   "outputs": [],
   "source": [
    "#lets not bother w pittsburgh\n",
    "school_df = school_df[school_df[\"District\"].isin(pgh_districts) == False]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "foreign-creation",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "PLUM                       26\n",
       "MCKEESPORT AREA            24\n",
       "MOON AREA                  22\n",
       "GATEWAY                    21\n",
       "MT LEBANON                 20\n",
       "                           ..\n",
       "STO-ROX REGION 1            1\n",
       "WOODLAND HILLS REGION 2     1\n",
       "EAST ALLEGHENY REGION 1     1\n",
       "CLAIRTON REGION 4           1\n",
       "CLAIRTON REGION 3           1\n",
       "Name: District, Length: 72, dtype: int64"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "school_df[\"District\"].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "moving-portugal",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>First Name</th>\n",
       "      <th>Last Name</th>\n",
       "      <th>Address 1</th>\n",
       "      <th>Address 2</th>\n",
       "      <th>City</th>\n",
       "      <th>Zip</th>\n",
       "      <th>DO</th>\n",
       "      <th>Office Title</th>\n",
       "      <th>Pseudo</th>\n",
       "      <th>District</th>\n",
       "      <th>...</th>\n",
       "      <th>Need to File</th>\n",
       "      <th>Muni</th>\n",
       "      <th>Ward</th>\n",
       "      <th>District.1</th>\n",
       "      <th>Term</th>\n",
       "      <th>Vote For</th>\n",
       "      <th>District Type</th>\n",
       "      <th>District ID</th>\n",
       "      <th>Unnamed: 20</th>\n",
       "      <th>Office ID</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>104</th>\n",
       "      <td>Carlos A.</td>\n",
       "      <td>Thomas</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7152 Upland St.</td>\n",
       "      <td>Pittsburgh</td>\n",
       "      <td>15208</td>\n",
       "      <td>1</td>\n",
       "      <td>School Director</td>\n",
       "      <td>729</td>\n",
       "      <td>DISTRICT 1</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>188</td>\n",
       "      <td>13</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>CITY SCHOOLS</td>\n",
       "      <td>PGHSCH1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>710</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>105</th>\n",
       "      <td>Sylvia C.</td>\n",
       "      <td>Wilson</td>\n",
       "      <td>NaN</td>\n",
       "      <td>P.O.Box 4812</td>\n",
       "      <td>Pittsburgh</td>\n",
       "      <td>15206</td>\n",
       "      <td>2</td>\n",
       "      <td>School Director</td>\n",
       "      <td>714</td>\n",
       "      <td>DISTRICT 1</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>188</td>\n",
       "      <td>12</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>CITY SCHOOLS</td>\n",
       "      <td>PGHSCH1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>710</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>106</th>\n",
       "      <td>Grace</td>\n",
       "      <td>Higginbotham</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7103 Kedron St.</td>\n",
       "      <td>Pittsburgh</td>\n",
       "      <td>15208</td>\n",
       "      <td>3</td>\n",
       "      <td>School Director</td>\n",
       "      <td>726</td>\n",
       "      <td>DISTRICT 1</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>188</td>\n",
       "      <td>13</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>CITY SCHOOLS</td>\n",
       "      <td>PGHSCH1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>710</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>107</th>\n",
       "      <td>Sylvia C.</td>\n",
       "      <td>Wilson</td>\n",
       "      <td>NaN</td>\n",
       "      <td>P.O.Box 4812</td>\n",
       "      <td>Pittsburgh</td>\n",
       "      <td>15206</td>\n",
       "      <td>1</td>\n",
       "      <td>School Director</td>\n",
       "      <td>714</td>\n",
       "      <td>DISTRICT 1</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>188</td>\n",
       "      <td>12</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>CITY SCHOOLS</td>\n",
       "      <td>PGHSCH1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>710</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>108</th>\n",
       "      <td>Lamont</td>\n",
       "      <td>Frazier, Jr.</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5161 Hillcrest St.</td>\n",
       "      <td>Pittsburgh</td>\n",
       "      <td>15224</td>\n",
       "      <td>1</td>\n",
       "      <td>School Director</td>\n",
       "      <td>691</td>\n",
       "      <td>DISTRICT 3</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>188</td>\n",
       "      <td>10</td>\n",
       "      <td>19</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>CITY SCHOOLS</td>\n",
       "      <td>PGHSCH3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>710</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    First Name     Last Name Address 1           Address 2        City    Zip  \\\n",
       "104  Carlos A.        Thomas       NaN     7152 Upland St.  Pittsburgh  15208   \n",
       "105  Sylvia C.        Wilson       NaN        P.O.Box 4812  Pittsburgh  15206   \n",
       "106      Grace  Higginbotham       NaN     7103 Kedron St.  Pittsburgh  15208   \n",
       "107  Sylvia C.        Wilson       NaN        P.O.Box 4812  Pittsburgh  15206   \n",
       "108     Lamont  Frazier, Jr.       NaN  5161 Hillcrest St.  Pittsburgh  15224   \n",
       "\n",
       "     DO     Office Title  Pseudo    District  ... Need to File  Muni  Ward  \\\n",
       "104   1  School Director     729  DISTRICT 1  ...        False   188    13   \n",
       "105   2  School Director     714  DISTRICT 1  ...        False   188    12   \n",
       "106   3  School Director     726  DISTRICT 1  ...        False   188    13   \n",
       "107   1  School Director     714  DISTRICT 1  ...        False   188    12   \n",
       "108   1  School Director     691  DISTRICT 3  ...        False   188    10   \n",
       "\n",
       "     District.1  Term  Vote For  District Type  District ID Unnamed: 20  \\\n",
       "104           4     4         1   CITY SCHOOLS      PGHSCH1         NaN   \n",
       "105           5     4         1   CITY SCHOOLS      PGHSCH1         NaN   \n",
       "106           1     4         1   CITY SCHOOLS      PGHSCH1         NaN   \n",
       "107           5     4         1   CITY SCHOOLS      PGHSCH1         NaN   \n",
       "108          19     4         1   CITY SCHOOLS      PGHSCH3         NaN   \n",
       "\n",
       "    Office ID  \n",
       "104       710  \n",
       "105       710  \n",
       "106       710  \n",
       "107       710  \n",
       "108       710  \n",
       "\n",
       "[5 rows x 22 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# this is way too many columns\n",
    "school_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "emerging-fabric",
   "metadata": {},
   "outputs": [],
   "source": [
    "school_indices = list(school_df.index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "decimal-spell",
   "metadata": {},
   "outputs": [],
   "source": [
    "school_cleaned = pd.DataFrame()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "thrown-technical",
   "metadata": {},
   "outputs": [],
   "source": [
    "name = []\n",
    "party = []\n",
    "district = []\n",
    "for i in school_indices:\n",
    "    row = school_df[school_df.index==i]\n",
    "    name.append(row[\"First Name\"].to_string(index=False) + \" \" + row[\"Last Name\"].to_string(index=False))\n",
    "    party.append(row[\"Party\"].to_string(index=False))\n",
    "    district.append(row[\"District\"].to_string(index=False))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "greater-tuner",
   "metadata": {},
   "outputs": [],
   "source": [
    "district2 = []\n",
    "ward = []\n",
    "for x in district:\n",
    "    if \"REGION\" in x:\n",
    "        parts = x.split(\"REGION\")\n",
    "        ward.append(int(parts[-1]))\n",
    "        district2.append(' '.join(parts[:-1]).strip())\n",
    "    else:\n",
    "        ward.append(np.nan)\n",
    "        district2.append(x)\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "suspected-flash",
   "metadata": {},
   "outputs": [],
   "source": [
    "district3 = []\n",
    "for x in district2:\n",
    "    if x == \"PINE RICHLAND\":\n",
    "        district3.append(\"PINE-RICHLAND\")\n",
    "    else:\n",
    "        district3.append(x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "brief-shoulder",
   "metadata": {},
   "outputs": [],
   "source": [
    "school_cleaned[\"name\"] = name\n",
    "school_cleaned[\"party\"] = party\n",
    "school_cleaned[\"district\"] = district3\n",
    "school_cleaned[\"ward\"] = ward"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "requested-strike",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>party</th>\n",
       "      <th>district</th>\n",
       "      <th>ward</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Carlos A. Thomas</td>\n",
       "      <td>Democratic</td>\n",
       "      <td>DISTRICT 1</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Sylvia C. Wilson</td>\n",
       "      <td>Democratic</td>\n",
       "      <td>DISTRICT 1</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Grace Higginbotham</td>\n",
       "      <td>Democratic</td>\n",
       "      <td>DISTRICT 1</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Sylvia C. Wilson</td>\n",
       "      <td>Republican</td>\n",
       "      <td>DISTRICT 1</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Lamont Frazier, Jr.</td>\n",
       "      <td>Democratic</td>\n",
       "      <td>DISTRICT 3</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  name       party    district  ward\n",
       "0     Carlos A. Thomas  Democratic  DISTRICT 1   NaN\n",
       "1     Sylvia C. Wilson  Democratic  DISTRICT 1   NaN\n",
       "2   Grace Higginbotham  Democratic  DISTRICT 1   NaN\n",
       "3     Sylvia C. Wilson  Republican  DISTRICT 1   NaN\n",
       "4  Lamont Frazier, Jr.  Democratic  DISTRICT 3   NaN"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "school_cleaned.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "detailed-identity",
   "metadata": {},
   "outputs": [],
   "source": [
    "school_pos_df = pd.read_csv(\"schoolpos.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "third-ottawa",
   "metadata": {},
   "outputs": [],
   "source": [
    "school_pos_df.columns = [\"num\",\"district\",\"term\",\"ward\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "electronic-congo",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>num</th>\n",
       "      <th>district</th>\n",
       "      <th>term</th>\n",
       "      <th>ward</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>4</td>\n",
       "      <td>ALLEGHENY VALLEY</td>\n",
       "      <td>4-year</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4</td>\n",
       "      <td>AVONWORTH</td>\n",
       "      <td>4-year</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>4</td>\n",
       "      <td>BALDWIN-WHITEHALL</td>\n",
       "      <td>4-year</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>BETHEL PARK</td>\n",
       "      <td>4-year</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>BRENTWOOD</td>\n",
       "      <td>4-year</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   num           district    term ward\n",
       "0    4   ALLEGHENY VALLEY  4-year  NaN\n",
       "1    4          AVONWORTH  4-year  NaN\n",
       "2    4  BALDWIN-WHITEHALL  4-year  NaN\n",
       "3    4        BETHEL PARK  4-year  NaN\n",
       "4    4          BRENTWOOD  4-year  NaN"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "school_pos_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "intermediate-booth",
   "metadata": {},
   "outputs": [],
   "source": [
    "school_pos_df.term = school_pos_df.term.map(lambda x: int(x.split(\"-\")[0]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "bizarre-response",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>num</th>\n",
       "      <th>district</th>\n",
       "      <th>term</th>\n",
       "      <th>ward</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>4</td>\n",
       "      <td>ALLEGHENY VALLEY</td>\n",
       "      <td>4</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4</td>\n",
       "      <td>AVONWORTH</td>\n",
       "      <td>4</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>4</td>\n",
       "      <td>BALDWIN-WHITEHALL</td>\n",
       "      <td>4</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>BETHEL PARK</td>\n",
       "      <td>4</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>BRENTWOOD</td>\n",
       "      <td>4</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   num           district  term ward\n",
       "0    4   ALLEGHENY VALLEY     4  NaN\n",
       "1    4          AVONWORTH     4  NaN\n",
       "2    4  BALDWIN-WHITEHALL     4  NaN\n",
       "3    4        BETHEL PARK     4  NaN\n",
       "4    4          BRENTWOOD     4  NaN"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "school_pos_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "educated-compact",
   "metadata": {},
   "outputs": [],
   "source": [
    "school_pos_cleaned = school_pos_df[school_pos_df.ward.notna()==False]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "european-apple",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>num</th>\n",
       "      <th>district</th>\n",
       "      <th>term</th>\n",
       "      <th>ward</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>4</td>\n",
       "      <td>ALLEGHENY VALLEY</td>\n",
       "      <td>4</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4</td>\n",
       "      <td>AVONWORTH</td>\n",
       "      <td>4</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>4</td>\n",
       "      <td>BALDWIN-WHITEHALL</td>\n",
       "      <td>4</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>BETHEL PARK</td>\n",
       "      <td>4</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>BRENTWOOD</td>\n",
       "      <td>4</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   num           district  term ward\n",
       "0    4   ALLEGHENY VALLEY     4  NaN\n",
       "1    4          AVONWORTH     4  NaN\n",
       "2    4  BALDWIN-WHITEHALL     4  NaN\n",
       "3    4        BETHEL PARK     4  NaN\n",
       "4    4          BRENTWOOD     4  NaN"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "school_pos_cleaned.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "reduced-clinic",
   "metadata": {},
   "outputs": [],
   "source": [
    "schoolward_df = school_pos_df[school_pos_df.ward.notna()==True]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "organic-prompt",
   "metadata": {},
   "outputs": [],
   "source": [
    "def dewardify(ward_df):\n",
    "    row_list = []\n",
    "    for row in range(len(ward_df)):\n",
    "        regions = ward_df.iloc[[row]].ward.values[0].split(\",\")\n",
    "        num = int(ward_df.iloc[row,0])//len(regions)\n",
    "        if len(regions)>1:\n",
    "            for x in regions:\n",
    "                temp_dict = {\n",
    "                    \"num\": num, \n",
    "                    \"district\": ward_df.iloc[row,1],\n",
    "                    \"term\": ward_df.iloc[row,2],\n",
    "                    \"ward\": x\n",
    "                }\n",
    "                row_list.append(temp_dict)  \n",
    "        else:\n",
    "            temp_dict = {\n",
    "                \"num\": ward_df.iloc[row,0], \n",
    "                \"district\": ward_df.iloc[row,1],\n",
    "                \"term\": ward_df.iloc[row,2],\n",
    "                \"ward\": ward_df.iloc[row,3]\n",
    "                }\n",
    "            row_list.append(temp_dict)  \n",
    "    return row_list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "marked-morrison",
   "metadata": {},
   "outputs": [],
   "source": [
    "row_list = dewardify(schoolward_df)\n",
    "#row_list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "direct-puppy",
   "metadata": {},
   "outputs": [],
   "source": [
    "school_pos_cleaned = school_pos_cleaned.append(row_list)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "informational-finder",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1           15\n",
       "3           14\n",
       "2           12\n",
       "7            2\n",
       "4            2\n",
       "at-large     2\n",
       "9            2\n",
       "5            1\n",
       "Name: ward, dtype: int64"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "school_pos_cleaned.ward.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "short-exercise",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>num</th>\n",
       "      <th>district</th>\n",
       "      <th>term</th>\n",
       "      <th>ward</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>4</td>\n",
       "      <td>ALLEGHENY VALLEY</td>\n",
       "      <td>4</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4</td>\n",
       "      <td>AVONWORTH</td>\n",
       "      <td>4</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>4</td>\n",
       "      <td>BALDWIN-WHITEHALL</td>\n",
       "      <td>4</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>BETHEL PARK</td>\n",
       "      <td>4</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>BRENTWOOD</td>\n",
       "      <td>4</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>2</td>\n",
       "      <td>WEST ALLEGHENY</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>1</td>\n",
       "      <td>WOODLAND HILLS</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>1</td>\n",
       "      <td>WOODLAND HILLS</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>2</td>\n",
       "      <td>WOODLAND HILLS</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>1</td>\n",
       "      <td>WOODLAND HILLS</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>82 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    num           district  term ward\n",
       "0     4   ALLEGHENY VALLEY     4  NaN\n",
       "1     4          AVONWORTH     4  NaN\n",
       "2     4  BALDWIN-WHITEHALL     4  NaN\n",
       "3     4        BETHEL PARK     4  NaN\n",
       "4     4          BRENTWOOD     4  NaN\n",
       "..  ...                ...   ...  ...\n",
       "45    2     WEST ALLEGHENY     4    2\n",
       "46    1     WOODLAND HILLS     4    1\n",
       "47    1     WOODLAND HILLS     4    2\n",
       "48    2     WOODLAND HILLS     4    3\n",
       "49    1     WOODLAND HILLS     2    1\n",
       "\n",
       "[82 rows x 4 columns]"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "school_pos_cleaned"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "periodic-active",
   "metadata": {},
   "outputs": [],
   "source": [
    "school_pos_cleaned = school_pos_cleaned[school_pos_cleaned.district != \"PITTSBURGH\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "drawn-incident",
   "metadata": {},
   "source": [
    "## Data Analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "dominican-present",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>party</th>\n",
       "      <th>district</th>\n",
       "      <th>ward</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Carlos A. Thomas</td>\n",
       "      <td>Democratic</td>\n",
       "      <td>DISTRICT 1</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Sylvia C. Wilson</td>\n",
       "      <td>Democratic</td>\n",
       "      <td>DISTRICT 1</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Grace Higginbotham</td>\n",
       "      <td>Democratic</td>\n",
       "      <td>DISTRICT 1</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Sylvia C. Wilson</td>\n",
       "      <td>Republican</td>\n",
       "      <td>DISTRICT 1</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Lamont Frazier, Jr.</td>\n",
       "      <td>Democratic</td>\n",
       "      <td>DISTRICT 3</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  name       party    district  ward\n",
       "0     Carlos A. Thomas  Democratic  DISTRICT 1   NaN\n",
       "1     Sylvia C. Wilson  Democratic  DISTRICT 1   NaN\n",
       "2   Grace Higginbotham  Democratic  DISTRICT 1   NaN\n",
       "3     Sylvia C. Wilson  Republican  DISTRICT 1   NaN\n",
       "4  Lamont Frazier, Jr.  Democratic  DISTRICT 3   NaN"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "school_cleaned.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "intellectual-shareware",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "PLUM                    26\n",
       "MCKEESPORT AREA         24\n",
       "MOON AREA               22\n",
       "GATEWAY                 21\n",
       "SHALER AREA             20\n",
       "MT LEBANON              20\n",
       "PINE-RICHLAND           18\n",
       "AVONWORTH               17\n",
       "NORTHGATE               16\n",
       "NORTH ALLEGHENY         16\n",
       "NORTH HILLS             16\n",
       "CHARTIERS VALLEY        15\n",
       "WEST MIFFLIN AREA       14\n",
       "BETHEL PARK             14\n",
       "SOUTH ALLEGHENY         12\n",
       "RIVERVIEW               12\n",
       "PENN HILLS              12\n",
       "QUAKER VALLEY           12\n",
       "WILKINSBURG             11\n",
       "FOX CHAPEL              11\n",
       "WEST ALLEGHENY          11\n",
       "BRENTWOOD               10\n",
       "DEER LAKES              10\n",
       "STO-ROX                 10\n",
       "UPPER SAINT CLAIR       10\n",
       "CARLYNTON               10\n",
       "KEYSTONE OAKS            9\n",
       "WOODLAND HILLS           9\n",
       "HIGHLANDS                8\n",
       "HAMPTON                  8\n",
       "MONTOUR                  8\n",
       "SOUTH FAYETTE            8\n",
       "ALLEGHENY VALLEY         8\n",
       "SOUTH PARK               8\n",
       "BALDWIN WHITEHALL        8\n",
       "ELIZABETH FORWARD        8\n",
       "WEST JEFFERSON HILLS     8\n",
       "CLAIRTON                 7\n",
       "STEEL VALLEY             7\n",
       "DISTRICT 9               4\n",
       "EAST ALLEGHENY           4\n",
       "DISTRICT 1               4\n",
       "DISTRICT 5               3\n",
       "DUQUESNE                 3\n",
       "CORNELL                  2\n",
       "DISTRICT 7               2\n",
       "DISTRICT 3               2\n",
       "Name: district, dtype: int64"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "school_cleaned.district.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "sharp-spectacular",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "CLAIRTON                5\n",
       "EAST ALLEGHENY          5\n",
       "STO-ROX                 5\n",
       "WOODLAND HILLS          4\n",
       "FOX CHAPEL AREA         4\n",
       "SHALER AREA             3\n",
       "PINE-RICHLAND           3\n",
       "WEST ALLEGHENY          3\n",
       "HIGHLANDS               3\n",
       "QUAKER VALLEY           3\n",
       "KEYSTONE OAKS           3\n",
       "MONTOUR                 2\n",
       "STEEL VALLEY            2\n",
       "CHARTIERS VALLEY        2\n",
       "SOUTH ALLEGHENY         2\n",
       "BRENTWOOD               2\n",
       "NORTHGATE               1\n",
       "MOUNT LEBANON           1\n",
       "BALDWIN-WHITEHALL       1\n",
       "PENN HILLS              1\n",
       "GATEWAY                 1\n",
       "WEST JEFFERSON HILLS    1\n",
       "WILKINSBURG             1\n",
       "HAMPTON                 1\n",
       "AVONWORTH               1\n",
       "DEER LAKES              1\n",
       "MCKEESPORT AREA         1\n",
       "CORNELL                 1\n",
       "DUQUESNE                1\n",
       "UPPER ST. CLAIR         1\n",
       "ELIZABETH-FORWARD       1\n",
       "NORTH HILLS             1\n",
       "ALLEGHENY VALLEY        1\n",
       "RIVERVIEW               1\n",
       "SOUTH PARK              1\n",
       "SOUTH FAYETTE           1\n",
       "NORTH ALLEGHENY         1\n",
       "BETHEL PARK             1\n",
       "WEST MIFFLIN AREA       1\n",
       "CARLYNTON               1\n",
       "PLUM                    1\n",
       "MOON AREA               1\n",
       "Name: district, dtype: int64"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "school_pos_cleaned.district.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "pleasant-stable",
   "metadata": {},
   "outputs": [],
   "source": [
    "no_candidates = []\n",
    "for dis in school_pos_cleaned.district:\n",
    "    if dis not in list(school_cleaned.district):\n",
    "        no_candidates.append(dis)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "subject-somerset",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Baldwin-whitehall\n",
      "Elizabeth-forward\n",
      "Fox chapel area\n",
      "Mount lebanon\n",
      "Upper st. clair\n"
     ]
    }
   ],
   "source": [
    "no_candidates = list(set(no_candidates))\n",
    "no_candidates = [x.capitalize() for x in no_candidates]\n",
    "for x in sorted(no_candidates):\n",
    "    print(x)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "interior-utility",
   "metadata": {},
   "source": [
    "# Municipality Data\n",
    "## Data Cleaning"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "secondary-george",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "MUNICIPAL         695\n",
       "SPECPREC          424\n",
       "SCHOOL            383\n",
       "WARD              222\n",
       "SCH/REGION        120\n",
       "COUNTYWIDE         83\n",
       "MAGISTERIAL        72\n",
       "CITY SCHOOLS       15\n",
       "COUNTY COUNCIL     11\n",
       "CITY COUNCIL        6\n",
       "CITYWIDE            4\n",
       "DISTRICT            2\n",
       "Name: District Type, dtype: int64"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "candidate_df[\"District Type\"].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "usual-mayor",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Member of Council             331\n",
       "Mayor                         112\n",
       "Tax Collector                  96\n",
       "Constable                      64\n",
       "Commissioner                   38\n",
       "Supervisor                     34\n",
       "Auditor                         7\n",
       "Member of Council At-Large      6\n",
       "Commissioner At-Large           4\n",
       "Controller                      2\n",
       "Treasurer                       1\n",
       "Name: Office Title, dtype: int64"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#include\n",
    "candidate_df[candidate_df[\"District Type\"]==\"MUNICIPAL\"][\"Office Title\"].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "informative-semester",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>First Name</th>\n",
       "      <th>Last Name</th>\n",
       "      <th>Address 1</th>\n",
       "      <th>Address 2</th>\n",
       "      <th>City</th>\n",
       "      <th>Zip</th>\n",
       "      <th>DO</th>\n",
       "      <th>Office Title</th>\n",
       "      <th>Pseudo</th>\n",
       "      <th>District</th>\n",
       "      <th>...</th>\n",
       "      <th>Need to File</th>\n",
       "      <th>Muni</th>\n",
       "      <th>Ward</th>\n",
       "      <th>District.1</th>\n",
       "      <th>Term</th>\n",
       "      <th>Vote For</th>\n",
       "      <th>District Type</th>\n",
       "      <th>District ID</th>\n",
       "      <th>Unnamed: 20</th>\n",
       "      <th>Office ID</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>904</th>\n",
       "      <td>Joseph</td>\n",
       "      <td>Senko</td>\n",
       "      <td>NaN</td>\n",
       "      <td>700 Bower Hill Rd., Apt. 7112</td>\n",
       "      <td>Pittsburgh</td>\n",
       "      <td>15234</td>\n",
       "      <td>1</td>\n",
       "      <td>Treasurer</td>\n",
       "      <td>426</td>\n",
       "      <td>MT LEBANON</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>173</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>MUNICIPAL</td>\n",
       "      <td>MUN173</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1650</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    First Name Last Name Address 1                      Address 2        City  \\\n",
       "904     Joseph     Senko       NaN  700 Bower Hill Rd., Apt. 7112  Pittsburgh   \n",
       "\n",
       "       Zip  DO Office Title  Pseudo    District  ... Need to File  Muni  Ward  \\\n",
       "904  15234   1    Treasurer     426  MT LEBANON  ...        False   173     1   \n",
       "\n",
       "     District.1  Term  Vote For  District Type  District ID Unnamed: 20  \\\n",
       "904           6     4         1      MUNICIPAL      MUN173          NaN   \n",
       "\n",
       "    Office ID  \n",
       "904      1650  \n",
       "\n",
       "[1 rows x 22 columns]"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "candidate_df[candidate_df[\"Office Title\"]==\"Treasurer\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "guided-annual",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Judge of Election        243\n",
       "Inspector of Election    181\n",
       "Name: Office Title, dtype: int64"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# do not include\n",
    "candidate_df[candidate_df[\"District Type\"]==\"SPECPREC\"][\"Office Title\"].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "tested-insertion",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Member of Council    129\n",
       "Constable             52\n",
       "Commissioner          41\n",
       "Name: Office Title, dtype: int64"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# include\n",
    "candidate_df[candidate_df[\"District Type\"]==\"WARD\"][\"Office Title\"].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "atmospheric-investment",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "School Director    120\n",
       "Name: Office Title, dtype: int64"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# do not include\n",
    "candidate_df[candidate_df[\"District Type\"]==\"SCH/REGION\"][\"Office Title\"].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "focused-sunday",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>First Name</th>\n",
       "      <th>Last Name</th>\n",
       "      <th>Address 1</th>\n",
       "      <th>Address 2</th>\n",
       "      <th>City</th>\n",
       "      <th>Zip</th>\n",
       "      <th>DO</th>\n",
       "      <th>Office Title</th>\n",
       "      <th>Pseudo</th>\n",
       "      <th>District</th>\n",
       "      <th>...</th>\n",
       "      <th>Need to File</th>\n",
       "      <th>Muni</th>\n",
       "      <th>Ward</th>\n",
       "      <th>District.1</th>\n",
       "      <th>Term</th>\n",
       "      <th>Vote For</th>\n",
       "      <th>District Type</th>\n",
       "      <th>District ID</th>\n",
       "      <th>Unnamed: 20</th>\n",
       "      <th>Office ID</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1495</th>\n",
       "      <td>John A.</td>\n",
       "      <td>Marshall</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4149 Glasgow Rd.</td>\n",
       "      <td>Valencia</td>\n",
       "      <td>16059</td>\n",
       "      <td>1</td>\n",
       "      <td>Supervisor</td>\n",
       "      <td>1030</td>\n",
       "      <td>Richland 1</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>194</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>DISTRICT</td>\n",
       "      <td>Richland1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2085</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1496</th>\n",
       "      <td>Ann M.</td>\n",
       "      <td>Miller</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1028 Applejack Dr.</td>\n",
       "      <td>Gibsonia</td>\n",
       "      <td>15044</td>\n",
       "      <td>1</td>\n",
       "      <td>Supervisor</td>\n",
       "      <td>1031</td>\n",
       "      <td>Richland 2</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>194</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>DISTRICT</td>\n",
       "      <td>Richland2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2085</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     First Name Last Name Address 1           Address 2      City    Zip  DO  \\\n",
       "1495    John A.  Marshall       NaN    4149 Glasgow Rd.  Valencia  16059   1   \n",
       "1496     Ann M.    Miller       NaN  1028 Applejack Dr.  Gibsonia  15044   1   \n",
       "\n",
       "     Office Title  Pseudo    District  ... Need to File  Muni  Ward  \\\n",
       "1495   Supervisor    1030  Richland 1  ...        False   194     0   \n",
       "1496   Supervisor    1031  Richland 2  ...        False   194     0   \n",
       "\n",
       "      District.1  Term  Vote For  District Type  District ID Unnamed: 20  \\\n",
       "1495           1     4         1       DISTRICT    Richland1         NaN   \n",
       "1496           2     4         1       DISTRICT    Richland2         NaN   \n",
       "\n",
       "     Office ID  \n",
       "1495      2085  \n",
       "1496      2085  \n",
       "\n",
       "[2 rows x 22 columns]"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# include\n",
    "candidate_df[candidate_df[\"District Type\"]==\"DISTRICT\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "comparative-casino",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>First Name</th>\n",
       "      <th>Last Name</th>\n",
       "      <th>Address 1</th>\n",
       "      <th>Address 2</th>\n",
       "      <th>City</th>\n",
       "      <th>Zip</th>\n",
       "      <th>DO</th>\n",
       "      <th>Office Title</th>\n",
       "      <th>Pseudo</th>\n",
       "      <th>District</th>\n",
       "      <th>...</th>\n",
       "      <th>Need to File</th>\n",
       "      <th>Muni</th>\n",
       "      <th>Ward</th>\n",
       "      <th>District.1</th>\n",
       "      <th>Term</th>\n",
       "      <th>Vote For</th>\n",
       "      <th>District Type</th>\n",
       "      <th>District ID</th>\n",
       "      <th>Unnamed: 20</th>\n",
       "      <th>Office ID</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>954</th>\n",
       "      <td>Arthur</td>\n",
       "      <td>Buccigrossi III</td>\n",
       "      <td>NaN</td>\n",
       "      <td>971 Glen Hays Drive</td>\n",
       "      <td>Crescent</td>\n",
       "      <td>15046</td>\n",
       "      <td>1</td>\n",
       "      <td>Commissioner</td>\n",
       "      <td>148</td>\n",
       "      <td>CRESCENT WARD 2</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>127</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>WARD</td>\n",
       "      <td>WRD1002</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1945</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>955</th>\n",
       "      <td>Ed</td>\n",
       "      <td>Kissel</td>\n",
       "      <td>NaN</td>\n",
       "      <td>406 Marion St.</td>\n",
       "      <td>Creighton</td>\n",
       "      <td>15030</td>\n",
       "      <td>1</td>\n",
       "      <td>Commissioner</td>\n",
       "      <td>173</td>\n",
       "      <td>EAST DEER WARD 2</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>131</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>WARD</td>\n",
       "      <td>WRD1202</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1945</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>956</th>\n",
       "      <td>Kyle A.</td>\n",
       "      <td>Walk</td>\n",
       "      <td>NaN</td>\n",
       "      <td>609 Oberdick Dr.</td>\n",
       "      <td>McKeesport</td>\n",
       "      <td>15135</td>\n",
       "      <td>1</td>\n",
       "      <td>Commissioner</td>\n",
       "      <td>188</td>\n",
       "      <td>ELIZABETH TOWNSHIP WARD 2</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>137</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>WARD</td>\n",
       "      <td>WRD1402</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1945</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>957</th>\n",
       "      <td>Kevin R.</td>\n",
       "      <td>Cunningham</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2029 Country Club Dr.</td>\n",
       "      <td>McKeesport</td>\n",
       "      <td>15135</td>\n",
       "      <td>1</td>\n",
       "      <td>Commissioner</td>\n",
       "      <td>190</td>\n",
       "      <td>ELIZABETH TOWNSHIP WARD 4</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>137</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>WARD</td>\n",
       "      <td>WRD1404</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1945</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>958</th>\n",
       "      <td>Joshua Michael</td>\n",
       "      <td>Walls</td>\n",
       "      <td>NaN</td>\n",
       "      <td>208 Duncan Station Rd.</td>\n",
       "      <td>McKeesport</td>\n",
       "      <td>15135</td>\n",
       "      <td>1</td>\n",
       "      <td>Commissioner</td>\n",
       "      <td>191</td>\n",
       "      <td>ELIZABETH TOWNSHIP WARD 4</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>137</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>WARD</td>\n",
       "      <td>WRD1404</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1945</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         First Name        Last Name Address 1               Address 2  \\\n",
       "954          Arthur  Buccigrossi III       NaN     971 Glen Hays Drive   \n",
       "955              Ed           Kissel       NaN          406 Marion St.   \n",
       "956         Kyle A.             Walk       NaN        609 Oberdick Dr.   \n",
       "957        Kevin R.       Cunningham       NaN   2029 Country Club Dr.   \n",
       "958  Joshua Michael            Walls       NaN  208 Duncan Station Rd.   \n",
       "\n",
       "           City    Zip  DO  Office Title  Pseudo                   District  \\\n",
       "954    Crescent  15046   1  Commissioner     148            CRESCENT WARD 2   \n",
       "955   Creighton  15030   1  Commissioner     173           EAST DEER WARD 2   \n",
       "956  McKeesport  15135   1  Commissioner     188  ELIZABETH TOWNSHIP WARD 2   \n",
       "957  McKeesport  15135   1  Commissioner     190  ELIZABETH TOWNSHIP WARD 4   \n",
       "958  McKeesport  15135   1  Commissioner     191  ELIZABETH TOWNSHIP WARD 4   \n",
       "\n",
       "     ... Need to File  Muni  Ward  District.1  Term  Vote For  District Type  \\\n",
       "954  ...        False   127     2           0     4         1           WARD   \n",
       "955  ...        False   131     2           0     4         1           WARD   \n",
       "956  ...        False   137     2           0     4         1           WARD   \n",
       "957  ...        False   137     4           1     4         1           WARD   \n",
       "958  ...        False   137     4           2     4         1           WARD   \n",
       "\n",
       "     District ID Unnamed: 20 Office ID  \n",
       "954      WRD1002         NaN      1945  \n",
       "955      WRD1202         NaN      1945  \n",
       "956      WRD1402         NaN      1945  \n",
       "957      WRD1404         NaN      1945  \n",
       "958      WRD1404         NaN      1945  \n",
       "\n",
       "[5 rows x 22 columns]"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "candidate_df[candidate_df[\"District Type\"]==\"WARD\"].head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "western-sydney",
   "metadata": {},
   "outputs": [],
   "source": [
    "muni_df = candidate_df[candidate_df[\"District Type\"].isin([\"MUNICIPAL\",\"WARD\",\"DISTRICT\"])]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "innovative-analyst",
   "metadata": {},
   "outputs": [],
   "source": [
    "#lets not bother w pittsburgh\n",
    "muni_df = muni_df[muni_df[\"District\"].isin(pgh_districts) == False]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "facial-bread",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>First Name</th>\n",
       "      <th>Last Name</th>\n",
       "      <th>Address 1</th>\n",
       "      <th>Address 2</th>\n",
       "      <th>City</th>\n",
       "      <th>Zip</th>\n",
       "      <th>DO</th>\n",
       "      <th>Office Title</th>\n",
       "      <th>Pseudo</th>\n",
       "      <th>District</th>\n",
       "      <th>...</th>\n",
       "      <th>Need to File</th>\n",
       "      <th>Muni</th>\n",
       "      <th>Ward</th>\n",
       "      <th>District.1</th>\n",
       "      <th>Term</th>\n",
       "      <th>Vote For</th>\n",
       "      <th>District Type</th>\n",
       "      <th>District ID</th>\n",
       "      <th>Unnamed: 20</th>\n",
       "      <th>Office ID</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>694</th>\n",
       "      <td>David C.</td>\n",
       "      <td>Brown</td>\n",
       "      <td>NaN</td>\n",
       "      <td>227 First Street</td>\n",
       "      <td>Aspinwall</td>\n",
       "      <td>15215</td>\n",
       "      <td>1</td>\n",
       "      <td>Mayor</td>\n",
       "      <td>2</td>\n",
       "      <td>ASPINWALL</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>102</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>MUNICIPAL</td>\n",
       "      <td>MUN102</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1340</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>695</th>\n",
       "      <td>Joseph</td>\n",
       "      <td>Noro</td>\n",
       "      <td>NaN</td>\n",
       "      <td>24 3rd St.</td>\n",
       "      <td>Pittsburgh</td>\n",
       "      <td>15215</td>\n",
       "      <td>1</td>\n",
       "      <td>Mayor</td>\n",
       "      <td>2</td>\n",
       "      <td>ASPINWALL</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>102</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>MUNICIPAL</td>\n",
       "      <td>MUN102</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1340</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>696</th>\n",
       "      <td>Thomas R</td>\n",
       "      <td>Lloyd, Jr.</td>\n",
       "      <td>NaN</td>\n",
       "      <td>225 South Ohio St.</td>\n",
       "      <td>Pittsburgh</td>\n",
       "      <td>15202</td>\n",
       "      <td>1</td>\n",
       "      <td>Mayor</td>\n",
       "      <td>5</td>\n",
       "      <td>AVALON</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>103</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>MUNICIPAL</td>\n",
       "      <td>MUN103</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1340</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>697</th>\n",
       "      <td>David M.</td>\n",
       "      <td>Depretis</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2957 Meadowvue Dr.</td>\n",
       "      <td>Pittsburgh</td>\n",
       "      <td>15227</td>\n",
       "      <td>1</td>\n",
       "      <td>Mayor</td>\n",
       "      <td>22</td>\n",
       "      <td>BALDWIN BOROUGH</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>104</td>\n",
       "      <td>0</td>\n",
       "      <td>12</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>MUNICIPAL</td>\n",
       "      <td>MUN104</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1340</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>698</th>\n",
       "      <td>Kenneth L.</td>\n",
       "      <td>Alvania</td>\n",
       "      <td>NaN</td>\n",
       "      <td>141 Sevin Rd.</td>\n",
       "      <td>Sewickley</td>\n",
       "      <td>15143</td>\n",
       "      <td>1</td>\n",
       "      <td>Mayor</td>\n",
       "      <td>31</td>\n",
       "      <td>BELL ACRES</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>106</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>MUNICIPAL</td>\n",
       "      <td>MUN106</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1340</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     First Name   Last Name Address 1           Address 2        City    Zip  \\\n",
       "694    David C.       Brown       NaN    227 First Street   Aspinwall  15215   \n",
       "695      Joseph        Noro       NaN          24 3rd St.  Pittsburgh  15215   \n",
       "696    Thomas R  Lloyd, Jr.       NaN  225 South Ohio St.  Pittsburgh  15202   \n",
       "697    David M.    Depretis       NaN  2957 Meadowvue Dr.  Pittsburgh  15227   \n",
       "698  Kenneth L.     Alvania       NaN       141 Sevin Rd.   Sewickley  15143   \n",
       "\n",
       "     DO Office Title  Pseudo         District  ... Need to File  Muni  Ward  \\\n",
       "694   1        Mayor       2        ASPINWALL  ...        False   102     0   \n",
       "695   1        Mayor       2        ASPINWALL  ...        False   102     0   \n",
       "696   1        Mayor       5           AVALON  ...        False   103     1   \n",
       "697   1        Mayor      22  BALDWIN BOROUGH  ...        False   104     0   \n",
       "698   1        Mayor      31       BELL ACRES  ...        False   106     0   \n",
       "\n",
       "     District.1  Term  Vote For  District Type  District ID Unnamed: 20  \\\n",
       "694           1     4         1      MUNICIPAL      MUN102          NaN   \n",
       "695           1     4         1      MUNICIPAL      MUN102          NaN   \n",
       "696           0     4         1      MUNICIPAL      MUN103          NaN   \n",
       "697          12     4         1      MUNICIPAL      MUN104          NaN   \n",
       "698           1     4         1      MUNICIPAL      MUN106          NaN   \n",
       "\n",
       "    Office ID  \n",
       "694      1340  \n",
       "695      1340  \n",
       "696      1340  \n",
       "697      1340  \n",
       "698      1340  \n",
       "\n",
       "[5 rows x 22 columns]"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "muni_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "developmental-disability",
   "metadata": {},
   "outputs": [],
   "source": [
    "muni_indices = list(muni_df.index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "sustainable-homeless",
   "metadata": {},
   "outputs": [],
   "source": [
    "name = [] #first name + last name\n",
    "party = [] \n",
    "district = [] #District\n",
    "office = [] #Office Title\n",
    "ward = [] #Ward\n",
    "for i in muni_indices:\n",
    "    row = muni_df[muni_df.index==i]\n",
    "    name.append(row[\"First Name\"].to_string(index=False) + \" \" + row[\"Last Name\"].to_string(index=False))\n",
    "    party.append(row[\"Party\"].to_string(index=False))\n",
    "    district.append(row[\"District\"].to_string(index=False))\n",
    "    office.append(row[\"Office Title\"].to_string(index=False))\n",
    "    ward.append(row[\"Ward\"].to_string(index=False))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "devoted-riding",
   "metadata": {},
   "outputs": [],
   "source": [
    "muni_cleaned = pd.DataFrame()\n",
    "muni_cleaned[\"name\"] = name\n",
    "muni_cleaned[\"party\"] = party\n",
    "muni_cleaned[\"district\"] = district\n",
    "muni_cleaned[\"office\"] = office\n",
    "muni_cleaned[\"ward\"] = ward"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "acquired-makeup",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>party</th>\n",
       "      <th>district</th>\n",
       "      <th>office</th>\n",
       "      <th>ward</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>David C. Brown</td>\n",
       "      <td>Democratic</td>\n",
       "      <td>ASPINWALL</td>\n",
       "      <td>Mayor</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Joseph Noro</td>\n",
       "      <td>Republican</td>\n",
       "      <td>ASPINWALL</td>\n",
       "      <td>Mayor</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Thomas R Lloyd, Jr.</td>\n",
       "      <td>Democratic</td>\n",
       "      <td>AVALON</td>\n",
       "      <td>Mayor</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>David M. Depretis</td>\n",
       "      <td>Democratic</td>\n",
       "      <td>BALDWIN BOROUGH</td>\n",
       "      <td>Mayor</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Kenneth L. Alvania</td>\n",
       "      <td>Democratic</td>\n",
       "      <td>BELL ACRES</td>\n",
       "      <td>Mayor</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  name       party         district office ward\n",
       "0       David C. Brown  Democratic        ASPINWALL  Mayor    0\n",
       "1          Joseph Noro  Republican        ASPINWALL  Mayor    0\n",
       "2  Thomas R Lloyd, Jr.  Democratic           AVALON  Mayor    1\n",
       "3    David M. Depretis  Democratic  BALDWIN BOROUGH  Mayor    0\n",
       "4   Kenneth L. Alvania  Democratic       BELL ACRES  Mayor    0"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "muni_cleaned.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "consolidated-inventory",
   "metadata": {},
   "outputs": [],
   "source": [
    "muni_cleaned_indices = list(muni_cleaned.index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "guilty-clear",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['ROSS', '4']\n",
      "            name       party     district        office ward\n",
      "282  Eric Ticjak  Republican  ROSS WARD 4  Commissioner    2\n",
      "\n",
      "['UPPER ST CLAIR', '4']\n",
      "                name       party               district        office ward\n",
      "297  Todd Burlingame  Republican  UPPER ST CLAIR WARD 4  Commissioner    0\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# here i'm figuring out if the ward # matches the ward # within the district name\n",
    "for i in muni_cleaned_indices:\n",
    "    row = muni_cleaned[muni_cleaned.index==i]\n",
    "    pts = row.district.to_string(index=False).split(\" WARD \")\n",
    "    if len(pts)>1:\n",
    "        if int(pts[-1])!=int(row.ward.to_string(index=False)):\n",
    "            print(pts)\n",
    "            print(row)\n",
    "            print()\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "identical-receipt",
   "metadata": {},
   "outputs": [],
   "source": [
    "# ok so idk wtf is up w those two but i guess i will just move on\n",
    "muni_cleaned.district = muni_cleaned.district.map(lambda x: x.split(\" WARD \")[0])\n",
    "muni_cleaned= muni_cleaned.replace(\"Richland 1\",\"RICHLAND\")\n",
    "muni_cleaned= muni_cleaned.replace(\"Richland 2\",\"RICHLAND\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "attached-kingdom",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>party</th>\n",
       "      <th>district</th>\n",
       "      <th>office</th>\n",
       "      <th>ward</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>David C. Brown</td>\n",
       "      <td>Democratic</td>\n",
       "      <td>ASPINWALL</td>\n",
       "      <td>Mayor</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Joseph Noro</td>\n",
       "      <td>Republican</td>\n",
       "      <td>ASPINWALL</td>\n",
       "      <td>Mayor</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Thomas R Lloyd, Jr.</td>\n",
       "      <td>Democratic</td>\n",
       "      <td>AVALON</td>\n",
       "      <td>Mayor</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>David M. Depretis</td>\n",
       "      <td>Democratic</td>\n",
       "      <td>BALDWIN BOROUGH</td>\n",
       "      <td>Mayor</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Kenneth L. Alvania</td>\n",
       "      <td>Democratic</td>\n",
       "      <td>BELL ACRES</td>\n",
       "      <td>Mayor</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  name       party         district office ward\n",
       "0       David C. Brown  Democratic        ASPINWALL  Mayor    0\n",
       "1          Joseph Noro  Republican        ASPINWALL  Mayor    0\n",
       "2  Thomas R Lloyd, Jr.  Democratic           AVALON  Mayor    1\n",
       "3    David M. Depretis  Democratic  BALDWIN BOROUGH  Mayor    0\n",
       "4   Kenneth L. Alvania  Democratic       BELL ACRES  Mayor    0"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "muni_cleaned.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "outstanding-circulation",
   "metadata": {},
   "outputs": [],
   "source": [
    "muni_pos_df = pd.read_csv(\"munipos.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "supreme-serial",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>number</th>\n",
       "      <th>position</th>\n",
       "      <th>term</th>\n",
       "      <th>ward</th>\n",
       "      <th>muni</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>TAX COLLECTOR</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ALEPPO</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>3</td>\n",
       "      <td>COMMISSIONER</td>\n",
       "      <td>4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ALEPPO</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>COMMISSIONER</td>\n",
       "      <td>2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ALEPPO</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2</td>\n",
       "      <td>CONSTABLE</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ALEPPO</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>MAYOR</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ASPINWALL</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   number       position term ward       muni\n",
       "0       1  TAX COLLECTOR  NaN  NaN     ALEPPO\n",
       "1       3   COMMISSIONER    4  NaN     ALEPPO\n",
       "2       1   COMMISSIONER    2  NaN     ALEPPO\n",
       "3       2      CONSTABLE  NaN  NaN     ALEPPO\n",
       "4       1          MAYOR  NaN  NaN  ASPINWALL"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "muni_pos_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "obvious-planner",
   "metadata": {},
   "outputs": [],
   "source": [
    "muni_pos_cleaned = muni_pos_df[muni_pos_df.ward.notna()==False]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "happy-linux",
   "metadata": {},
   "outputs": [],
   "source": [
    "dewardify_df = muni_pos_df[muni_pos_df.ward.notna()==True]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "great-fossil",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3     28\n",
       "1     24\n",
       "2     11\n",
       "4     11\n",
       "5      3\n",
       "7      1\n",
       "9      1\n",
       "12     1\n",
       "Name: number, dtype: int64"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dewardify_df.number.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "tender-offer",
   "metadata": {},
   "outputs": [],
   "source": [
    "def dewardify2(ward_df):\n",
    "    row_list = []\n",
    "    for row in range(len(ward_df)):\n",
    "        print(regions)\n",
    "        num = int(ward_df.iloc[row,0])//len(regions)\n",
    "        if len(regions)>1:\n",
    "            for x in regions:\n",
    "                temp_dict = {\n",
    "                    \"number\": num, \n",
    "                    \"position\": ward_df.iloc[row,1],\n",
    "                    \"term\": ward_df.iloc[row,2],\n",
    "                    \"ward\": x,\n",
    "                    \"muni\": ward_df.iloc[row,4]\n",
    "                }\n",
    "                row_list.append(temp_dict)  \n",
    "        else:\n",
    "            temp_dict = {\n",
    "                \"number\": int(ward_df.iloc[row,0]), \n",
    "                \"position\": ward_df.iloc[row,1],\n",
    "                \"term\": ward_df.iloc[row,2],\n",
    "                \"ward\": ward_df.iloc[row,3],\n",
    "                \"muni\": ward_df.iloc[row,4]\n",
    "                }\n",
    "            row_list.append(temp_dict)  \n",
    "    return row_list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "significant-input",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>number</th>\n",
       "      <th>position</th>\n",
       "      <th>term</th>\n",
       "      <th>ward</th>\n",
       "      <th>muni</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>TAX COLLECTOR</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ALEPPO</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>3</td>\n",
       "      <td>COMMISSIONER</td>\n",
       "      <td>4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ALEPPO</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>COMMISSIONER</td>\n",
       "      <td>2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ALEPPO</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2</td>\n",
       "      <td>CONSTABLE</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ALEPPO</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>MAYOR</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ASPINWALL</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   number       position term ward       muni\n",
       "0       1  TAX COLLECTOR  NaN  NaN     ALEPPO\n",
       "1       3   COMMISSIONER    4  NaN     ALEPPO\n",
       "2       1   COMMISSIONER    2  NaN     ALEPPO\n",
       "3       2      CONSTABLE  NaN  NaN     ALEPPO\n",
       "4       1          MAYOR  NaN  NaN  ASPINWALL"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "muni_pos_cleaned.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "alert-rebel",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['TAX COLLECTOR', 'COMMISSIONER', 'CONSTABLE', 'MAYOR',\n",
       "       'MEMBER OF COUNCIL', 'AUDITOR', 'CONTROLLER', 'SUPERVISOR',\n",
       "       'MEMBERS OF COUNCIL', 'TREASURER'], dtype=object)"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "muni_pos_cleaned.position.unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "infrared-ancient",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-64-b115d6eaf588>: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: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  muni_pos_cleaned[\"position\"] = muni_pos_cleaned[\"position\"].map(str.lower)\n"
     ]
    }
   ],
   "source": [
    "muni_pos_cleaned[\"position\"] = muni_pos_cleaned[\"position\"].map(str.lower)\n",
    "muni_pos_cleaned= muni_pos_cleaned.replace(\"members of council\",\"member of council\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "innovative-tactics",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['tax collector', 'commissioner', 'constable', 'mayor',\n",
       "       'member of council', 'auditor', 'controller', 'supervisor',\n",
       "       'treasurer'], dtype=object)"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "muni_pos_cleaned.position.unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "numerical-seller",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Mayor', 'Controller', 'Tax Collector', 'Treasurer', 'Auditor',\n",
       "       'Commissioner At-Large', 'Commissioner',\n",
       "       'Member of Council At-Large', 'Member of Council', 'Supervisor',\n",
       "       'Constable'], dtype=object)"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "muni_cleaned.office.unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "featured-monitor",
   "metadata": {},
   "outputs": [],
   "source": [
    "muni_cleaned[\"position\"] = muni_cleaned.office.map(str.lower)\n",
    "muni_cleaned = muni_cleaned.drop(columns=[\"office\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "alternate-granny",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['mayor', 'controller', 'tax collector', 'treasurer', 'auditor',\n",
       "       'commissioner at-large', 'commissioner',\n",
       "       'member of council at-large', 'member of council', 'supervisor',\n",
       "       'constable'], dtype=object)"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "muni_cleaned.position.unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "id": "diverse-barcelona",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['mayor', 'controller', 'tax collector', 'treasurer', 'auditor',\n",
       "       'commissioner', 'member of council', 'supervisor', 'constable'],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "muni_cleaned = muni_cleaned.replace(\"commissioner at-large\",\"commissioner\")\n",
    "muni_cleaned = muni_cleaned.replace(\"member of council at-large\",\"member of council\")\n",
    "muni_cleaned.position.unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "timely-kruger",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sorted(list(muni_cleaned.position.unique())) == sorted(list(muni_pos_cleaned.position.unique()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "id": "visible-explosion",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# scream\n",
    "sorted(list(muni_pos_cleaned.muni.unique())) == sorted(list(muni_cleaned.district.unique()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "id": "stupid-bench",
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_bad_names(l1,l2):\n",
    "    l3 = list(set(l1 + l2))\n",
    "    bad = []\n",
    "    for x in l3:\n",
    "        if x not in l1 and l2:\n",
    "            bad.append(x)\n",
    "    return bad"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "id": "labeled-defeat",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['ALEPPO', 'ASPINWALL', 'AVALON', 'BALDWIN BOROUGH', 'BALDWIN TOWNSHIP', 'BELL ACRES', 'BELLEVUE', 'BEN AVON', 'BEN AVON HEIGHTS', 'BETHEL PARK', 'BLAWNOX', 'BRACKENRIDGE', 'BRADDOCK', 'BRADDOCK HILLS', 'BRADDOCK WOODS', 'BRENTWOOD', 'BRIDGEVILLE', 'CARNEGIE', 'CASTLE SHANNON', 'CHALFANT', 'CHESWICK', 'CHURCHILL', 'CLAIRTON', 'COLLIER', 'CORAOPOLIS', 'CRAFTON', 'CRESCENT', 'DORMONT', 'DRAVOSBURG', 'DUQUESNE', 'EAST DEER', 'EAST MCKEESPORT', 'EAST PITTSBURGH', 'EDGEWOOD', 'EDGEWORTH', 'ELIZABETH BOROUGH', 'ELIZABETH TOWNSHIP', 'EMSWORTH', 'ETNA', 'FAWN', 'FINDLAY', 'FOREST HILLS', 'FORWARD', 'FOX CHAPEL', 'FRANKLIN PARK', 'FRAZER', 'GLASSPORT', 'GLEN OSBORNE', 'GLENFIELD', 'GREEN TREE', 'HAMPTON', 'HARMAR', 'HARRISON', 'HAYSVILLE', 'HEIDELBERG', 'HOMESTEAD', 'INDIANA', 'INGRAM', 'JEFFERSON HILLS', 'KENNEDY', 'KILBUCK', 'LEET', 'LEETSDALE', 'LIBERTY', 'LINCOLN', 'MARSHALL', 'MCCANDLESS', 'MCKEES ROCKS', 'MCKEESPORT', 'MILLVALE', 'MONROEVILLE', 'MOON', 'MOUNT LEBANON', 'MOUNT OLIVER', 'MUNHALL', 'NEVILLE', 'NORTH BRADDOCK', 'NORTH FAYETTE', 'NORTH VERSAILLES', 'OAKDALE', 'OAKMONT', 'OHIO', 'O’HARA', 'PENN HILLS', 'PENNSBURY VILLAGE', 'PINE', 'PITCAIRN', 'PLEASANT HILLS', 'PLUM', 'PORT VUE', 'RANKIN', 'RESERVE', 'RICHLAND', 'ROBINSON', 'ROSS', 'ROSSLYN FARMS', 'SCOTT', 'SEWICKLEY', 'SEWICKLEY HEIGHTS', 'SEWICKLEY HILLS', 'SHALER', 'SHARPSBURG', 'SOUTH FAYETTE', 'SOUTH PARK', 'SOUTH VERSAILLES', 'SPRINGDALE BOROUGH', 'SPRINGDALE TOWNSHIP', 'STOWE', 'SWISSVALE', 'TARENTUM', 'THORNBURG', 'TURTLE CREEK', 'UPPER ST. CLAIR', 'VERONA', 'VERSAILLES', 'WALL', 'WEST DEER', 'WEST ELIZABETH', 'WEST HOMESTEAD', 'WEST MIFFLIN', 'WEST VIEW', 'WHITAKER', 'WHITE OAK', 'WHITEHALL', 'WILKINS', 'WILKINSBURG', 'WILMERDING']\n",
      "\n",
      "['ALEPPO', 'ASPINWALL', 'AVALON', 'BALDWIN BOROUGH', 'BALDWIN TOWNSHIP', 'BELL ACRES', 'BELLEVUE', 'BEN AVON', 'BEN AVON HEIGHTS', 'BETHEL PARK', 'BLAWNOX', 'BRACKENRIDGE', 'BRADDOCK', 'BRADDOCK HILLS', 'BRADFORD WOODS ', 'BRENTWOOD', 'BRIDGEVILLE', 'CARNEGIE', 'CASTLE SHANNON', 'CHALFANT', 'CHESWICK', 'CHURCHILL', 'CLAIRTON', 'COLLIER', 'CORAOPOLIS', 'CRAFTON', 'CRESCENT', 'DORMONT', 'DRAVOSBURG', 'DUQUESNE', 'EAST DEER', 'EAST MCKEESPORT', 'EAST PITTSBURGH', 'EDGEWOOD', 'EDGEWORTH', 'ELIZABETH BOROUGH', 'ELIZABETH TOWNSHIP', 'EMSWORTH', 'ETNA', 'FAWN', 'FINDLAY', 'FOREST HILLS', 'FORWARD', 'FOX CHAPEL', 'FRANKLIN PARK', 'FRAZER', 'GLASSPORT', 'GREEN TREE', 'HAMPTON', 'HARMAR', 'HARRISON', 'HEIDELBERG', 'HOMESTEAD', 'INDIANA', 'INGRAM', 'JEFFERSON HILLS', 'KENNEDY', 'KILBUCK', 'LEET', 'LEETSDALE', 'LIBERTY', 'LINCOLN', 'MARSHALL', 'MCCANDLESS', 'MCKEES ROCKS', 'MCKEESPORT', 'MILLVALE', 'MONROEVILLE', 'MOON', 'MT LEBANON', 'MT OLIVER', 'MUNHALL', 'NEVILLE', 'NORTH BRADDOCK', 'NORTH FAYETTE', 'NORTH VERSAILLES', 'OAKDALE', 'OAKMONT', 'OHARA', 'OHIO', 'OSBORNE', 'PENN HILLS', 'PENNSBURY VILLAGE', 'PINE', 'PITCAIRN', 'PLEASANT HILL', 'PLUM', 'PORT VUE', 'RANKIN', 'RESERVE', 'RICHLAND', 'ROBINSON', 'ROSS', 'ROSSLYN FARM', 'SCOTT', 'SEWICKLEY', 'SEWICKLEY HEIGHTS', 'SEWICKLEY HILLS', 'SHALER', 'SHARPSBURG', 'SOUTH FAYETTE', 'SOUTH PARK', 'SOUTH VERSAILLES', 'SPRINGDALE BOROUGH', 'SPRINGDALE TOWNSHIP', 'STOWE', 'SWISSVALE', 'TARENTUM', 'THORNBURG', 'TURTLE CREEK', 'UPPER ST CLAIR', 'VERONA', 'VERSAILLES', 'WALL', 'WEST DEER', 'WEST ELIZABETH', 'WEST HOMESTEAD', 'WEST MIFFLIN', 'WEST VIEW', 'WHITAKER', 'WHITE OAK', 'WHITEHALL', 'WILKINS', 'WILKINSBURG', 'WILMERDING']\n"
     ]
    }
   ],
   "source": [
    "print(sorted(list(muni_pos_cleaned.muni.unique())))\n",
    "print()\n",
    "print(sorted(list(muni_cleaned.district.unique())))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "id": "dynamic-coffee",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['MT OLIVER',\n",
       " 'ROSSLYN FARM',\n",
       " 'UPPER ST CLAIR',\n",
       " 'BRADFORD WOODS ',\n",
       " 'PLEASANT HILL',\n",
       " 'OSBORNE',\n",
       " 'OHARA',\n",
       " 'MT LEBANON']"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "get_bad_names(list(muni_pos_cleaned.muni.unique()), list(muni_cleaned.district.unique()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "id": "reduced-scoop",
   "metadata": {},
   "outputs": [],
   "source": [
    "def fix_name_issues(muni_list):\n",
    "    # it doesn't work when i do all the stuff in one line idk\n",
    "    muni_list2 = []\n",
    "    for x in muni_list:\n",
    "        temp = x.strip().replace(\"MT\",\"MOUNT\").replace(\"ST.\",\"ST\")\n",
    "        if temp==\"ROSSLYN FARM\":\n",
    "            muni_list2.append(\"ROSSLYN FARMS\")\n",
    "        elif temp==\"PLEASANT HILL\":\n",
    "            muni_list2.append(\"PLEASANT HILLS\")\n",
    "        elif temp==\"O’HARA\":\n",
    "            muni_list2.append(\"OHARA\")\n",
    "        elif temp==\"OSBORNE\":\n",
    "            muni_list2.append(\"GLEN OSBORNE\")\n",
    "        else:\n",
    "            muni_list2.append(temp)\n",
    "    return muni_list2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "id": "varied-doctrine",
   "metadata": {},
   "outputs": [],
   "source": [
    "muni_pos_cleaned[\"district\"] = fix_name_issues(list(muni_pos_cleaned.muni))\n",
    "muni_pos_cleaned = muni_pos_cleaned.drop(columns=[\"muni\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "id": "opposite-lafayette",
   "metadata": {},
   "outputs": [],
   "source": [
    "muni_cleaned[\"district\"] = fix_name_issues(list(muni_cleaned.district))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "id": "powerful-pound",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False"
      ]
     },
     "execution_count": 78,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# s c r e a m\n",
    "sorted(list(muni_pos_cleaned.district.unique())) == sorted(list(muni_cleaned.district.unique()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "id": "compound-pakistan",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['BRADFORD WOODS']"
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "get_bad_names(list(muni_pos_cleaned.district.unique()), list(muni_cleaned.district.unique()))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "balanced-durham",
   "metadata": {},
   "source": [
    "## Data Analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "id": "innovative-stationery",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>party</th>\n",
       "      <th>district</th>\n",
       "      <th>ward</th>\n",
       "      <th>position</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>David C. Brown</td>\n",
       "      <td>Democratic</td>\n",
       "      <td>ASPINWALL</td>\n",
       "      <td>0</td>\n",
       "      <td>mayor</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Joseph Noro</td>\n",
       "      <td>Republican</td>\n",
       "      <td>ASPINWALL</td>\n",
       "      <td>0</td>\n",
       "      <td>mayor</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Thomas R Lloyd, Jr.</td>\n",
       "      <td>Democratic</td>\n",
       "      <td>AVALON</td>\n",
       "      <td>1</td>\n",
       "      <td>mayor</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>David M. Depretis</td>\n",
       "      <td>Democratic</td>\n",
       "      <td>BALDWIN BOROUGH</td>\n",
       "      <td>0</td>\n",
       "      <td>mayor</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Kenneth L. Alvania</td>\n",
       "      <td>Democratic</td>\n",
       "      <td>BELL ACRES</td>\n",
       "      <td>0</td>\n",
       "      <td>mayor</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  name       party         district ward position\n",
       "0       David C. Brown  Democratic        ASPINWALL    0    mayor\n",
       "1          Joseph Noro  Republican        ASPINWALL    0    mayor\n",
       "2  Thomas R Lloyd, Jr.  Democratic           AVALON    1    mayor\n",
       "3    David M. Depretis  Democratic  BALDWIN BOROUGH    0    mayor\n",
       "4   Kenneth L. Alvania  Democratic       BELL ACRES    0    mayor"
      ]
     },
     "execution_count": 80,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "muni_cleaned.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "id": "controlling-audit",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "district\n",
       "ALEPPO               5\n",
       "ASPINWALL            9\n",
       "AVALON              12\n",
       "BALDWIN BOROUGH      9\n",
       "BALDWIN TOWNSHIP     2\n",
       "                    ..\n",
       "WHITE OAK           10\n",
       "WHITEHALL            9\n",
       "WILKINS              3\n",
       "WILKINSBURG         14\n",
       "WILMERDING           6\n",
       "Name: position, Length: 125, dtype: int64"
      ]
     },
     "execution_count": 81,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "muni_cleaned.groupby(\"district\")[\"position\"].count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "id": "satellite-convention",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-82-0694beed5e1a>:1: UserWarning: Boolean Series key will be reindexed to match DataFrame index.\n",
      "  muni_cleaned.loc[muni_cleaned.district==\"ALEPPO\"][muni_cleaned.position==\"tax collector\"].name\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "114    Casey Cunningham\n",
       "115    Clayton R. Steup\n",
       "Name: name, dtype: object"
      ]
     },
     "execution_count": 82,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "muni_cleaned.loc[muni_cleaned.district==\"ALEPPO\"][muni_cleaned.position==\"tax collector\"].name"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "id": "specialized-climate",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>number</th>\n",
       "      <th>position</th>\n",
       "      <th>term</th>\n",
       "      <th>ward</th>\n",
       "      <th>district</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>tax collector</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ALEPPO</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>3</td>\n",
       "      <td>commissioner</td>\n",
       "      <td>4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ALEPPO</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>commissioner</td>\n",
       "      <td>2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ALEPPO</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2</td>\n",
       "      <td>constable</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ALEPPO</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>mayor</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ASPINWALL</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   number       position term  ward   district\n",
       "0       1  tax collector  NaN   NaN     ALEPPO\n",
       "1       3   commissioner    4   NaN     ALEPPO\n",
       "2       1   commissioner    2   NaN     ALEPPO\n",
       "3       2      constable  NaN   NaN     ALEPPO\n",
       "4       1          mayor  NaN   NaN  ASPINWALL"
      ]
     },
     "execution_count": 83,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "muni_pos_cleaned.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "id": "beautiful-stadium",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>party</th>\n",
       "      <th>district</th>\n",
       "      <th>ward</th>\n",
       "      <th>position</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>114</th>\n",
       "      <td>Casey Cunningham</td>\n",
       "      <td>Democratic</td>\n",
       "      <td>ALEPPO</td>\n",
       "      <td>0</td>\n",
       "      <td>tax collector</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>115</th>\n",
       "      <td>Clayton R. Steup</td>\n",
       "      <td>Republican</td>\n",
       "      <td>ALEPPO</td>\n",
       "      <td>0</td>\n",
       "      <td>tax collector</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 name       party district ward       position\n",
       "114  Casey Cunningham  Democratic   ALEPPO    0  tax collector\n",
       "115  Clayton R. Steup  Republican   ALEPPO    0  tax collector"
      ]
     },
     "execution_count": 84,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "muni_cleaned[lambda df: df[\"district\"]==\"ALEPPO\"][lambda df: df[\"position\"]==\"tax collector\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "id": "bridal-census",
   "metadata": {},
   "outputs": [],
   "source": [
    "mc_df = pd.DataFrame()\n",
    "mc_df = mc_df.append(muni_pos_cleaned)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "id": "unexpected-accountability",
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_candidates(pos_df):\n",
    "    candidates = []\n",
    "    can_count = []\n",
    "    parties = []\n",
    "    \n",
    "    for index in pos_df.index:\n",
    "        row = pos_df.loc[[index]]\n",
    "        \n",
    "        pos, dis, ward = row[\"position\"].to_string(index=False), row[\"district\"].to_string(index=False), row[\"ward\"].to_string(index=False)\n",
    "        \n",
    "        if ward==\"NaN\":\n",
    "            subset = muni_cleaned[lambda df: df[\"district\"]==dis][lambda df: df[\"position\"]==pos]\n",
    "            can_count.append(len(subset))\n",
    "            if len(subset)>0:\n",
    "                candidates.append([x.strip() for x in subset.name.to_string(index=False).split(\"\\n\")])\n",
    "                parties.append([x.strip() for x in subset.party.to_string(index=False).split(\"\\n\")])\n",
    "            else:\n",
    "                candidates.append([\"none\"])\n",
    "                parties.append([\"N/A\"])\n",
    "        else:\n",
    "            subset = muni_cleaned[lambda df: df[\"district\"]==dis][lambda df: df[\"position\"]==pos][lambda df: df[\"ward\"]==ward]\n",
    "            can_count.append(len(subset))\n",
    "            if len(subset)>0:\n",
    "                candidates([x.strip() for x in subset.name.to_string(index=False).split(\"\\n\")])\n",
    "                parties.append([x.strip() for x in subset.party.to_string(index=False).split(\"\\n\")])\n",
    "            else:\n",
    "                candidates.append([\"none\"])\n",
    "                parties.append([\"N/A\"])\n",
    "    return candidates, can_count, parties"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "id": "wooden-mayor",
   "metadata": {},
   "outputs": [],
   "source": [
    "candidates, can_count, party = get_candidates(mc_df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "id": "careful-resolution",
   "metadata": {},
   "outputs": [],
   "source": [
    "mc_df[\"candidates\"] = candidates\n",
    "mc_df[\"candidate_count\"] = can_count\n",
    "mc_df[\"party\"] = party"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "id": "damaged-court",
   "metadata": {},
   "outputs": [],
   "source": [
    "# wooooooo\n",
    "mc_df.head()\n",
    "mc_df.to_csv(\"all_muni_positions.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "id": "informed-syndication",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>number</th>\n",
       "      <th>position</th>\n",
       "      <th>term</th>\n",
       "      <th>ward</th>\n",
       "      <th>district</th>\n",
       "      <th>candidates</th>\n",
       "      <th>candidate_count</th>\n",
       "      <th>party</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2</td>\n",
       "      <td>constable</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ALEPPO</td>\n",
       "      <td>[none]</td>\n",
       "      <td>0</td>\n",
       "      <td>[N/A]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>1</td>\n",
       "      <td>constable</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ASPINWALL</td>\n",
       "      <td>[none]</td>\n",
       "      <td>0</td>\n",
       "      <td>[N/A]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>1</td>\n",
       "      <td>tax collector</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>AVALON</td>\n",
       "      <td>[none]</td>\n",
       "      <td>0</td>\n",
       "      <td>[N/A]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>1</td>\n",
       "      <td>tax collector</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>BALDWIN TOWNSHIP</td>\n",
       "      <td>[none]</td>\n",
       "      <td>0</td>\n",
       "      <td>[N/A]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>2</td>\n",
       "      <td>constable</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>BALDWIN TOWNSHIP</td>\n",
       "      <td>[none]</td>\n",
       "      <td>0</td>\n",
       "      <td>[N/A]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>494</th>\n",
       "      <td>1</td>\n",
       "      <td>mayor</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>WHITAKER</td>\n",
       "      <td>[none]</td>\n",
       "      <td>0</td>\n",
       "      <td>[N/A]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>501</th>\n",
       "      <td>1</td>\n",
       "      <td>constable</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>WHITEHALL</td>\n",
       "      <td>[none]</td>\n",
       "      <td>0</td>\n",
       "      <td>[N/A]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>505</th>\n",
       "      <td>1</td>\n",
       "      <td>constable</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>WHITE OAK</td>\n",
       "      <td>[none]</td>\n",
       "      <td>0</td>\n",
       "      <td>[N/A]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>509</th>\n",
       "      <td>2</td>\n",
       "      <td>constable</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>WILKINS</td>\n",
       "      <td>[none]</td>\n",
       "      <td>0</td>\n",
       "      <td>[N/A]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>518</th>\n",
       "      <td>1</td>\n",
       "      <td>constable</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>WILMERDING</td>\n",
       "      <td>[none]</td>\n",
       "      <td>0</td>\n",
       "      <td>[N/A]</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>118 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     number       position term  ward          district candidates  \\\n",
       "3         2      constable  NaN   NaN            ALEPPO     [none]   \n",
       "7         1      constable  NaN   NaN         ASPINWALL     [none]   \n",
       "9         1  tax collector  NaN   NaN            AVALON     [none]   \n",
       "18        1  tax collector  NaN   NaN  BALDWIN TOWNSHIP     [none]   \n",
       "20        2      constable  NaN   NaN  BALDWIN TOWNSHIP     [none]   \n",
       "..      ...            ...  ...   ...               ...        ...   \n",
       "494       1          mayor  NaN   NaN          WHITAKER     [none]   \n",
       "501       1      constable  NaN   NaN         WHITEHALL     [none]   \n",
       "505       1      constable  NaN   NaN         WHITE OAK     [none]   \n",
       "509       2      constable  NaN   NaN           WILKINS     [none]   \n",
       "518       1      constable  NaN   NaN        WILMERDING     [none]   \n",
       "\n",
       "     candidate_count  party  \n",
       "3                  0  [N/A]  \n",
       "7                  0  [N/A]  \n",
       "9                  0  [N/A]  \n",
       "18                 0  [N/A]  \n",
       "20                 0  [N/A]  \n",
       "..               ...    ...  \n",
       "494                0  [N/A]  \n",
       "501                0  [N/A]  \n",
       "505                0  [N/A]  \n",
       "509                0  [N/A]  \n",
       "518                0  [N/A]  \n",
       "\n",
       "[118 rows x 8 columns]"
      ]
     },
     "execution_count": 100,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "empty_df = mc_df[mc_df.candidate_count==0]\n",
    "empty_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "id": "adverse-writer",
   "metadata": {},
   "outputs": [],
   "source": [
    "empty_df.to_csv(\"no_candidates.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "id": "treated-portland",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>number</th>\n",
       "      <th>position</th>\n",
       "      <th>term</th>\n",
       "      <th>ward</th>\n",
       "      <th>district</th>\n",
       "      <th>candidates</th>\n",
       "      <th>candidate_count</th>\n",
       "      <th>party</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>3</td>\n",
       "      <td>commissioner</td>\n",
       "      <td>4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ALEPPO</td>\n",
       "      <td>[Judith M. Haluka, Daniel M. Darragh, George J...</td>\n",
       "      <td>3</td>\n",
       "      <td>[Democratic, Republican, Republican]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1</td>\n",
       "      <td>tax collector</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ASPINWALL</td>\n",
       "      <td>[Dawn E. Eastley]</td>\n",
       "      <td>1</td>\n",
       "      <td>[Democratic]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>1</td>\n",
       "      <td>mayor</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>AVALON</td>\n",
       "      <td>[Thomas R Lloyd, Jr.]</td>\n",
       "      <td>1</td>\n",
       "      <td>[Democratic]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>1</td>\n",
       "      <td>mayor</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>BALDWIN BOROUGH</td>\n",
       "      <td>[David M. Depretis]</td>\n",
       "      <td>1</td>\n",
       "      <td>[Democratic]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>1</td>\n",
       "      <td>tax collector</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>BALDWIN BOROUGH</td>\n",
       "      <td>[Gail Dobson Mikush]</td>\n",
       "      <td>1</td>\n",
       "      <td>[Democratic]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>503</th>\n",
       "      <td>1</td>\n",
       "      <td>tax collector</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>WHITE OAK</td>\n",
       "      <td>[Lisa Pitchford]</td>\n",
       "      <td>1</td>\n",
       "      <td>[Democratic]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>506</th>\n",
       "      <td>1</td>\n",
       "      <td>tax collector</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>WILKINS</td>\n",
       "      <td>[Michelle Criner]</td>\n",
       "      <td>1</td>\n",
       "      <td>[Democratic]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>511</th>\n",
       "      <td>1</td>\n",
       "      <td>tax collector</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>WILKINSBURG</td>\n",
       "      <td>[Lisa Ciccarelli]</td>\n",
       "      <td>1</td>\n",
       "      <td>[Democratic]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>515</th>\n",
       "      <td>1</td>\n",
       "      <td>mayor</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>WILMERDING</td>\n",
       "      <td>[Gregory M. Jakub]</td>\n",
       "      <td>1</td>\n",
       "      <td>[Democratic]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>516</th>\n",
       "      <td>1</td>\n",
       "      <td>tax collector</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>WILMERDING</td>\n",
       "      <td>[Frank J. Tylka]</td>\n",
       "      <td>1</td>\n",
       "      <td>[Democratic]</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>197 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     number       position term  ward         district  \\\n",
       "1         3   commissioner    4   NaN           ALEPPO   \n",
       "5         1  tax collector  NaN   NaN        ASPINWALL   \n",
       "8         1          mayor  NaN   NaN           AVALON   \n",
       "14        1          mayor  NaN   NaN  BALDWIN BOROUGH   \n",
       "15        1  tax collector  NaN   NaN  BALDWIN BOROUGH   \n",
       "..      ...            ...  ...   ...              ...   \n",
       "503       1  tax collector  NaN   NaN        WHITE OAK   \n",
       "506       1  tax collector  NaN   NaN          WILKINS   \n",
       "511       1  tax collector  NaN   NaN      WILKINSBURG   \n",
       "515       1          mayor  NaN   NaN       WILMERDING   \n",
       "516       1  tax collector  NaN   NaN       WILMERDING   \n",
       "\n",
       "                                            candidates  candidate_count  \\\n",
       "1    [Judith M. Haluka, Daniel M. Darragh, George J...                3   \n",
       "5                                    [Dawn E. Eastley]                1   \n",
       "8                                [Thomas R Lloyd, Jr.]                1   \n",
       "14                                 [David M. Depretis]                1   \n",
       "15                                [Gail Dobson Mikush]                1   \n",
       "..                                                 ...              ...   \n",
       "503                                   [Lisa Pitchford]                1   \n",
       "506                                  [Michelle Criner]                1   \n",
       "511                                  [Lisa Ciccarelli]                1   \n",
       "515                                 [Gregory M. Jakub]                1   \n",
       "516                                   [Frank J. Tylka]                1   \n",
       "\n",
       "                                    party  \n",
       "1    [Democratic, Republican, Republican]  \n",
       "5                            [Democratic]  \n",
       "8                            [Democratic]  \n",
       "14                           [Democratic]  \n",
       "15                           [Democratic]  \n",
       "..                                    ...  \n",
       "503                          [Democratic]  \n",
       "506                          [Democratic]  \n",
       "511                          [Democratic]  \n",
       "515                          [Democratic]  \n",
       "516                          [Democratic]  \n",
       "\n",
       "[197 rows x 8 columns]"
      ]
     },
     "execution_count": 102,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "unopposed_df = mc_df[mc_df.candidate_count==mc_df.number]\n",
    "unopposed_df\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "id": "conservative-companion",
   "metadata": {},
   "outputs": [],
   "source": [
    "unopposed_df.to_csv(\"unopposed_candidates.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "id": "several-photography",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-104-7f684ad084ed>:1: UserWarning: Boolean Series key will be reindexed to match DataFrame index.\n",
      "  not_enough_candidates_df = mc_df[lambda df: df.candidate_count!=0][mc_df.candidate_count<mc_df.number]\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>number</th>\n",
       "      <th>position</th>\n",
       "      <th>term</th>\n",
       "      <th>ward</th>\n",
       "      <th>district</th>\n",
       "      <th>candidates</th>\n",
       "      <th>candidate_count</th>\n",
       "      <th>party</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>3</td>\n",
       "      <td>member of council</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>BEN AVON HEIGHTS</td>\n",
       "      <td>[Joseph M. Dawley]</td>\n",
       "      <td>1</td>\n",
       "      <td>[Democratic]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>4</td>\n",
       "      <td>member of council</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>BRADDOCK HILLS</td>\n",
       "      <td>[Anette Nance, Marguerite L. Bolton, Cassandra...</td>\n",
       "      <td>3</td>\n",
       "      <td>[Democratic, Democratic, Democratic]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>86</th>\n",
       "      <td>4</td>\n",
       "      <td>member of council</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CHESWICK</td>\n",
       "      <td>[Frank Meledandri Jr., Kathleen M. Gillard]</td>\n",
       "      <td>2</td>\n",
       "      <td>[Republican, Republican]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98</th>\n",
       "      <td>2</td>\n",
       "      <td>constable</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>COLLIER</td>\n",
       "      <td>[Daniel A. Styche]</td>\n",
       "      <td>1</td>\n",
       "      <td>[Democratic]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>111</th>\n",
       "      <td>2</td>\n",
       "      <td>constable</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CRESCENT</td>\n",
       "      <td>[Daniel Perciavalle]</td>\n",
       "      <td>1</td>\n",
       "      <td>[Democratic]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>114</th>\n",
       "      <td>4</td>\n",
       "      <td>member of council</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>DORMONT</td>\n",
       "      <td>[Jennifer Mazzocco, Alvaro A. Varela, III, Ile...</td>\n",
       "      <td>3</td>\n",
       "      <td>[Democratic, Democratic, Democratic]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>147</th>\n",
       "      <td>4</td>\n",
       "      <td>member of council</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ELIZABETH BOROUGH</td>\n",
       "      <td>[Chad Rager, Dana Cress]</td>\n",
       "      <td>2</td>\n",
       "      <td>[Democratic, Democratic]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151</th>\n",
       "      <td>2</td>\n",
       "      <td>constable</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ELIZABETH TOWNSHIP</td>\n",
       "      <td>[Gary Corey]</td>\n",
       "      <td>1</td>\n",
       "      <td>[Republican]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>154</th>\n",
       "      <td>4</td>\n",
       "      <td>member of council</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>EMSWORTH</td>\n",
       "      <td>[Kevin Yurkovich, Daniel Lenz]</td>\n",
       "      <td>2</td>\n",
       "      <td>[Democratic, Democratic]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>197</th>\n",
       "      <td>4</td>\n",
       "      <td>member of council</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>GLEN OSBORNE</td>\n",
       "      <td>[John Orndorff, Mary Scalerico]</td>\n",
       "      <td>2</td>\n",
       "      <td>[Democratic, Democratic]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>253</th>\n",
       "      <td>2</td>\n",
       "      <td>constable</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>KENNEDY</td>\n",
       "      <td>[John Buckley, III]</td>\n",
       "      <td>1</td>\n",
       "      <td>[Democratic]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>278</th>\n",
       "      <td>2</td>\n",
       "      <td>constable</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MCCANDLESS</td>\n",
       "      <td>[Nathan Wolfe]</td>\n",
       "      <td>1</td>\n",
       "      <td>[Republican]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>303</th>\n",
       "      <td>2</td>\n",
       "      <td>constable</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MOUNT LEBANON</td>\n",
       "      <td>[Dimitro C. Kulik]</td>\n",
       "      <td>1</td>\n",
       "      <td>[Republican]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>315</th>\n",
       "      <td>2</td>\n",
       "      <td>constable</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NEVILLE</td>\n",
       "      <td>[James K. Claytor]</td>\n",
       "      <td>1</td>\n",
       "      <td>[Democratic]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>327</th>\n",
       "      <td>2</td>\n",
       "      <td>constable</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NORTH VERSAILLES</td>\n",
       "      <td>[Thomas R. Leicht, Jr.]</td>\n",
       "      <td>1</td>\n",
       "      <td>[Democratic]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>339</th>\n",
       "      <td>2</td>\n",
       "      <td>constable</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>OHARA</td>\n",
       "      <td>[Francis Peitz]</td>\n",
       "      <td>1</td>\n",
       "      <td>[Democratic]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>381</th>\n",
       "      <td>2</td>\n",
       "      <td>constable</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ROBINSON</td>\n",
       "      <td>[Craig M. Cannella]</td>\n",
       "      <td>1</td>\n",
       "      <td>[Democratic]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>434</th>\n",
       "      <td>2</td>\n",
       "      <td>constable</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>STOWE</td>\n",
       "      <td>[Patrick S. Jennings, Sr.]</td>\n",
       "      <td>1</td>\n",
       "      <td>[Democratic]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>479</th>\n",
       "      <td>4</td>\n",
       "      <td>member of council</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>WEST ELIZABETH</td>\n",
       "      <td>[Lisa Morris, Louise M. Biddle, Raymond P. Dod...</td>\n",
       "      <td>3</td>\n",
       "      <td>[Democratic, Democratic, Democratic]</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     number           position term  ward            district  \\\n",
       "38        3  member of council  NaN   NaN    BEN AVON HEIGHTS   \n",
       "57        4  member of council  NaN   NaN      BRADDOCK HILLS   \n",
       "86        4  member of council  NaN   NaN            CHESWICK   \n",
       "98        2          constable  NaN   NaN             COLLIER   \n",
       "111       2          constable  NaN   NaN            CRESCENT   \n",
       "114       4  member of council  NaN   NaN             DORMONT   \n",
       "147       4  member of council  NaN   NaN   ELIZABETH BOROUGH   \n",
       "151       2          constable  NaN   NaN  ELIZABETH TOWNSHIP   \n",
       "154       4  member of council  NaN   NaN            EMSWORTH   \n",
       "197       4  member of council  NaN   NaN        GLEN OSBORNE   \n",
       "253       2          constable  NaN   NaN             KENNEDY   \n",
       "278       2          constable  NaN   NaN          MCCANDLESS   \n",
       "303       2          constable  NaN   NaN       MOUNT LEBANON   \n",
       "315       2          constable  NaN   NaN             NEVILLE   \n",
       "327       2          constable  NaN   NaN    NORTH VERSAILLES   \n",
       "339       2          constable  NaN   NaN               OHARA   \n",
       "381       2          constable  NaN   NaN            ROBINSON   \n",
       "434       2          constable  NaN   NaN               STOWE   \n",
       "479       4  member of council  NaN   NaN      WEST ELIZABETH   \n",
       "\n",
       "                                            candidates  candidate_count  \\\n",
       "38                                  [Joseph M. Dawley]                1   \n",
       "57   [Anette Nance, Marguerite L. Bolton, Cassandra...                3   \n",
       "86         [Frank Meledandri Jr., Kathleen M. Gillard]                2   \n",
       "98                                  [Daniel A. Styche]                1   \n",
       "111                               [Daniel Perciavalle]                1   \n",
       "114  [Jennifer Mazzocco, Alvaro A. Varela, III, Ile...                3   \n",
       "147                           [Chad Rager, Dana Cress]                2   \n",
       "151                                       [Gary Corey]                1   \n",
       "154                     [Kevin Yurkovich, Daniel Lenz]                2   \n",
       "197                    [John Orndorff, Mary Scalerico]                2   \n",
       "253                                [John Buckley, III]                1   \n",
       "278                                     [Nathan Wolfe]                1   \n",
       "303                                 [Dimitro C. Kulik]                1   \n",
       "315                                 [James K. Claytor]                1   \n",
       "327                            [Thomas R. Leicht, Jr.]                1   \n",
       "339                                    [Francis Peitz]                1   \n",
       "381                                [Craig M. Cannella]                1   \n",
       "434                         [Patrick S. Jennings, Sr.]                1   \n",
       "479  [Lisa Morris, Louise M. Biddle, Raymond P. Dod...                3   \n",
       "\n",
       "                                    party  \n",
       "38                           [Democratic]  \n",
       "57   [Democratic, Democratic, Democratic]  \n",
       "86               [Republican, Republican]  \n",
       "98                           [Democratic]  \n",
       "111                          [Democratic]  \n",
       "114  [Democratic, Democratic, Democratic]  \n",
       "147              [Democratic, Democratic]  \n",
       "151                          [Republican]  \n",
       "154              [Democratic, Democratic]  \n",
       "197              [Democratic, Democratic]  \n",
       "253                          [Democratic]  \n",
       "278                          [Republican]  \n",
       "303                          [Republican]  \n",
       "315                          [Democratic]  \n",
       "327                          [Democratic]  \n",
       "339                          [Democratic]  \n",
       "381                          [Democratic]  \n",
       "434                          [Democratic]  \n",
       "479  [Democratic, Democratic, Democratic]  "
      ]
     },
     "execution_count": 104,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "not_enough_candidates_df = mc_df[lambda df: df.candidate_count!=0][mc_df.candidate_count<mc_df.number]\n",
    "not_enough_candidates_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "id": "unlike-infection",
   "metadata": {},
   "outputs": [],
   "source": [
    "not_enough_candidates_df.to_csv(\"not_enough_candidates.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "endless-sharing",
   "metadata": {},
   "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": "3.8.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}