dataset-combiner.ipynb

{
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  {
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   "execution_count": 1,
   "id": "273c3a5b-8c5f-47da-9ca5-33bd6c39a67f",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import plotly as pl\n",
    "import seaborn as sns\n",
    "import warnings\n",
    "warnings.filterwarnings(\"ignore\")\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8f3f5ef9-2530-4357-9529-8bd1147599ea",
   "metadata": {},
   "source": [
    "## BLS Dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "3e270432-07cc-4a7d-95c9-9dd4b67875c9",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Organizations involved</th>\n",
       "      <th>States</th>\n",
       "      <th>Areas</th>\n",
       "      <th>Ownership</th>\n",
       "      <th>Industry code[1]</th>\n",
       "      <th>Union</th>\n",
       "      <th>Union acronym</th>\n",
       "      <th>Union Local</th>\n",
       "      <th>Bargaining unit</th>\n",
       "      <th>Work stoppage beginning date</th>\n",
       "      <th>Work stoppage ending date</th>\n",
       "      <th>Number of workers[2]</th>\n",
       "      <th>Days idle, cumulative for this work stoppage[3]</th>\n",
       "      <th>Note</th>\n",
       "      <th>NAICS_col</th>\n",
       "      <th>start_year</th>\n",
       "      <th>end_year</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Boeing Company</td>\n",
       "      <td>WA</td>\n",
       "      <td>Seattle</td>\n",
       "      <td>Private industry</td>\n",
       "      <td>336411</td>\n",
       "      <td>Seattle Professional Engineering Employees Ass...</td>\n",
       "      <td>SPEEA</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1993-01-19</td>\n",
       "      <td>1993-01-19</td>\n",
       "      <td>21000.0</td>\n",
       "      <td>21000.0</td>\n",
       "      <td>The union name was changed to the Society of P...</td>\n",
       "      <td>33</td>\n",
       "      <td>1993</td>\n",
       "      <td>1993</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Boston Gas Company</td>\n",
       "      <td>MA</td>\n",
       "      <td>Boston</td>\n",
       "      <td>Private industry</td>\n",
       "      <td>22121</td>\n",
       "      <td>United Steelworkers</td>\n",
       "      <td>USW</td>\n",
       "      <td>12003</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1993-01-24</td>\n",
       "      <td>1993-05-20</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>83000.0</td>\n",
       "      <td>Boston Gas Company also does business as \"Nati...</td>\n",
       "      <td>22</td>\n",
       "      <td>1993</td>\n",
       "      <td>1993</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Bituminous Coal Operators Association</td>\n",
       "      <td>IN, IL, KY, WV</td>\n",
       "      <td>Multiple states</td>\n",
       "      <td>Private industry</td>\n",
       "      <td>212112</td>\n",
       "      <td>United Mine Workers of America</td>\n",
       "      <td>UMWA</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1993-02-02</td>\n",
       "      <td>1993-03-02</td>\n",
       "      <td>6700.0</td>\n",
       "      <td>103400.0</td>\n",
       "      <td>Number of workers involved increased from 5,00...</td>\n",
       "      <td>21</td>\n",
       "      <td>1993</td>\n",
       "      <td>1993</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Douglas Aircraft</td>\n",
       "      <td>CA</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Private industry</td>\n",
       "      <td>336411</td>\n",
       "      <td>International Association of Machinists</td>\n",
       "      <td>IAM</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1993-03-02</td>\n",
       "      <td>1993-03-03</td>\n",
       "      <td>6800.0</td>\n",
       "      <td>13600.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>33</td>\n",
       "      <td>1993</td>\n",
       "      <td>1993</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Allied Signal Corp.</td>\n",
       "      <td>VA</td>\n",
       "      <td>Hopewell</td>\n",
       "      <td>Private industry</td>\n",
       "      <td>325222</td>\n",
       "      <td>International Brotherhood of Teamsters</td>\n",
       "      <td>IBT</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1993-03-22</td>\n",
       "      <td>1993-04-21</td>\n",
       "      <td>1600.0</td>\n",
       "      <td>36800.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>32</td>\n",
       "      <td>1993</td>\n",
       "      <td>1993</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  Organizations involved          States            Areas  \\\n",
       "1                         Boeing Company              WA          Seattle   \n",
       "2                     Boston Gas Company              MA           Boston   \n",
       "3  Bituminous Coal Operators Association  IN, IL, KY, WV  Multiple states   \n",
       "4                       Douglas Aircraft              CA              NaN   \n",
       "5                    Allied Signal Corp.              VA         Hopewell   \n",
       "\n",
       "          Ownership Industry code[1]  \\\n",
       "1  Private industry           336411   \n",
       "2  Private industry            22121   \n",
       "3  Private industry           212112   \n",
       "4  Private industry           336411   \n",
       "5  Private industry           325222   \n",
       "\n",
       "                                               Union Union acronym  \\\n",
       "1  Seattle Professional Engineering Employees Ass...         SPEEA   \n",
       "2                                United Steelworkers           USW   \n",
       "3                     United Mine Workers of America          UMWA   \n",
       "4            International Association of Machinists           IAM   \n",
       "5             International Brotherhood of Teamsters           IBT   \n",
       "\n",
       "  Union Local Bargaining unit Work stoppage beginning date  \\\n",
       "1         NaN             NaN                   1993-01-19   \n",
       "2       12003             NaN                   1993-01-24   \n",
       "3         NaN             NaN                   1993-02-02   \n",
       "4         NaN             NaN                   1993-03-02   \n",
       "5         NaN             NaN                   1993-03-22   \n",
       "\n",
       "  Work stoppage ending date  Number of workers[2]  \\\n",
       "1                1993-01-19               21000.0   \n",
       "2                1993-05-20                1000.0   \n",
       "3                1993-03-02                6700.0   \n",
       "4                1993-03-03                6800.0   \n",
       "5                1993-04-21                1600.0   \n",
       "\n",
       "   Days idle, cumulative for this work stoppage[3]  \\\n",
       "1                                          21000.0   \n",
       "2                                          83000.0   \n",
       "3                                         103400.0   \n",
       "4                                          13600.0   \n",
       "5                                          36800.0   \n",
       "\n",
       "                                                Note NAICS_col  start_year  \\\n",
       "1  The union name was changed to the Society of P...        33        1993   \n",
       "2  Boston Gas Company also does business as \"Nati...        22        1993   \n",
       "3  Number of workers involved increased from 5,00...        21        1993   \n",
       "4                                                NaN        33        1993   \n",
       "5                                                NaN        32        1993   \n",
       "\n",
       "   end_year  \n",
       "1      1993  \n",
       "2      1993  \n",
       "3      1993  \n",
       "4      1993  \n",
       "5      1993  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bls_df = pd.read_excel(\"monthly-listing-3.xlsx\",header=1)\n",
    "bls_df = bls_df[~bls_df['States'].isna()]\n",
    "bls_df[\"NAICS_col\"] = bls_df[\"Industry code[1]\"].astype(str).str[:2]\n",
    "bls_df[\"start_year\"] = pd.DatetimeIndex(bls_df[\"Work stoppage beginning date\"]).year\n",
    "bls_df[\"end_year\"] = pd.DatetimeIndex(bls_df[\"Work stoppage ending date\"]).year\n",
    "bls_df = bls_df[bls_df['start_year'] >= 1993]\n",
    "bls_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "2fe6e13a-aef5-4cfb-9437-3e849bb38cc9",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Organizations involved</th>\n",
       "      <th>States</th>\n",
       "      <th>Areas</th>\n",
       "      <th>Ownership</th>\n",
       "      <th>Industry code[1]</th>\n",
       "      <th>Union</th>\n",
       "      <th>Union acronym</th>\n",
       "      <th>Union Local</th>\n",
       "      <th>Bargaining unit</th>\n",
       "      <th>Work stoppage beginning date</th>\n",
       "      <th>Work stoppage ending date</th>\n",
       "      <th>Number of workers[2]</th>\n",
       "      <th>Days idle, cumulative for this work stoppage[3]</th>\n",
       "      <th>Note</th>\n",
       "      <th>NAICS_col</th>\n",
       "      <th>start_year</th>\n",
       "      <th>end_year</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Boeing Company</td>\n",
       "      <td>WA</td>\n",
       "      <td>Seattle</td>\n",
       "      <td>Private industry</td>\n",
       "      <td>336411</td>\n",
       "      <td>Seattle Professional Engineering Employees Ass...</td>\n",
       "      <td>SPEEA</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1993-01-19</td>\n",
       "      <td>1993-01-19</td>\n",
       "      <td>21000.0</td>\n",
       "      <td>21000.0</td>\n",
       "      <td>The union name was changed to the Society of P...</td>\n",
       "      <td>33</td>\n",
       "      <td>1993.0</td>\n",
       "      <td>1993.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Boston Gas Company</td>\n",
       "      <td>MA</td>\n",
       "      <td>Boston</td>\n",
       "      <td>Private industry</td>\n",
       "      <td>22121</td>\n",
       "      <td>United Steelworkers</td>\n",
       "      <td>USW</td>\n",
       "      <td>12003</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1993-01-24</td>\n",
       "      <td>1993-05-20</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>83000.0</td>\n",
       "      <td>Boston Gas Company also does business as \"Nati...</td>\n",
       "      <td>22</td>\n",
       "      <td>1993.0</td>\n",
       "      <td>1993.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Bituminous Coal Operators Association</td>\n",
       "      <td>IN</td>\n",
       "      <td>Multiple states</td>\n",
       "      <td>Private industry</td>\n",
       "      <td>212112</td>\n",
       "      <td>United Mine Workers of America</td>\n",
       "      <td>UMWA</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1993-02-02</td>\n",
       "      <td>1993-03-02</td>\n",
       "      <td>6700.0</td>\n",
       "      <td>103400.0</td>\n",
       "      <td>Number of workers involved increased from 5,00...</td>\n",
       "      <td>21</td>\n",
       "      <td>1993.0</td>\n",
       "      <td>1993.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Douglas Aircraft</td>\n",
       "      <td>CA</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Private industry</td>\n",
       "      <td>336411</td>\n",
       "      <td>International Association of Machinists</td>\n",
       "      <td>IAM</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1993-03-02</td>\n",
       "      <td>1993-03-03</td>\n",
       "      <td>6800.0</td>\n",
       "      <td>13600.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>33</td>\n",
       "      <td>1993.0</td>\n",
       "      <td>1993.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Allied Signal Corp.</td>\n",
       "      <td>VA</td>\n",
       "      <td>Hopewell</td>\n",
       "      <td>Private industry</td>\n",
       "      <td>325222</td>\n",
       "      <td>International Brotherhood of Teamsters</td>\n",
       "      <td>IBT</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1993-03-22</td>\n",
       "      <td>1993-04-21</td>\n",
       "      <td>1600.0</td>\n",
       "      <td>36800.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>32</td>\n",
       "      <td>1993.0</td>\n",
       "      <td>1993.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  Organizations involved States            Areas  \\\n",
       "1                         Boeing Company     WA          Seattle   \n",
       "2                     Boston Gas Company     MA           Boston   \n",
       "3  Bituminous Coal Operators Association     IN  Multiple states   \n",
       "4                       Douglas Aircraft     CA              NaN   \n",
       "5                    Allied Signal Corp.     VA         Hopewell   \n",
       "\n",
       "          Ownership Industry code[1]  \\\n",
       "1  Private industry           336411   \n",
       "2  Private industry            22121   \n",
       "3  Private industry           212112   \n",
       "4  Private industry           336411   \n",
       "5  Private industry           325222   \n",
       "\n",
       "                                               Union Union acronym  \\\n",
       "1  Seattle Professional Engineering Employees Ass...         SPEEA   \n",
       "2                                United Steelworkers           USW   \n",
       "3                     United Mine Workers of America          UMWA   \n",
       "4            International Association of Machinists           IAM   \n",
       "5             International Brotherhood of Teamsters           IBT   \n",
       "\n",
       "  Union Local Bargaining unit Work stoppage beginning date  \\\n",
       "1         NaN             NaN                   1993-01-19   \n",
       "2       12003             NaN                   1993-01-24   \n",
       "3         NaN             NaN                   1993-02-02   \n",
       "4         NaN             NaN                   1993-03-02   \n",
       "5         NaN             NaN                   1993-03-22   \n",
       "\n",
       "  Work stoppage ending date  Number of workers[2]  \\\n",
       "1                1993-01-19               21000.0   \n",
       "2                1993-05-20                1000.0   \n",
       "3                1993-03-02                6700.0   \n",
       "4                1993-03-03                6800.0   \n",
       "5                1993-04-21                1600.0   \n",
       "\n",
       "   Days idle, cumulative for this work stoppage[3]  \\\n",
       "1                                          21000.0   \n",
       "2                                          83000.0   \n",
       "3                                         103400.0   \n",
       "4                                          13600.0   \n",
       "5                                          36800.0   \n",
       "\n",
       "                                                Note NAICS_col  start_year  \\\n",
       "1  The union name was changed to the Society of P...        33      1993.0   \n",
       "2  Boston Gas Company also does business as \"Nati...        22      1993.0   \n",
       "3  Number of workers involved increased from 5,00...        21      1993.0   \n",
       "4                                                NaN        33      1993.0   \n",
       "5                                                NaN        32      1993.0   \n",
       "\n",
       "   end_year  \n",
       "1    1993.0  \n",
       "2    1993.0  \n",
       "3    1993.0  \n",
       "4    1993.0  \n",
       "5    1993.0  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "testing_df = bls_df.copy()\n",
    "for index, row in testing_df.iterrows():\n",
    "    if \",\" in row['States']:\n",
    "        states_list = row['States'].split(\",\")\n",
    "        testing_df.loc[index, 'States'] = states_list[0]\n",
    "        for i in np.arange(1,len(states_list)):\n",
    "            row_2 = row\n",
    "            row_2['States'] = states_list[i]\n",
    "            testing_df.loc[testing_df.index.max()+1, :] = row_2\n",
    "bls_df = testing_df\n",
    "bls_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "6b825feb-e288-4c13-9805-524f2bdc5faf",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Organizations involved</th>\n",
       "      <th>States</th>\n",
       "      <th>Areas</th>\n",
       "      <th>Ownership</th>\n",
       "      <th>Industry code[1]</th>\n",
       "      <th>Union</th>\n",
       "      <th>Union acronym</th>\n",
       "      <th>Union Local</th>\n",
       "      <th>Bargaining unit</th>\n",
       "      <th>Work stoppage beginning date</th>\n",
       "      <th>Work stoppage ending date</th>\n",
       "      <th>Number of workers[2]</th>\n",
       "      <th>Days idle, cumulative for this work stoppage[3]</th>\n",
       "      <th>Note</th>\n",
       "      <th>NAICS_col</th>\n",
       "      <th>start_year</th>\n",
       "      <th>end_year</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Boeing Company</td>\n",
       "      <td>WA</td>\n",
       "      <td>Seattle</td>\n",
       "      <td>Private industry</td>\n",
       "      <td>336411</td>\n",
       "      <td>Seattle Professional Engineering Employees Ass...</td>\n",
       "      <td>SPEEA</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1993-01-19</td>\n",
       "      <td>1993-01-19</td>\n",
       "      <td>21000.0</td>\n",
       "      <td>21000.0</td>\n",
       "      <td>The union name was changed to the Society of P...</td>\n",
       "      <td>33</td>\n",
       "      <td>1993.0</td>\n",
       "      <td>1993.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Boston Gas Company</td>\n",
       "      <td>MA</td>\n",
       "      <td>Boston</td>\n",
       "      <td>Private industry</td>\n",
       "      <td>22121</td>\n",
       "      <td>United Steelworkers</td>\n",
       "      <td>USW</td>\n",
       "      <td>12003</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1993-01-24</td>\n",
       "      <td>1993-05-20</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>83000.0</td>\n",
       "      <td>Boston Gas Company also does business as \"Nati...</td>\n",
       "      <td>22</td>\n",
       "      <td>1993.0</td>\n",
       "      <td>1993.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Bituminous Coal Operators Association</td>\n",
       "      <td>IN</td>\n",
       "      <td>Multiple states</td>\n",
       "      <td>Private industry</td>\n",
       "      <td>212112</td>\n",
       "      <td>United Mine Workers of America</td>\n",
       "      <td>UMWA</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1993-02-02</td>\n",
       "      <td>1993-03-02</td>\n",
       "      <td>6700.0</td>\n",
       "      <td>103400.0</td>\n",
       "      <td>Number of workers involved increased from 5,00...</td>\n",
       "      <td>21</td>\n",
       "      <td>1993.0</td>\n",
       "      <td>1993.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Douglas Aircraft</td>\n",
       "      <td>CA</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Private industry</td>\n",
       "      <td>336411</td>\n",
       "      <td>International Association of Machinists</td>\n",
       "      <td>IAM</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1993-03-02</td>\n",
       "      <td>1993-03-03</td>\n",
       "      <td>6800.0</td>\n",
       "      <td>13600.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>33</td>\n",
       "      <td>1993.0</td>\n",
       "      <td>1993.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Allied Signal Corp.</td>\n",
       "      <td>VA</td>\n",
       "      <td>Hopewell</td>\n",
       "      <td>Private industry</td>\n",
       "      <td>325222</td>\n",
       "      <td>International Brotherhood of Teamsters</td>\n",
       "      <td>IBT</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1993-03-22</td>\n",
       "      <td>1993-04-21</td>\n",
       "      <td>1600.0</td>\n",
       "      <td>36800.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>32</td>\n",
       "      <td>1993.0</td>\n",
       "      <td>1993.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  Organizations involved States            Areas  \\\n",
       "1                         Boeing Company     WA          Seattle   \n",
       "2                     Boston Gas Company     MA           Boston   \n",
       "3  Bituminous Coal Operators Association     IN  Multiple states   \n",
       "4                       Douglas Aircraft     CA              NaN   \n",
       "5                    Allied Signal Corp.     VA         Hopewell   \n",
       "\n",
       "          Ownership Industry code[1]  \\\n",
       "1  Private industry           336411   \n",
       "2  Private industry            22121   \n",
       "3  Private industry           212112   \n",
       "4  Private industry           336411   \n",
       "5  Private industry           325222   \n",
       "\n",
       "                                               Union Union acronym  \\\n",
       "1  Seattle Professional Engineering Employees Ass...         SPEEA   \n",
       "2                                United Steelworkers           USW   \n",
       "3                     United Mine Workers of America          UMWA   \n",
       "4            International Association of Machinists           IAM   \n",
       "5             International Brotherhood of Teamsters           IBT   \n",
       "\n",
       "  Union Local Bargaining unit Work stoppage beginning date  \\\n",
       "1         NaN             NaN                   1993-01-19   \n",
       "2       12003             NaN                   1993-01-24   \n",
       "3         NaN             NaN                   1993-02-02   \n",
       "4         NaN             NaN                   1993-03-02   \n",
       "5         NaN             NaN                   1993-03-22   \n",
       "\n",
       "  Work stoppage ending date  Number of workers[2]  \\\n",
       "1                1993-01-19               21000.0   \n",
       "2                1993-05-20                1000.0   \n",
       "3                1993-03-02                6700.0   \n",
       "4                1993-03-03                6800.0   \n",
       "5                1993-04-21                1600.0   \n",
       "\n",
       "   Days idle, cumulative for this work stoppage[3]  \\\n",
       "1                                          21000.0   \n",
       "2                                          83000.0   \n",
       "3                                         103400.0   \n",
       "4                                          13600.0   \n",
       "5                                          36800.0   \n",
       "\n",
       "                                                Note NAICS_col  start_year  \\\n",
       "1  The union name was changed to the Society of P...        33      1993.0   \n",
       "2  Boston Gas Company also does business as \"Nati...        22      1993.0   \n",
       "3  Number of workers involved increased from 5,00...        21      1993.0   \n",
       "4                                                NaN        33      1993.0   \n",
       "5                                                NaN        32      1993.0   \n",
       "\n",
       "   end_year  \n",
       "1    1993.0  \n",
       "2    1993.0  \n",
       "3    1993.0  \n",
       "4    1993.0  \n",
       "5    1993.0  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bls_df['States'] = bls_df['States'].str.strip()\n",
    "bls_df = bls_df[bls_df['States'].str.len()<=2]\n",
    "bls_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "19701030-82c0-434b-ae15-d3539384c585",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "915.0"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bls_df['num_years'] = bls_df[\"end_year\"] - bls_df[\"start_year\"] + 1\n",
    "bls_df['num_years'].sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "6e492fba-d415-4154-812d-5d4b19b22493",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\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>Organizations involved</th>\n",
       "      <th>States</th>\n",
       "      <th>Areas</th>\n",
       "      <th>Ownership</th>\n",
       "      <th>Industry code[1]</th>\n",
       "      <th>Union</th>\n",
       "      <th>Union acronym</th>\n",
       "      <th>Union Local</th>\n",
       "      <th>Bargaining unit</th>\n",
       "      <th>Work stoppage beginning date</th>\n",
       "      <th>Work stoppage ending date</th>\n",
       "      <th>Number of workers[2]</th>\n",
       "      <th>Days idle, cumulative for this work stoppage[3]</th>\n",
       "      <th>Note</th>\n",
       "      <th>NAICS_col</th>\n",
       "      <th>start_year</th>\n",
       "      <th>end_year</th>\n",
       "      <th>num_years</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Boeing Company</td>\n",
       "      <td>WA</td>\n",
       "      <td>Seattle</td>\n",
       "      <td>Private industry</td>\n",
       "      <td>336411</td>\n",
       "      <td>Seattle Professional Engineering Employees Ass...</td>\n",
       "      <td>SPEEA</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1993-01-19</td>\n",
       "      <td>1993-01-19</td>\n",
       "      <td>21000.0</td>\n",
       "      <td>21000.0</td>\n",
       "      <td>The union name was changed to the Society of P...</td>\n",
       "      <td>33</td>\n",
       "      <td>1993.0</td>\n",
       "      <td>1993.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Boston Gas Company</td>\n",
       "      <td>MA</td>\n",
       "      <td>Boston</td>\n",
       "      <td>Private industry</td>\n",
       "      <td>22121</td>\n",
       "      <td>United Steelworkers</td>\n",
       "      <td>USW</td>\n",
       "      <td>12003</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1993-01-24</td>\n",
       "      <td>1993-05-20</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>83000.0</td>\n",
       "      <td>Boston Gas Company also does business as \"Nati...</td>\n",
       "      <td>22</td>\n",
       "      <td>1993.0</td>\n",
       "      <td>1993.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Bituminous Coal Operators Association</td>\n",
       "      <td>IN</td>\n",
       "      <td>Multiple states</td>\n",
       "      <td>Private industry</td>\n",
       "      <td>212112</td>\n",
       "      <td>United Mine Workers of America</td>\n",
       "      <td>UMWA</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1993-02-02</td>\n",
       "      <td>1993-03-02</td>\n",
       "      <td>6700.0</td>\n",
       "      <td>103400.0</td>\n",
       "      <td>Number of workers involved increased from 5,00...</td>\n",
       "      <td>21</td>\n",
       "      <td>1993.0</td>\n",
       "      <td>1993.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Douglas Aircraft</td>\n",
       "      <td>CA</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Private industry</td>\n",
       "      <td>336411</td>\n",
       "      <td>International Association of Machinists</td>\n",
       "      <td>IAM</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1993-03-02</td>\n",
       "      <td>1993-03-03</td>\n",
       "      <td>6800.0</td>\n",
       "      <td>13600.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>33</td>\n",
       "      <td>1993.0</td>\n",
       "      <td>1993.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Allied Signal Corp.</td>\n",
       "      <td>VA</td>\n",
       "      <td>Hopewell</td>\n",
       "      <td>Private industry</td>\n",
       "      <td>325222</td>\n",
       "      <td>International Brotherhood of Teamsters</td>\n",
       "      <td>IBT</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1993-03-22</td>\n",
       "      <td>1993-04-21</td>\n",
       "      <td>1600.0</td>\n",
       "      <td>36800.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>32</td>\n",
       "      <td>1993.0</td>\n",
       "      <td>1993.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  Organizations involved States            Areas  \\\n",
       "1                         Boeing Company     WA          Seattle   \n",
       "2                     Boston Gas Company     MA           Boston   \n",
       "3  Bituminous Coal Operators Association     IN  Multiple states   \n",
       "4                       Douglas Aircraft     CA              NaN   \n",
       "5                    Allied Signal Corp.     VA         Hopewell   \n",
       "\n",
       "          Ownership Industry code[1]  \\\n",
       "1  Private industry           336411   \n",
       "2  Private industry            22121   \n",
       "3  Private industry           212112   \n",
       "4  Private industry           336411   \n",
       "5  Private industry           325222   \n",
       "\n",
       "                                               Union Union acronym  \\\n",
       "1  Seattle Professional Engineering Employees Ass...         SPEEA   \n",
       "2                                United Steelworkers           USW   \n",
       "3                     United Mine Workers of America          UMWA   \n",
       "4            International Association of Machinists           IAM   \n",
       "5             International Brotherhood of Teamsters           IBT   \n",
       "\n",
       "  Union Local Bargaining unit Work stoppage beginning date  \\\n",
       "1         NaN             NaN                   1993-01-19   \n",
       "2       12003             NaN                   1993-01-24   \n",
       "3         NaN             NaN                   1993-02-02   \n",
       "4         NaN             NaN                   1993-03-02   \n",
       "5         NaN             NaN                   1993-03-22   \n",
       "\n",
       "  Work stoppage ending date  Number of workers[2]  \\\n",
       "1                1993-01-19               21000.0   \n",
       "2                1993-05-20                1000.0   \n",
       "3                1993-03-02                6700.0   \n",
       "4                1993-03-03                6800.0   \n",
       "5                1993-04-21                1600.0   \n",
       "\n",
       "   Days idle, cumulative for this work stoppage[3]  \\\n",
       "1                                          21000.0   \n",
       "2                                          83000.0   \n",
       "3                                         103400.0   \n",
       "4                                          13600.0   \n",
       "5                                          36800.0   \n",
       "\n",
       "                                                Note NAICS_col  start_year  \\\n",
       "1  The union name was changed to the Society of P...        33      1993.0   \n",
       "2  Boston Gas Company also does business as \"Nati...        22      1993.0   \n",
       "3  Number of workers involved increased from 5,00...        21      1993.0   \n",
       "4                                                NaN        33      1993.0   \n",
       "5                                                NaN        32      1993.0   \n",
       "\n",
       "   end_year  num_years  \n",
       "1    1993.0        1.0  \n",
       "2    1993.0        1.0  \n",
       "3    1993.0        1.0  \n",
       "4    1993.0        1.0  \n",
       "5    1993.0        1.0  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "testing_df = bls_df.copy()\n",
    "for index, row in testing_df.iterrows():\n",
    "    if row['num_years'] > 1:\n",
    "        i = row['num_years']-1\n",
    "        start_year = row['start_year']\n",
    "        while i != 0:\n",
    "            row_2 = row\n",
    "            row_2['start_year'] = start_year + i\n",
    "            testing_df.loc[testing_df.index.max()+1, :] = row_2\n",
    "            i = i - 1\n",
    "bls_df = testing_df\n",
    "bls_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "a2abe1ff-3e71-4170-bc6f-aeb977976dfe",
   "metadata": {},
   "outputs": [],
   "source": [
    "bls_df.to_csv('bls_testing.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "32bb11d8-ff29-452d-91e2-4b48a550579f",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>States</th>\n",
       "      <th>start_year</th>\n",
       "      <th>Number of workers[2]</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>AK</td>\n",
       "      <td>1994.0</td>\n",
       "      <td>2900.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>AK</td>\n",
       "      <td>1999.0</td>\n",
       "      <td>1000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>AL</td>\n",
       "      <td>1993.0</td>\n",
       "      <td>1200.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>AL</td>\n",
       "      <td>1994.0</td>\n",
       "      <td>3200.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>AL</td>\n",
       "      <td>1996.0</td>\n",
       "      <td>1100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>486</th>\n",
       "      <td>WV</td>\n",
       "      <td>2003.0</td>\n",
       "      <td>3200.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>487</th>\n",
       "      <td>WV</td>\n",
       "      <td>2015.0</td>\n",
       "      <td>2200.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>488</th>\n",
       "      <td>WV</td>\n",
       "      <td>2016.0</td>\n",
       "      <td>2200.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>489</th>\n",
       "      <td>WV</td>\n",
       "      <td>2018.0</td>\n",
       "      <td>36400.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>490</th>\n",
       "      <td>WV</td>\n",
       "      <td>2019.0</td>\n",
       "      <td>36400.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>491 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    States  start_year  Number of workers[2]\n",
       "0       AK      1994.0                2900.0\n",
       "1       AK      1999.0                1000.0\n",
       "2       AL      1993.0                1200.0\n",
       "3       AL      1994.0                3200.0\n",
       "4       AL      1996.0                1100.0\n",
       "..     ...         ...                   ...\n",
       "486     WV      2003.0                3200.0\n",
       "487     WV      2015.0                2200.0\n",
       "488     WV      2016.0                2200.0\n",
       "489     WV      2018.0               36400.0\n",
       "490     WV      2019.0               36400.0\n",
       "\n",
       "[491 rows x 3 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "grouped_bls_df = bls_df.groupby(['States','start_year'])['Number of workers[2]'].sum().reset_index()\n",
    "grouped_bls_df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "eb9226f6-c04f-488f-934f-58c0a710149f",
   "metadata": {},
   "source": [
    "## FMCS Dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "bdc9aaf2-6a36-4797-a2c6-56325d1980ef",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
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       "      <th></th>\n",
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       "      <th>Union</th>\n",
       "      <th>Union Local</th>\n",
       "      <th>Case Number</th>\n",
       "      <th>BU</th>\n",
       "      <th>NAICS</th>\n",
       "      <th>Industry</th>\n",
       "      <th>City, State</th>\n",
       "      <th># Idled</th>\n",
       "      <th>Start Date</th>\n",
       "      <th>End Date</th>\n",
       "      <th>Duration</th>\n",
       "      <th>start_year</th>\n",
       "      <th>end_year</th>\n",
       "      <th>State</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>6814</th>\n",
       "      <td>Caterpillar Inc</td>\n",
       "      <td>UAW MULTI</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1991JU003706</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Manufacturing</td>\n",
       "      <td>Peoria, IL</td>\n",
       "      <td>11500.0</td>\n",
       "      <td>6/21/94</td>\n",
       "      <td>12/4/95</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1994</td>\n",
       "      <td>1995.0</td>\n",
       "      <td>IL</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7365</th>\n",
       "      <td>Douglas Aircraft Company (two Locations)</td>\n",
       "      <td>IAM 720</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1992KR003410</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Manufacturing</td>\n",
       "      <td>Torrance, CA</td>\n",
       "      <td>6759.0</td>\n",
       "      <td>3/2/93</td>\n",
       "      <td>3/3/93</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1993</td>\n",
       "      <td>1993.0</td>\n",
       "      <td>CA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7497</th>\n",
       "      <td>Boeing Company The</td>\n",
       "      <td>SPEEA</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1993BP000528</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Manufacturing</td>\n",
       "      <td>Seattle, WA</td>\n",
       "      <td>7000.0</td>\n",
       "      <td>1/21/93</td>\n",
       "      <td>1/22/93</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1993</td>\n",
       "      <td>1993.0</td>\n",
       "      <td>WA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7522</th>\n",
       "      <td>Independent Bituminous Coal Bargaining Allianc...</td>\n",
       "      <td>UMW</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1993CN000462</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Mining, Quarrying and Oil &amp; Gas Extraction</td>\n",
       "      <td>Birmingham, AL</td>\n",
       "      <td>1200.0</td>\n",
       "      <td>7/14/93</td>\n",
       "      <td>7/16/93</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1993</td>\n",
       "      <td>1993.0</td>\n",
       "      <td>AL</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7524</th>\n",
       "      <td>Fieldcrest Cannon Inc (section 28)</td>\n",
       "      <td>ACTWU BI COUNTY N NC &amp; S GA DIST</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1993CN000511</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Manufacturing</td>\n",
       "      <td>Eden, NC</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>5/17/93</td>\n",
       "      <td>5/19/93</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1993</td>\n",
       "      <td>1993.0</td>\n",
       "      <td>NC</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                               Employer  \\\n",
       "6814                                    Caterpillar Inc   \n",
       "7365           Douglas Aircraft Company (two Locations)   \n",
       "7497                                 Boeing Company The   \n",
       "7522  Independent Bituminous Coal Bargaining Allianc...   \n",
       "7524                 Fieldcrest Cannon Inc (section 28)   \n",
       "\n",
       "                                 Union Union Local   Case Number  BU  NAICS  \\\n",
       "6814                         UAW MULTI         NaN  1991JU003706 NaN    NaN   \n",
       "7365                           IAM 720         NaN  1992KR003410 NaN    NaN   \n",
       "7497                             SPEEA         NaN  1993BP000528 NaN    NaN   \n",
       "7522                               UMW         NaN  1993CN000462 NaN    NaN   \n",
       "7524  ACTWU BI COUNTY N NC & S GA DIST         NaN  1993CN000511 NaN    NaN   \n",
       "\n",
       "                                        Industry     City, State  # Idled  \\\n",
       "6814                               Manufacturing      Peoria, IL  11500.0   \n",
       "7365                               Manufacturing    Torrance, CA   6759.0   \n",
       "7497                               Manufacturing     Seattle, WA   7000.0   \n",
       "7522  Mining, Quarrying and Oil & Gas Extraction  Birmingham, AL   1200.0   \n",
       "7524                               Manufacturing        Eden, NC   1500.0   \n",
       "\n",
       "     Start Date End Date  Duration  start_year  end_year State  \n",
       "6814    6/21/94  12/4/95       NaN        1994    1995.0    IL  \n",
       "7365     3/2/93   3/3/93       NaN        1993    1993.0    CA  \n",
       "7497    1/21/93  1/22/93       NaN        1993    1993.0    WA  \n",
       "7522    7/14/93  7/16/93       NaN        1993    1993.0    AL  \n",
       "7524    5/17/93  5/19/93       NaN        1993    1993.0    NC  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "FMCS_df = pd.read_csv(\"work_stoppages.csv\")\n",
    "FMCS_df = FMCS_df[~FMCS_df['City, State'].isna()]\n",
    "FMCS_df = FMCS_df[FMCS_df['# Idled'] >= 1000]\n",
    "FMCS_df[\"start_year\"] = pd.DatetimeIndex(FMCS_df[\"Start Date\"]).year\n",
    "FMCS_df[\"end_year\"] = pd.DatetimeIndex(FMCS_df[\"End Date\"]).year\n",
    "FMCS_df = FMCS_df[~FMCS_df['City, State'].str.endswith(\", \")]\n",
    "FMCS_df['State'] = FMCS_df['City, State'].str[-2:]\n",
    "FMCS_df = FMCS_df[FMCS_df['start_year'] >= 1993]\n",
    "FMCS_df = FMCS_df[~(FMCS_df[\"Start Date\"] == FMCS_df[\"End Date\"])]\n",
    "FMCS_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "35fe076a-4273-480a-a761-8d0c495801dd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Employer</th>\n",
       "      <th>Union</th>\n",
       "      <th>Union Local</th>\n",
       "      <th>Case Number</th>\n",
       "      <th>BU</th>\n",
       "      <th>NAICS</th>\n",
       "      <th>Industry</th>\n",
       "      <th>City, State</th>\n",
       "      <th># Idled</th>\n",
       "      <th>Start Date</th>\n",
       "      <th>End Date</th>\n",
       "      <th>Duration</th>\n",
       "      <th>start_year</th>\n",
       "      <th>end_year</th>\n",
       "      <th>State</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Empty DataFrame\n",
       "Columns: [Employer, Union, Union Local, Case Number, BU, NAICS, Industry, City, State, # Idled, Start Date, End Date, Duration, start_year, end_year, State]\n",
       "Index: []"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "end_years_list = pd.DatetimeIndex(pd.DatetimeIndex(FMCS_df[(FMCS_df[\"end_year\"].isna()) & ~(FMCS_df[\"Duration\"].isna())]['Start Date']) + pd.to_timedelta(\n",
    "    FMCS_df[(FMCS_df[\"end_year\"].isna()) & ~(FMCS_df[\"Duration\"].isna())]['Duration'], unit='D')).year\n",
    "FMCS_df.loc[(FMCS_df[\"end_year\"].isna()) & ~(FMCS_df[\"Duration\"].isna()), \"end_year\"] = end_years_list\n",
    "FMCS_df.loc[(FMCS_df[\"end_year\"].isna()), \"end_year\"] = FMCS_df.loc[(FMCS_df[\"end_year\"].isna()), \"start_year\"]\n",
    "FMCS_df.loc[(FMCS_df[\"end_year\"].isna()), :]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "65dd2c49-1467-4ddf-b08f-bd1c8f4f0f87",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Employer</th>\n",
       "      <th>Union</th>\n",
       "      <th>Union Local</th>\n",
       "      <th>Case Number</th>\n",
       "      <th>BU</th>\n",
       "      <th>NAICS</th>\n",
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       "      <th>num_years</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>6814</th>\n",
       "      <td>Caterpillar Inc</td>\n",
       "      <td>UAW MULTI</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1991JU003706</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Manufacturing</td>\n",
       "      <td>Peoria, IL</td>\n",
       "      <td>11500.0</td>\n",
       "      <td>6/21/94</td>\n",
       "      <td>12/4/95</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1994</td>\n",
       "      <td>1995.0</td>\n",
       "      <td>IL</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7365</th>\n",
       "      <td>Douglas Aircraft Company (two Locations)</td>\n",
       "      <td>IAM 720</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1992KR003410</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Manufacturing</td>\n",
       "      <td>Torrance, CA</td>\n",
       "      <td>6759.0</td>\n",
       "      <td>3/2/93</td>\n",
       "      <td>3/3/93</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1993</td>\n",
       "      <td>1993.0</td>\n",
       "      <td>CA</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7497</th>\n",
       "      <td>Boeing Company The</td>\n",
       "      <td>SPEEA</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1993BP000528</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Manufacturing</td>\n",
       "      <td>Seattle, WA</td>\n",
       "      <td>7000.0</td>\n",
       "      <td>1/21/93</td>\n",
       "      <td>1/22/93</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1993</td>\n",
       "      <td>1993.0</td>\n",
       "      <td>WA</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7522</th>\n",
       "      <td>Independent Bituminous Coal Bargaining Allianc...</td>\n",
       "      <td>UMW</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1993CN000462</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Mining, Quarrying and Oil &amp; Gas Extraction</td>\n",
       "      <td>Birmingham, AL</td>\n",
       "      <td>1200.0</td>\n",
       "      <td>7/14/93</td>\n",
       "      <td>7/16/93</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1993</td>\n",
       "      <td>1993.0</td>\n",
       "      <td>AL</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7524</th>\n",
       "      <td>Fieldcrest Cannon Inc (section 28)</td>\n",
       "      <td>ACTWU BI COUNTY N NC &amp; S GA DIST</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1993CN000511</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Manufacturing</td>\n",
       "      <td>Eden, NC</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>5/17/93</td>\n",
       "      <td>5/19/93</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1993</td>\n",
       "      <td>1993.0</td>\n",
       "      <td>NC</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                               Employer  \\\n",
       "6814                                    Caterpillar Inc   \n",
       "7365           Douglas Aircraft Company (two Locations)   \n",
       "7497                                 Boeing Company The   \n",
       "7522  Independent Bituminous Coal Bargaining Allianc...   \n",
       "7524                 Fieldcrest Cannon Inc (section 28)   \n",
       "\n",
       "                                 Union Union Local   Case Number  BU  NAICS  \\\n",
       "6814                         UAW MULTI         NaN  1991JU003706 NaN    NaN   \n",
       "7365                           IAM 720         NaN  1992KR003410 NaN    NaN   \n",
       "7497                             SPEEA         NaN  1993BP000528 NaN    NaN   \n",
       "7522                               UMW         NaN  1993CN000462 NaN    NaN   \n",
       "7524  ACTWU BI COUNTY N NC & S GA DIST         NaN  1993CN000511 NaN    NaN   \n",
       "\n",
       "                                        Industry     City, State  # Idled  \\\n",
       "6814                               Manufacturing      Peoria, IL  11500.0   \n",
       "7365                               Manufacturing    Torrance, CA   6759.0   \n",
       "7497                               Manufacturing     Seattle, WA   7000.0   \n",
       "7522  Mining, Quarrying and Oil & Gas Extraction  Birmingham, AL   1200.0   \n",
       "7524                               Manufacturing        Eden, NC   1500.0   \n",
       "\n",
       "     Start Date End Date  Duration  start_year  end_year State  num_years  \n",
       "6814    6/21/94  12/4/95       NaN        1994    1995.0    IL        2.0  \n",
       "7365     3/2/93   3/3/93       NaN        1993    1993.0    CA        1.0  \n",
       "7497    1/21/93  1/22/93       NaN        1993    1993.0    WA        1.0  \n",
       "7522    7/14/93  7/16/93       NaN        1993    1993.0    AL        1.0  \n",
       "7524    5/17/93  5/19/93       NaN        1993    1993.0    NC        1.0  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "FMCS_df['num_years'] = FMCS_df[\"end_year\"] - FMCS_df[\"start_year\"] + 1\n",
    "FMCS_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "33061ec5-35df-4f31-94e6-36a4970de890",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>6814</th>\n",
       "      <td>Caterpillar Inc</td>\n",
       "      <td>UAW MULTI</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1991JU003706</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>Manufacturing</td>\n",
       "      <td>Peoria, IL</td>\n",
       "      <td>11500.0</td>\n",
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       "      <td>NaN</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>7365</th>\n",
       "      <td>Douglas Aircraft Company (two Locations)</td>\n",
       "      <td>IAM 720</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1992KR003410</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Manufacturing</td>\n",
       "      <td>Torrance, CA</td>\n",
       "      <td>6759.0</td>\n",
       "      <td>3/2/93</td>\n",
       "      <td>3/3/93</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1993.0</td>\n",
       "      <td>1993.0</td>\n",
       "      <td>CA</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7497</th>\n",
       "      <td>Boeing Company The</td>\n",
       "      <td>SPEEA</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1993BP000528</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Manufacturing</td>\n",
       "      <td>Seattle, WA</td>\n",
       "      <td>7000.0</td>\n",
       "      <td>1/21/93</td>\n",
       "      <td>1/22/93</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1993.0</td>\n",
       "      <td>1993.0</td>\n",
       "      <td>WA</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7522</th>\n",
       "      <td>Independent Bituminous Coal Bargaining Allianc...</td>\n",
       "      <td>UMW</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1993CN000462</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Mining, Quarrying and Oil &amp; Gas Extraction</td>\n",
       "      <td>Birmingham, AL</td>\n",
       "      <td>1200.0</td>\n",
       "      <td>7/14/93</td>\n",
       "      <td>7/16/93</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1993.0</td>\n",
       "      <td>1993.0</td>\n",
       "      <td>AL</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7524</th>\n",
       "      <td>Fieldcrest Cannon Inc (section 28)</td>\n",
       "      <td>ACTWU BI COUNTY N NC &amp; S GA DIST</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1993CN000511</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Manufacturing</td>\n",
       "      <td>Eden, NC</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>5/17/93</td>\n",
       "      <td>5/19/93</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1993.0</td>\n",
       "      <td>1993.0</td>\n",
       "      <td>NC</td>\n",
       "      <td>1.0</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14338</th>\n",
       "      <td>Charter/Spectrum</td>\n",
       "      <td>IBEW 3</td>\n",
       "      <td>3</td>\n",
       "      <td>2.01709E+11</td>\n",
       "      <td>1800.0</td>\n",
       "      <td>54.0</td>\n",
       "      <td>Professional, Scientific &amp;Tech Serv</td>\n",
       "      <td>New York, NJ</td>\n",
       "      <td>1800.0</td>\n",
       "      <td>3/29/17</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1130.0</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>NJ</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14339</th>\n",
       "      <td>Charter/Spectrum</td>\n",
       "      <td>IBEW 3</td>\n",
       "      <td>3</td>\n",
       "      <td>2.01709E+11</td>\n",
       "      <td>1800.0</td>\n",
       "      <td>54.0</td>\n",
       "      <td>Professional, Scientific &amp;Tech Serv</td>\n",
       "      <td>New York, NJ</td>\n",
       "      <td>1800.0</td>\n",
       "      <td>3/29/17</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1130.0</td>\n",
       "      <td>2019.0</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>NJ</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14340</th>\n",
       "      <td>Charter/Spectrum</td>\n",
       "      <td>IBEW 3</td>\n",
       "      <td>3</td>\n",
       "      <td>2.01709E+11</td>\n",
       "      <td>1800.0</td>\n",
       "      <td>54.0</td>\n",
       "      <td>Professional, Scientific &amp;Tech Serv</td>\n",
       "      <td>New York, NJ</td>\n",
       "      <td>1800.0</td>\n",
       "      <td>3/29/17</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1130.0</td>\n",
       "      <td>2018.0</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>NJ</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14341</th>\n",
       "      <td>National Grid</td>\n",
       "      <td>USW 12003</td>\n",
       "      <td>12003</td>\n",
       "      <td>2018N1001656</td>\n",
       "      <td>875.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>Utilities</td>\n",
       "      <td>Waltham, MA</td>\n",
       "      <td>1200.0</td>\n",
       "      <td>6/25/18</td>\n",
       "      <td>1/7/19</td>\n",
       "      <td>197.0</td>\n",
       "      <td>2019.0</td>\n",
       "      <td>2019.0</td>\n",
       "      <td>MA</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14342</th>\n",
       "      <td>ASARCO Multiple Unions</td>\n",
       "      <td>USW IBB IAM IUOE IBEW IBT</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0209E+11</td>\n",
       "      <td>2108.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>Mining and Oil &amp; Gas Extraction</td>\n",
       "      <td>Tucson, AZ</td>\n",
       "      <td>2108.0</td>\n",
       "      <td>10/14/19</td>\n",
       "      <td>NaN</td>\n",
       "      <td>262.0</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>AZ</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>524 rows × 16 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                Employer  \\\n",
       "6814                                     Caterpillar Inc   \n",
       "7365            Douglas Aircraft Company (two Locations)   \n",
       "7497                                  Boeing Company The   \n",
       "7522   Independent Bituminous Coal Bargaining Allianc...   \n",
       "7524                  Fieldcrest Cannon Inc (section 28)   \n",
       "...                                                  ...   \n",
       "14338                                   Charter/Spectrum   \n",
       "14339                                   Charter/Spectrum   \n",
       "14340                                   Charter/Spectrum   \n",
       "14341                                      National Grid   \n",
       "14342                             ASARCO Multiple Unions   \n",
       "\n",
       "                                  Union Union Local   Case Number      BU  \\\n",
       "6814                          UAW MULTI         NaN  1991JU003706     NaN   \n",
       "7365                            IAM 720         NaN  1992KR003410     NaN   \n",
       "7497                              SPEEA         NaN  1993BP000528     NaN   \n",
       "7522                                UMW         NaN  1993CN000462     NaN   \n",
       "7524   ACTWU BI COUNTY N NC & S GA DIST         NaN  1993CN000511     NaN   \n",
       "...                                 ...         ...           ...     ...   \n",
       "14338                            IBEW 3           3   2.01709E+11  1800.0   \n",
       "14339                            IBEW 3           3   2.01709E+11  1800.0   \n",
       "14340                            IBEW 3           3   2.01709E+11  1800.0   \n",
       "14341                         USW 12003       12003  2018N1001656   875.0   \n",
       "14342         USW IBB IAM IUOE IBEW IBT         NaN    2.0209E+11  2108.0   \n",
       "\n",
       "       NAICS                                    Industry     City, State  \\\n",
       "6814     NaN                               Manufacturing      Peoria, IL   \n",
       "7365     NaN                               Manufacturing    Torrance, CA   \n",
       "7497     NaN                               Manufacturing     Seattle, WA   \n",
       "7522     NaN  Mining, Quarrying and Oil & Gas Extraction  Birmingham, AL   \n",
       "7524     NaN                               Manufacturing        Eden, NC   \n",
       "...      ...                                         ...             ...   \n",
       "14338   54.0         Professional, Scientific &Tech Serv    New York, NJ   \n",
       "14339   54.0         Professional, Scientific &Tech Serv    New York, NJ   \n",
       "14340   54.0         Professional, Scientific &Tech Serv    New York, NJ   \n",
       "14341   22.0                                   Utilities     Waltham, MA   \n",
       "14342   21.0             Mining and Oil & Gas Extraction      Tucson, AZ   \n",
       "\n",
       "       # Idled Start Date End Date  Duration  start_year  end_year State  \\\n",
       "6814   11500.0    6/21/94  12/4/95       NaN      1994.0    1995.0    IL   \n",
       "7365    6759.0     3/2/93   3/3/93       NaN      1993.0    1993.0    CA   \n",
       "7497    7000.0    1/21/93  1/22/93       NaN      1993.0    1993.0    WA   \n",
       "7522    1200.0    7/14/93  7/16/93       NaN      1993.0    1993.0    AL   \n",
       "7524    1500.0    5/17/93  5/19/93       NaN      1993.0    1993.0    NC   \n",
       "...        ...        ...      ...       ...         ...       ...   ...   \n",
       "14338   1800.0    3/29/17      NaN    1130.0      2020.0    2020.0    NJ   \n",
       "14339   1800.0    3/29/17      NaN    1130.0      2019.0    2020.0    NJ   \n",
       "14340   1800.0    3/29/17      NaN    1130.0      2018.0    2020.0    NJ   \n",
       "14341   1200.0    6/25/18   1/7/19     197.0      2019.0    2019.0    MA   \n",
       "14342   2108.0   10/14/19      NaN     262.0      2020.0    2020.0    AZ   \n",
       "\n",
       "       num_years  \n",
       "6814         2.0  \n",
       "7365         1.0  \n",
       "7497         1.0  \n",
       "7522         1.0  \n",
       "7524         1.0  \n",
       "...          ...  \n",
       "14338        4.0  \n",
       "14339        4.0  \n",
       "14340        4.0  \n",
       "14341        2.0  \n",
       "14342        2.0  \n",
       "\n",
       "[524 rows x 16 columns]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "testing_df = FMCS_df.copy()\n",
    "for index, row in testing_df.iterrows():\n",
    "    if row['num_years'] > 1:\n",
    "        i = row['num_years']-1\n",
    "        start_year = row['start_year']\n",
    "        while i != 0:\n",
    "            row_2 = row\n",
    "            row_2['start_year'] = start_year + i\n",
    "            testing_df.loc[testing_df.index.max()+1, :] = row_2\n",
    "            i = i - 1\n",
    "FMCS_df = testing_df\n",
    "FMCS_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "568956fd-fd52-4835-8431-6da40c37b3cd",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Employer</th>\n",
       "      <th>Union</th>\n",
       "      <th>Union Local</th>\n",
       "      <th>Case Number</th>\n",
       "      <th>BU</th>\n",
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       "      <th>num_years</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>6814</th>\n",
       "      <td>Caterpillar Inc</td>\n",
       "      <td>UAW MULTI</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1991JU003706</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Manufacturing</td>\n",
       "      <td>Peoria, IL</td>\n",
       "      <td>11500.0</td>\n",
       "      <td>6/21/94</td>\n",
       "      <td>12/4/95</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1994.0</td>\n",
       "      <td>1995.0</td>\n",
       "      <td>IL</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7365</th>\n",
       "      <td>Douglas Aircraft Company (two Locations)</td>\n",
       "      <td>IAM 720</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1992KR003410</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Manufacturing</td>\n",
       "      <td>Torrance, CA</td>\n",
       "      <td>6759.0</td>\n",
       "      <td>3/2/93</td>\n",
       "      <td>3/3/93</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1993.0</td>\n",
       "      <td>1993.0</td>\n",
       "      <td>CA</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7497</th>\n",
       "      <td>Boeing Company The</td>\n",
       "      <td>SPEEA</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1993BP000528</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Manufacturing</td>\n",
       "      <td>Seattle, WA</td>\n",
       "      <td>7000.0</td>\n",
       "      <td>1/21/93</td>\n",
       "      <td>1/22/93</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1993.0</td>\n",
       "      <td>1993.0</td>\n",
       "      <td>WA</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7522</th>\n",
       "      <td>Independent Bituminous Coal Bargaining Allianc...</td>\n",
       "      <td>UMW</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1993CN000462</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Mining, Quarrying and Oil &amp; Gas Extraction</td>\n",
       "      <td>Birmingham, AL</td>\n",
       "      <td>1200.0</td>\n",
       "      <td>7/14/93</td>\n",
       "      <td>7/16/93</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1993.0</td>\n",
       "      <td>1993.0</td>\n",
       "      <td>AL</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7524</th>\n",
       "      <td>Fieldcrest Cannon Inc (section 28)</td>\n",
       "      <td>ACTWU BI COUNTY N NC &amp; S GA DIST</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1993CN000511</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Manufacturing</td>\n",
       "      <td>Eden, NC</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>5/17/93</td>\n",
       "      <td>5/19/93</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1993.0</td>\n",
       "      <td>1993.0</td>\n",
       "      <td>NC</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                               Employer  \\\n",
       "6814                                    Caterpillar Inc   \n",
       "7365           Douglas Aircraft Company (two Locations)   \n",
       "7497                                 Boeing Company The   \n",
       "7522  Independent Bituminous Coal Bargaining Allianc...   \n",
       "7524                 Fieldcrest Cannon Inc (section 28)   \n",
       "\n",
       "                                 Union Union Local   Case Number  BU  NAICS  \\\n",
       "6814                         UAW MULTI         NaN  1991JU003706 NaN    NaN   \n",
       "7365                           IAM 720         NaN  1992KR003410 NaN    NaN   \n",
       "7497                             SPEEA         NaN  1993BP000528 NaN    NaN   \n",
       "7522                               UMW         NaN  1993CN000462 NaN    NaN   \n",
       "7524  ACTWU BI COUNTY N NC & S GA DIST         NaN  1993CN000511 NaN    NaN   \n",
       "\n",
       "                                        Industry     City, State  # Idled  \\\n",
       "6814                               Manufacturing      Peoria, IL  11500.0   \n",
       "7365                               Manufacturing    Torrance, CA   6759.0   \n",
       "7497                               Manufacturing     Seattle, WA   7000.0   \n",
       "7522  Mining, Quarrying and Oil & Gas Extraction  Birmingham, AL   1200.0   \n",
       "7524                               Manufacturing        Eden, NC   1500.0   \n",
       "\n",
       "     Start Date End Date  Duration  start_year  end_year State  num_years  \n",
       "6814    6/21/94  12/4/95       NaN      1994.0    1995.0    IL        2.0  \n",
       "7365     3/2/93   3/3/93       NaN      1993.0    1993.0    CA        1.0  \n",
       "7497    1/21/93  1/22/93       NaN      1993.0    1993.0    WA        1.0  \n",
       "7522    7/14/93  7/16/93       NaN      1993.0    1993.0    AL        1.0  \n",
       "7524    5/17/93  5/19/93       NaN      1993.0    1993.0    NC        1.0  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "FMCS_df = FMCS_df[~FMCS_df.duplicated(['Employer','# Idled','start_year'])]\n",
    "FMCS_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "4970b30f-11f4-48e3-95b9-ba7c4004153f",
   "metadata": {},
   "outputs": [],
   "source": [
    "FMCS_df.to_csv('FMCS_testing.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "ddda103f-1314-4861-89e2-83990a5d8681",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Caterpillar Inc</td>\n",
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       "      <th>1</th>\n",
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       "      <td>NaN</td>\n",
       "      <td>Manufacturing</td>\n",
       "      <td>Torrance, CA</td>\n",
       "      <td>6800</td>\n",
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       "      <td>3/3/93</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1993</td>\n",
       "      <td>1993</td>\n",
       "      <td>CA</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Boeing Company The</td>\n",
       "      <td>SPEEA</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1993BP000528</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Manufacturing</td>\n",
       "      <td>Seattle, WA</td>\n",
       "      <td>21000</td>\n",
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       "      <td>1/22/93</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1993</td>\n",
       "      <td>1993</td>\n",
       "      <td>WA</td>\n",
       "      <td>1</td>\n",
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       "      <th>3</th>\n",
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       "      <td>1993CN000462</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Mining, Quarrying and Oil &amp; Gas Extraction</td>\n",
       "      <td>Birmingham, AL</td>\n",
       "      <td>6700</td>\n",
       "      <td>7/14/93</td>\n",
       "      <td>7/16/93</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1993</td>\n",
       "      <td>1993</td>\n",
       "      <td>AL</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Fieldcrest Cannon Inc (section 28)</td>\n",
       "      <td>ACTWU BI COUNTY N NC &amp; S GA DIST</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1993CN000511</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Manufacturing</td>\n",
       "      <td>Eden, NC</td>\n",
       "      <td>2000</td>\n",
       "      <td>5/17/93</td>\n",
       "      <td>5/19/93</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1993</td>\n",
       "      <td>1993</td>\n",
       "      <td>NC</td>\n",
       "      <td>1</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>371</th>\n",
       "      <td>FairPoint Communications - Yelm</td>\n",
       "      <td>IBEW Local SCT-9</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2014N0502678</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Utilities</td>\n",
       "      <td>Various - ME, NH, VT, NH</td>\n",
       "      <td>1700</td>\n",
       "      <td>10/17/14</td>\n",
       "      <td>2/24/15</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015</td>\n",
       "      <td>2015</td>\n",
       "      <td>NH</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>372</th>\n",
       "      <td>Charter/Spectrum</td>\n",
       "      <td>IBEW 3</td>\n",
       "      <td>3</td>\n",
       "      <td>2.02E+11</td>\n",
       "      <td>1800.0</td>\n",
       "      <td>54.0</td>\n",
       "      <td>Professional, Scientific &amp;Tech Serv</td>\n",
       "      <td>New York, NJ</td>\n",
       "      <td>1800</td>\n",
       "      <td>3/29/17</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1130.0</td>\n",
       "      <td>2020</td>\n",
       "      <td>2020</td>\n",
       "      <td>NJ</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>373</th>\n",
       "      <td>Charter/Spectrum</td>\n",
       "      <td>IBEW 3</td>\n",
       "      <td>3</td>\n",
       "      <td>2.02E+11</td>\n",
       "      <td>1800.0</td>\n",
       "      <td>54.0</td>\n",
       "      <td>Professional, Scientific &amp;Tech Serv</td>\n",
       "      <td>New York, NJ</td>\n",
       "      <td>1800</td>\n",
       "      <td>3/29/17</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1130.0</td>\n",
       "      <td>2019</td>\n",
       "      <td>2020</td>\n",
       "      <td>NJ</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>374</th>\n",
       "      <td>Charter/Spectrum</td>\n",
       "      <td>IBEW 3</td>\n",
       "      <td>3</td>\n",
       "      <td>2.02E+11</td>\n",
       "      <td>1800.0</td>\n",
       "      <td>54.0</td>\n",
       "      <td>Professional, Scientific &amp;Tech Serv</td>\n",
       "      <td>New York, NJ</td>\n",
       "      <td>1800</td>\n",
       "      <td>3/29/17</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1130.0</td>\n",
       "      <td>2018</td>\n",
       "      <td>2020</td>\n",
       "      <td>NJ</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>375</th>\n",
       "      <td>National Grid</td>\n",
       "      <td>USW 12003</td>\n",
       "      <td>12003</td>\n",
       "      <td>2018N1001656</td>\n",
       "      <td>875.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>Utilities</td>\n",
       "      <td>Waltham, MA</td>\n",
       "      <td>1200</td>\n",
       "      <td>6/25/18</td>\n",
       "      <td>1/7/19</td>\n",
       "      <td>197.0</td>\n",
       "      <td>2019</td>\n",
       "      <td>2019</td>\n",
       "      <td>MA</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>376 rows × 16 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                              Employer  \\\n",
       "0                                      Caterpillar Inc   \n",
       "1             Douglas Aircraft Company (two Locations)   \n",
       "2                                   Boeing Company The   \n",
       "3    Independent Bituminous Coal Bargaining Allianc...   \n",
       "4                   Fieldcrest Cannon Inc (section 28)   \n",
       "..                                                 ...   \n",
       "371                    FairPoint Communications - Yelm   \n",
       "372                                   Charter/Spectrum   \n",
       "373                                   Charter/Spectrum   \n",
       "374                                   Charter/Spectrum   \n",
       "375                                      National Grid   \n",
       "\n",
       "                                Union Union Local   Case Number      BU  \\\n",
       "0                           UAW MULTI         NaN  1991JU003706     NaN   \n",
       "1                             IAM 720         NaN  1992KR003410     NaN   \n",
       "2                               SPEEA         NaN  1993BP000528     NaN   \n",
       "3                                 UMW         NaN  1993CN000462     NaN   \n",
       "4    ACTWU BI COUNTY N NC & S GA DIST         NaN  1993CN000511     NaN   \n",
       "..                                ...         ...           ...     ...   \n",
       "371                  IBEW Local SCT-9         NaN  2014N0502678     NaN   \n",
       "372                            IBEW 3           3      2.02E+11  1800.0   \n",
       "373                            IBEW 3           3      2.02E+11  1800.0   \n",
       "374                            IBEW 3           3      2.02E+11  1800.0   \n",
       "375                         USW 12003       12003  2018N1001656   875.0   \n",
       "\n",
       "     NAICS                                    Industry  \\\n",
       "0      NaN                               Manufacturing   \n",
       "1      NaN                               Manufacturing   \n",
       "2      NaN                               Manufacturing   \n",
       "3      NaN  Mining, Quarrying and Oil & Gas Extraction   \n",
       "4      NaN                               Manufacturing   \n",
       "..     ...                                         ...   \n",
       "371    NaN                                   Utilities   \n",
       "372   54.0         Professional, Scientific &Tech Serv   \n",
       "373   54.0         Professional, Scientific &Tech Serv   \n",
       "374   54.0         Professional, Scientific &Tech Serv   \n",
       "375   22.0                                   Utilities   \n",
       "\n",
       "                  City, State  # Idled Start Date End Date  Duration  \\\n",
       "0                  Peoria, IL    14000    6/21/94  12/4/95       NaN   \n",
       "1                Torrance, CA     6800     3/2/93   3/3/93       NaN   \n",
       "2                 Seattle, WA    21000    1/21/93  1/22/93       NaN   \n",
       "3              Birmingham, AL     6700    7/14/93  7/16/93       NaN   \n",
       "4                    Eden, NC     2000    5/17/93  5/19/93       NaN   \n",
       "..                        ...      ...        ...      ...       ...   \n",
       "371  Various - ME, NH, VT, NH     1700   10/17/14  2/24/15       NaN   \n",
       "372              New York, NJ     1800    3/29/17      NaN    1130.0   \n",
       "373              New York, NJ     1800    3/29/17      NaN    1130.0   \n",
       "374              New York, NJ     1800    3/29/17      NaN    1130.0   \n",
       "375               Waltham, MA     1200    6/25/18   1/7/19     197.0   \n",
       "\n",
       "     start_year  end_year State  num_years  \n",
       "0          1994      1995    IL          2  \n",
       "1          1993      1993    CA          1  \n",
       "2          1993      1993    WA          1  \n",
       "3          1993      1993    AL          1  \n",
       "4          1993      1993    NC          1  \n",
       "..          ...       ...   ...        ...  \n",
       "371        2015      2015    NH          2  \n",
       "372        2020      2020    NJ          4  \n",
       "373        2019      2020    NJ          4  \n",
       "374        2018      2020    NJ          4  \n",
       "375        2019      2019    MA          2  \n",
       "\n",
       "[376 rows x 16 columns]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "FMCS_df = pd.read_csv('FMCS_testing_2.csv')\n",
    "FMCS_df = FMCS_df.iloc[:,1:]\n",
    "FMCS_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "8eed4fcd-19d9-4e13-b43e-6d9483be1fad",
   "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",
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       "    }\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>State</th>\n",
       "      <th>start_year</th>\n",
       "      <th># Idled</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>AK</td>\n",
       "      <td>1999</td>\n",
       "      <td>1000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>AL</td>\n",
       "      <td>1993</td>\n",
       "      <td>6700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>AL</td>\n",
       "      <td>1994</td>\n",
       "      <td>2000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>AL</td>\n",
       "      <td>1996</td>\n",
       "      <td>1100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>AL</td>\n",
       "      <td>1997</td>\n",
       "      <td>1000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  State  start_year  # Idled\n",
       "0    AK        1999     1000\n",
       "1    AL        1993     6700\n",
       "2    AL        1994     2000\n",
       "3    AL        1996     1100\n",
       "4    AL        1997     1000"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "grouped_fmcs_df = FMCS_df.groupby([\"State\",\"start_year\"])[\"# Idled\"].sum().reset_index()\n",
    "grouped_fmcs_df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "87c9b962-6c60-4807-891a-9844829090dd",
   "metadata": {},
   "source": [
    "## Union Member Dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "f0ec53cd-d266-4c60-b773-10f06ec20788",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Alabama', 'Alaska', 'Arizona', 'Arkansas', 'California',\n",
       "       'Colorado', 'Connecticut', 'Delaware', 'District of Columbia',\n",
       "       'Florida', 'Georgia', 'Hawaii', 'Idaho', 'Illinois', 'Indiana',\n",
       "       'Iowa', 'Kansas', 'Kentucky', 'Louisiana', 'Maine', 'Maryland',\n",
       "       'Massachusetts', 'Michigan', 'Minnesota', 'Mississippi',\n",
       "       'Missouri', 'Montana', 'Nebraska', 'Nevada', 'New Hampshire',\n",
       "       'New Jersey', 'New Mexico', 'New York', 'North Carolina',\n",
       "       'North Dakota', 'Ohio', 'Oklahoma', 'Oregon', 'Pennsylvania',\n",
       "       'Rhode Island', 'South Carolina', 'South Dakota', 'Tennessee',\n",
       "       'Texas', 'Utah', 'Vermont', 'Virginia', 'Washington',\n",
       "       'West Virginia', 'Wisconsin', 'Wyoming'], dtype=object)"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "union_df = pd.read_csv(\"union_membership.csv\")\n",
    "union_df['State'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "2f86890b-c10d-43ac-ae72-409dbe8ced8a",
   "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>Year</th>\n",
       "      <th>State</th>\n",
       "      <th>% Mem</th>\n",
       "      <th>Employment (in 1000s)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1993</td>\n",
       "      <td>AL</td>\n",
       "      <td>12.0%</td>\n",
       "      <td>1,381</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>1993</td>\n",
       "      <td>AK</td>\n",
       "      <td>10.3%</td>\n",
       "      <td>165</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>1993</td>\n",
       "      <td>AZ</td>\n",
       "      <td>5.2%</td>\n",
       "      <td>1,212</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>1993</td>\n",
       "      <td>AR</td>\n",
       "      <td>7.5%</td>\n",
       "      <td>778</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>1993</td>\n",
       "      <td>CA</td>\n",
       "      <td>11.6%</td>\n",
       "      <td>9,967</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Year State  % Mem Employment (in 1000s)\n",
       "2   1993    AL  12.0%                 1,381\n",
       "7   1993    AK  10.3%                   165\n",
       "12  1993    AZ   5.2%                 1,212\n",
       "17  1993    AR   7.5%                   778\n",
       "22  1993    CA  11.6%                 9,967"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "us_state_to_abbrev_union = {\"State\" : {\n",
    "    \"Alabama\": \"AL\",\n",
    "    \"Alaska\": \"AK\",\n",
    "    \"Arizona\": \"AZ\",\n",
    "    \"Arkansas\": \"AR\",\n",
    "    \"California\": \"CA\",\n",
    "    \"Colorado\": \"CO\",\n",
    "    \"Connecticut\": \"CT\",\n",
    "    \"Delaware\": \"DE\",\n",
    "    \"Florida\": \"FL\",\n",
    "    \"Georgia\": \"GA\",\n",
    "    \"Hawaii\": \"HI\",\n",
    "    \"Idaho\": \"ID\",\n",
    "    \"Illinois\": \"IL\",\n",
    "    \"Indiana\": \"IN\",\n",
    "    \"Iowa\": \"IA\",\n",
    "    \"Kansas\": \"KS\",\n",
    "    \"Kentucky\": \"KY\",\n",
    "    \"Louisiana\": \"LA\",\n",
    "    \"Maine\": \"ME\",\n",
    "    \"Maryland\": \"MD\",\n",
    "    \"Massachusetts\": \"MA\",\n",
    "    \"Michigan\": \"MI\",\n",
    "    \"Minnesota\": \"MN\",\n",
    "    \"Mississippi\": \"MS\",\n",
    "    \"Missouri\": \"MO\",\n",
    "    \"Montana\": \"MT\",\n",
    "    \"Nebraska\": \"NE\",\n",
    "    \"Nevada\": \"NV\",\n",
    "    \"New Hampshire\": \"NH\",\n",
    "    \"New Jersey\": \"NJ\",\n",
    "    \"New Mexico\": \"NM\",\n",
    "    \"New York\": \"NY\",\n",
    "    \"North Carolina\": \"NC\",\n",
    "    \"North Dakota\": \"ND\",\n",
    "    \"Ohio\": \"OH\",\n",
    "    \"Oklahoma\": \"OK\",\n",
    "    \"Oregon\": \"OR\",\n",
    "    \"Pennsylvania\": \"PA\",\n",
    "    \"Rhode Island\": \"RI\",\n",
    "    \"South Carolina\": \"SC\",\n",
    "    \"South Dakota\": \"SD\",\n",
    "    \"Tennessee\": \"TN\",\n",
    "    \"Texas\": \"TX\",\n",
    "    \"Utah\": \"UT\",\n",
    "    \"Vermont\": \"VT\",\n",
    "    \"Virginia\": \"VA\",\n",
    "    \"Washington\": \"WA\",\n",
    "    \"West Virginia\": \"WV\",\n",
    "    \"Wisconsin\": \"WI\",\n",
    "    \"Wyoming\": \"WY\",\n",
    "    \"District of Columbia\": \"DC\",\n",
    "    \"American Samoa\": \"AS\",\n",
    "    \"Guam\": \"GU\",\n",
    "    \"Northern Mariana Islands\": \"MP\",\n",
    "    \"Puerto Rico\": \"PR\",\n",
    "    \"United States Minor Outlying Islands\": \"UM\",\n",
    "    \"U.S. Virgin Islands\": \"VI\",\n",
    "}}\n",
    "union_df = union_df.replace(us_state_to_abbrev_union)\n",
    "union_df_priv = union_df[union_df['Sector'] == 'Private'][[\"Year\",\"State\",\"% Mem\",'Employment (in 1000s)']]\n",
    "union_df_priv.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dbeea152-f6b7-4d9a-9267-d2e27417d11e",
   "metadata": {},
   "source": [
    "## Political Lean Dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "2880d3a5-a710-48c8-8a56-44b820251ea8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
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       "    }\n",
       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>year</th>\n",
       "      <th>state</th>\n",
       "      <th>state_po</th>\n",
       "      <th>state_fips</th>\n",
       "      <th>state_cen</th>\n",
       "      <th>state_ic</th>\n",
       "      <th>office</th>\n",
       "      <th>district</th>\n",
       "      <th>stage</th>\n",
       "      <th>runoff</th>\n",
       "      <th>special</th>\n",
       "      <th>candidate</th>\n",
       "      <th>party</th>\n",
       "      <th>writein</th>\n",
       "      <th>mode</th>\n",
       "      <th>candidatevotes</th>\n",
       "      <th>totalvotes</th>\n",
       "      <th>unofficial</th>\n",
       "      <th>version</th>\n",
       "      <th>fusion_ticket</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>11083</th>\n",
       "      <td>1994</td>\n",
       "      <td>ALABAMA</td>\n",
       "      <td>AL</td>\n",
       "      <td>1</td>\n",
       "      <td>63</td>\n",
       "      <td>41</td>\n",
       "      <td>US HOUSE</td>\n",
       "      <td>1</td>\n",
       "      <td>GEN</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>DON WOMACK</td>\n",
       "      <td>DEMOCRAT</td>\n",
       "      <td>False</td>\n",
       "      <td>TOTAL</td>\n",
       "      <td>50227</td>\n",
       "      <td>153767</td>\n",
       "      <td>False</td>\n",
       "      <td>20220331</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11084</th>\n",
       "      <td>1994</td>\n",
       "      <td>ALABAMA</td>\n",
       "      <td>AL</td>\n",
       "      <td>1</td>\n",
       "      <td>63</td>\n",
       "      <td>41</td>\n",
       "      <td>US HOUSE</td>\n",
       "      <td>1</td>\n",
       "      <td>GEN</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>SONNY CALLAHAN</td>\n",
       "      <td>REPUBLICAN</td>\n",
       "      <td>False</td>\n",
       "      <td>TOTAL</td>\n",
       "      <td>103431</td>\n",
       "      <td>153767</td>\n",
       "      <td>False</td>\n",
       "      <td>20220331</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11085</th>\n",
       "      <td>1994</td>\n",
       "      <td>ALABAMA</td>\n",
       "      <td>AL</td>\n",
       "      <td>1</td>\n",
       "      <td>63</td>\n",
       "      <td>41</td>\n",
       "      <td>US HOUSE</td>\n",
       "      <td>1</td>\n",
       "      <td>GEN</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>WRITEIN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>True</td>\n",
       "      <td>TOTAL</td>\n",
       "      <td>109</td>\n",
       "      <td>153767</td>\n",
       "      <td>False</td>\n",
       "      <td>20220331</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11086</th>\n",
       "      <td>1994</td>\n",
       "      <td>ALABAMA</td>\n",
       "      <td>AL</td>\n",
       "      <td>1</td>\n",
       "      <td>63</td>\n",
       "      <td>41</td>\n",
       "      <td>US HOUSE</td>\n",
       "      <td>2</td>\n",
       "      <td>GEN</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>BRIAN DOWLING</td>\n",
       "      <td>DEMOCRAT</td>\n",
       "      <td>False</td>\n",
       "      <td>TOTAL</td>\n",
       "      <td>44694</td>\n",
       "      <td>169213</td>\n",
       "      <td>False</td>\n",
       "      <td>20220331</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11087</th>\n",
       "      <td>1994</td>\n",
       "      <td>ALABAMA</td>\n",
       "      <td>AL</td>\n",
       "      <td>1</td>\n",
       "      <td>63</td>\n",
       "      <td>41</td>\n",
       "      <td>US HOUSE</td>\n",
       "      <td>2</td>\n",
       "      <td>GEN</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>TERRY EVERETT</td>\n",
       "      <td>REPUBLICAN</td>\n",
       "      <td>False</td>\n",
       "      <td>TOTAL</td>\n",
       "      <td>124465</td>\n",
       "      <td>169213</td>\n",
       "      <td>False</td>\n",
       "      <td>20220331</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       year    state state_po  state_fips  state_cen  state_ic    office  \\\n",
       "11083  1994  ALABAMA       AL           1         63        41  US HOUSE   \n",
       "11084  1994  ALABAMA       AL           1         63        41  US HOUSE   \n",
       "11085  1994  ALABAMA       AL           1         63        41  US HOUSE   \n",
       "11086  1994  ALABAMA       AL           1         63        41  US HOUSE   \n",
       "11087  1994  ALABAMA       AL           1         63        41  US HOUSE   \n",
       "\n",
       "       district stage runoff  special       candidate       party  writein  \\\n",
       "11083         1   GEN  False    False      DON WOMACK    DEMOCRAT    False   \n",
       "11084         1   GEN  False    False  SONNY CALLAHAN  REPUBLICAN    False   \n",
       "11085         1   GEN  False    False         WRITEIN         NaN     True   \n",
       "11086         2   GEN  False    False   BRIAN DOWLING    DEMOCRAT    False   \n",
       "11087         2   GEN  False    False   TERRY EVERETT  REPUBLICAN    False   \n",
       "\n",
       "        mode  candidatevotes  totalvotes  unofficial   version  fusion_ticket  \n",
       "11083  TOTAL           50227      153767       False  20220331          False  \n",
       "11084  TOTAL          103431      153767       False  20220331          False  \n",
       "11085  TOTAL             109      153767       False  20220331          False  \n",
       "11086  TOTAL           44694      169213       False  20220331          False  \n",
       "11087  TOTAL          124465      169213       False  20220331          False  "
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "poli_df = pd.read_csv(\"1976-2020-house.csv\")\n",
    "poli_df = poli_df[poli_df['year'] >= 1993]\n",
    "poli_df = poli_df[~poli_df['state_po'].isin(['DC'])]\n",
    "poli_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "ae083bd3-2fca-4cc9-a995-16e1e8ea94c7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(               candidatevotes\n",
       " state_po year                \n",
       " AK       1994          118537\n",
       "          1996          138834\n",
       "          1998          139676\n",
       "          2000          190862\n",
       "          2002          169685,\n",
       "                totalvotes\n",
       " state_po year            \n",
       " AK       1994      208240\n",
       "          1996      233700\n",
       "          1998      223300\n",
       "          2000      274393\n",
       "          2002      227725)"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "votes_by_party = poli_df.groupby(['state_po','year','party'])['candidatevotes'].sum().reset_index()\n",
    "votes_by_party = votes_by_party[votes_by_party['party'] == 'REPUBLICAN']\n",
    "votes_by_party = votes_by_party.set_index(['state_po','year']).drop(columns=['party'])\n",
    "total_votes = poli_df.groupby(['state_po','year','district'])['totalvotes'].first().reset_index()\n",
    "total_votes = total_votes.groupby(['state_po','year'])['totalvotes'].sum().reset_index()\n",
    "total_votes = total_votes.set_index(['state_po','year'])\n",
    "votes_by_party.head(), total_votes.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "329cf2ed-613e-49dd-a860-58da1fbe07de",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['INDEPENDENT', 'LIBERTY UNION', 'ENERGY INDEPENDENCE', 'DEMOCRAT',\n",
       "       'PROGRESSIVE', nan], dtype=object)"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "poli_df.loc[(poli_df['state_po'] == 'MN') & (poli_df['year'].isin([1992])) & (poli_df['party'].isin([\"INDEPENDENT-REPUBLICAN\"])),'party'] = \"REPUBLICAN\"\n",
    "poli_df.loc[(poli_df['state_po'] == 'HI') & (poli_df['year'].isin([1982])),:]['party'].unique()\n",
    "poli_df.loc[(poli_df['state_po'] == 'DC') & (poli_df['year'].isin([2020])),:]['party'].unique()\n",
    "poli_df.loc[(poli_df['state_po'] == 'VT') & (poli_df['year'].isin([2008,2016])),:]['party'].unique()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "11b146c6-7f96-46d2-981b-2bf6ee2cda03",
   "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></th>\n",
       "      <th>totalvotes</th>\n",
       "      <th>candidatevotes</th>\n",
       "      <th>prop_rep_votes</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>state_po</th>\n",
       "      <th>year</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">AK</th>\n",
       "      <th>1994</th>\n",
       "      <td>208240</td>\n",
       "      <td>118537.0</td>\n",
       "      <td>0.569233</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1996</th>\n",
       "      <td>233700</td>\n",
       "      <td>138834.0</td>\n",
       "      <td>0.594069</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1998</th>\n",
       "      <td>223300</td>\n",
       "      <td>139676.0</td>\n",
       "      <td>0.625508</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000</th>\n",
       "      <td>274393</td>\n",
       "      <td>190862.0</td>\n",
       "      <td>0.695579</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2002</th>\n",
       "      <td>227725</td>\n",
       "      <td>169685.0</td>\n",
       "      <td>0.745131</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">WY</th>\n",
       "      <th>2012</th>\n",
       "      <td>250700</td>\n",
       "      <td>166452.0</td>\n",
       "      <td>0.663949</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014</th>\n",
       "      <td>171153</td>\n",
       "      <td>113038.0</td>\n",
       "      <td>0.660450</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016</th>\n",
       "      <td>258788</td>\n",
       "      <td>156176.0</td>\n",
       "      <td>0.603490</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018</th>\n",
       "      <td>201245</td>\n",
       "      <td>127963.0</td>\n",
       "      <td>0.635857</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020</th>\n",
       "      <td>278503</td>\n",
       "      <td>185732.0</td>\n",
       "      <td>0.666894</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>700 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "               totalvotes  candidatevotes  prop_rep_votes\n",
       "state_po year                                            \n",
       "AK       1994      208240        118537.0        0.569233\n",
       "         1996      233700        138834.0        0.594069\n",
       "         1998      223300        139676.0        0.625508\n",
       "         2000      274393        190862.0        0.695579\n",
       "         2002      227725        169685.0        0.745131\n",
       "...                   ...             ...             ...\n",
       "WY       2012      250700        166452.0        0.663949\n",
       "         2014      171153        113038.0        0.660450\n",
       "         2016      258788        156176.0        0.603490\n",
       "         2018      201245        127963.0        0.635857\n",
       "         2020      278503        185732.0        0.666894\n",
       "\n",
       "[700 rows x 3 columns]"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "merged_poli_df = total_votes.merge(votes_by_party, left_index=True, right_index=True, how=\"left\")\n",
    "merged_poli_df['candidatevotes'] = merged_poli_df['candidatevotes'].fillna(0)\n",
    "merged_poli_df['prop_rep_votes'] = merged_poli_df['candidatevotes']/merged_poli_df['totalvotes']\n",
    "merged_poli_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "7828c32f-d152-46eb-a1d8-17139e82395e",
   "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>state_po</th>\n",
       "      <th>year</th>\n",
       "      <th>totalvotes</th>\n",
       "      <th>candidatevotes</th>\n",
       "      <th>prop_rep_votes</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>AK</td>\n",
       "      <td>1994.0</td>\n",
       "      <td>208240.0</td>\n",
       "      <td>118537.0</td>\n",
       "      <td>0.569233</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>AK</td>\n",
       "      <td>1996.0</td>\n",
       "      <td>233700.0</td>\n",
       "      <td>138834.0</td>\n",
       "      <td>0.594069</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>AK</td>\n",
       "      <td>1998.0</td>\n",
       "      <td>223300.0</td>\n",
       "      <td>139676.0</td>\n",
       "      <td>0.625508</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>AK</td>\n",
       "      <td>2000.0</td>\n",
       "      <td>274393.0</td>\n",
       "      <td>190862.0</td>\n",
       "      <td>0.695579</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>AK</td>\n",
       "      <td>2002.0</td>\n",
       "      <td>227725.0</td>\n",
       "      <td>169685.0</td>\n",
       "      <td>0.745131</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  state_po    year  totalvotes  candidatevotes  prop_rep_votes\n",
       "0       AK  1994.0    208240.0        118537.0        0.569233\n",
       "1       AK  1996.0    233700.0        138834.0        0.594069\n",
       "2       AK  1998.0    223300.0        139676.0        0.625508\n",
       "3       AK  2000.0    274393.0        190862.0        0.695579\n",
       "4       AK  2002.0    227725.0        169685.0        0.745131"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "full_poli_df = merged_poli_df.reset_index()\n",
    "for state in full_poli_df['state_po'].unique():\n",
    "    for year in np.arange(1995,2020,2):\n",
    "        try:\n",
    "            full_poli_df.loc[full_poli_df.index.max()+1,:] = full_poli_df.loc[\n",
    "                (full_poli_df['state_po'] == state) & (full_poli_df['year'] == year-1),:].iloc[0]\n",
    "            full_poli_df.loc[full_poli_df.index.max(),'year']=year\n",
    "        except:\n",
    "            print(state,year)\n",
    "full_poli_df.head()        \n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c300f593-984c-4b82-be6b-e731a6b2e2fb",
   "metadata": {},
   "source": [
    "## Minimum Wage Dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "b87256d9-f15d-4fc1-b4f7-e7b9f2790136",
   "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>Year</th>\n",
       "      <th>State</th>\n",
       "      <th>State.Minimum.Wage</th>\n",
       "      <th>State.Minimum.Wage.2020.Dollars</th>\n",
       "      <th>Federal.Minimum.Wage</th>\n",
       "      <th>Federal.Minimum.Wage.2020.Dollars</th>\n",
       "      <th>Effective.Minimum.Wage</th>\n",
       "      <th>Effective.Minimum.Wage.2020.Dollars</th>\n",
       "      <th>CPI.Average</th>\n",
       "      <th>Department.Of.Labor.Uncleaned.Data</th>\n",
       "      <th>Department.Of.Labor.Cleaned.Low.Value</th>\n",
       "      <th>Department.Of.Labor.Cleaned.Low.Value.2020.Dollars</th>\n",
       "      <th>Department.Of.Labor.Cleaned.High.Value</th>\n",
       "      <th>Department.Of.Labor.Cleaned.High.Value.2020.Dollars</th>\n",
       "      <th>Footnote</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1350</th>\n",
       "      <td>1993</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>4.25</td>\n",
       "      <td>7.61</td>\n",
       "      <td>4.25</td>\n",
       "      <td>7.61</td>\n",
       "      <td>144.50</td>\n",
       "      <td>...</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1351</th>\n",
       "      <td>1993</td>\n",
       "      <td>Alaska</td>\n",
       "      <td>4.75</td>\n",
       "      <td>8.50</td>\n",
       "      <td>4.25</td>\n",
       "      <td>7.61</td>\n",
       "      <td>4.75</td>\n",
       "      <td>8.50</td>\n",
       "      <td>144.50</td>\n",
       "      <td>4.75</td>\n",
       "      <td>4.75</td>\n",
       "      <td>8.50</td>\n",
       "      <td>4.75</td>\n",
       "      <td>8.50</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1352</th>\n",
       "      <td>1993</td>\n",
       "      <td>Arizona</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>4.25</td>\n",
       "      <td>7.61</td>\n",
       "      <td>4.25</td>\n",
       "      <td>7.61</td>\n",
       "      <td>144.50</td>\n",
       "      <td>...</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1353</th>\n",
       "      <td>1993</td>\n",
       "      <td>Arkansas</td>\n",
       "      <td>3.65</td>\n",
       "      <td>6.53</td>\n",
       "      <td>4.25</td>\n",
       "      <td>7.61</td>\n",
       "      <td>4.25</td>\n",
       "      <td>7.61</td>\n",
       "      <td>144.50</td>\n",
       "      <td>3.65</td>\n",
       "      <td>3.65</td>\n",
       "      <td>6.53</td>\n",
       "      <td>3.65</td>\n",
       "      <td>6.53</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1354</th>\n",
       "      <td>1993</td>\n",
       "      <td>California</td>\n",
       "      <td>4.25</td>\n",
       "      <td>7.61</td>\n",
       "      <td>4.25</td>\n",
       "      <td>7.61</td>\n",
       "      <td>4.25</td>\n",
       "      <td>7.61</td>\n",
       "      <td>144.50</td>\n",
       "      <td>4.25</td>\n",
       "      <td>4.25</td>\n",
       "      <td>7.61</td>\n",
       "      <td>4.25</td>\n",
       "      <td>7.61</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",
       "      <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>2857</th>\n",
       "      <td>2020</td>\n",
       "      <td>Virginia</td>\n",
       "      <td>7.25</td>\n",
       "      <td>7.25</td>\n",
       "      <td>7.25</td>\n",
       "      <td>7.25</td>\n",
       "      <td>7.25</td>\n",
       "      <td>7.25</td>\n",
       "      <td>258.66</td>\n",
       "      <td>7.25[c]</td>\n",
       "      <td>7.25</td>\n",
       "      <td>7.25</td>\n",
       "      <td>7.25</td>\n",
       "      <td>7.25</td>\n",
       "      <td>[c]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2858</th>\n",
       "      <td>2020</td>\n",
       "      <td>Washington</td>\n",
       "      <td>13.50</td>\n",
       "      <td>13.50</td>\n",
       "      <td>7.25</td>\n",
       "      <td>7.25</td>\n",
       "      <td>13.50</td>\n",
       "      <td>13.50</td>\n",
       "      <td>258.66</td>\n",
       "      <td>13.5</td>\n",
       "      <td>13.50</td>\n",
       "      <td>13.50</td>\n",
       "      <td>13.50</td>\n",
       "      <td>13.50</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2859</th>\n",
       "      <td>2020</td>\n",
       "      <td>West Virginia</td>\n",
       "      <td>8.75</td>\n",
       "      <td>8.75</td>\n",
       "      <td>7.25</td>\n",
       "      <td>7.25</td>\n",
       "      <td>8.75</td>\n",
       "      <td>8.75</td>\n",
       "      <td>258.66</td>\n",
       "      <td>8.75</td>\n",
       "      <td>8.75</td>\n",
       "      <td>8.75</td>\n",
       "      <td>8.75</td>\n",
       "      <td>8.75</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2860</th>\n",
       "      <td>2020</td>\n",
       "      <td>Wisconsin</td>\n",
       "      <td>7.25</td>\n",
       "      <td>7.25</td>\n",
       "      <td>7.25</td>\n",
       "      <td>7.25</td>\n",
       "      <td>7.25</td>\n",
       "      <td>7.25</td>\n",
       "      <td>258.66</td>\n",
       "      <td>7.25</td>\n",
       "      <td>7.25</td>\n",
       "      <td>7.25</td>\n",
       "      <td>7.25</td>\n",
       "      <td>7.25</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2861</th>\n",
       "      <td>2020</td>\n",
       "      <td>Wyoming</td>\n",
       "      <td>5.15</td>\n",
       "      <td>5.15</td>\n",
       "      <td>7.25</td>\n",
       "      <td>7.25</td>\n",
       "      <td>7.25</td>\n",
       "      <td>7.25</td>\n",
       "      <td>258.66</td>\n",
       "      <td>5.15</td>\n",
       "      <td>5.15</td>\n",
       "      <td>5.15</td>\n",
       "      <td>5.15</td>\n",
       "      <td>5.15</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1512 rows × 15 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Year          State  State.Minimum.Wage  \\\n",
       "1350  1993        Alabama                0.00   \n",
       "1351  1993         Alaska                4.75   \n",
       "1352  1993        Arizona                0.00   \n",
       "1353  1993       Arkansas                3.65   \n",
       "1354  1993     California                4.25   \n",
       "...    ...            ...                 ...   \n",
       "2857  2020       Virginia                7.25   \n",
       "2858  2020     Washington               13.50   \n",
       "2859  2020  West Virginia                8.75   \n",
       "2860  2020      Wisconsin                7.25   \n",
       "2861  2020        Wyoming                5.15   \n",
       "\n",
       "      State.Minimum.Wage.2020.Dollars  Federal.Minimum.Wage  \\\n",
       "1350                             0.00                  4.25   \n",
       "1351                             8.50                  4.25   \n",
       "1352                             0.00                  4.25   \n",
       "1353                             6.53                  4.25   \n",
       "1354                             7.61                  4.25   \n",
       "...                               ...                   ...   \n",
       "2857                             7.25                  7.25   \n",
       "2858                            13.50                  7.25   \n",
       "2859                             8.75                  7.25   \n",
       "2860                             7.25                  7.25   \n",
       "2861                             5.15                  7.25   \n",
       "\n",
       "      Federal.Minimum.Wage.2020.Dollars  Effective.Minimum.Wage  \\\n",
       "1350                               7.61                    4.25   \n",
       "1351                               7.61                    4.75   \n",
       "1352                               7.61                    4.25   \n",
       "1353                               7.61                    4.25   \n",
       "1354                               7.61                    4.25   \n",
       "...                                 ...                     ...   \n",
       "2857                               7.25                    7.25   \n",
       "2858                               7.25                   13.50   \n",
       "2859                               7.25                    8.75   \n",
       "2860                               7.25                    7.25   \n",
       "2861                               7.25                    7.25   \n",
       "\n",
       "      Effective.Minimum.Wage.2020.Dollars  CPI.Average  \\\n",
       "1350                                 7.61       144.50   \n",
       "1351                                 8.50       144.50   \n",
       "1352                                 7.61       144.50   \n",
       "1353                                 7.61       144.50   \n",
       "1354                                 7.61       144.50   \n",
       "...                                   ...          ...   \n",
       "2857                                 7.25       258.66   \n",
       "2858                                13.50       258.66   \n",
       "2859                                 8.75       258.66   \n",
       "2860                                 7.25       258.66   \n",
       "2861                                 7.25       258.66   \n",
       "\n",
       "     Department.Of.Labor.Uncleaned.Data  \\\n",
       "1350                                ...   \n",
       "1351                               4.75   \n",
       "1352                                ...   \n",
       "1353                               3.65   \n",
       "1354                               4.25   \n",
       "...                                 ...   \n",
       "2857                            7.25[c]   \n",
       "2858                               13.5   \n",
       "2859                               8.75   \n",
       "2860                               7.25   \n",
       "2861                               5.15   \n",
       "\n",
       "      Department.Of.Labor.Cleaned.Low.Value  \\\n",
       "1350                                   0.00   \n",
       "1351                                   4.75   \n",
       "1352                                   0.00   \n",
       "1353                                   3.65   \n",
       "1354                                   4.25   \n",
       "...                                     ...   \n",
       "2857                                   7.25   \n",
       "2858                                  13.50   \n",
       "2859                                   8.75   \n",
       "2860                                   7.25   \n",
       "2861                                   5.15   \n",
       "\n",
       "      Department.Of.Labor.Cleaned.Low.Value.2020.Dollars  \\\n",
       "1350                                               0.00    \n",
       "1351                                               8.50    \n",
       "1352                                               0.00    \n",
       "1353                                               6.53    \n",
       "1354                                               7.61    \n",
       "...                                                 ...    \n",
       "2857                                               7.25    \n",
       "2858                                              13.50    \n",
       "2859                                               8.75    \n",
       "2860                                               7.25    \n",
       "2861                                               5.15    \n",
       "\n",
       "      Department.Of.Labor.Cleaned.High.Value  \\\n",
       "1350                                    0.00   \n",
       "1351                                    4.75   \n",
       "1352                                    0.00   \n",
       "1353                                    3.65   \n",
       "1354                                    4.25   \n",
       "...                                      ...   \n",
       "2857                                    7.25   \n",
       "2858                                   13.50   \n",
       "2859                                    8.75   \n",
       "2860                                    7.25   \n",
       "2861                                    5.15   \n",
       "\n",
       "      Department.Of.Labor.Cleaned.High.Value.2020.Dollars Footnote  \n",
       "1350                                               0.00        NaN  \n",
       "1351                                               8.50        NaN  \n",
       "1352                                               0.00        NaN  \n",
       "1353                                               6.53        NaN  \n",
       "1354                                               7.61        NaN  \n",
       "...                                                 ...        ...  \n",
       "2857                                               7.25        [c]  \n",
       "2858                                              13.50        NaN  \n",
       "2859                                               8.75        NaN  \n",
       "2860                                               7.25        NaN  \n",
       "2861                                               5.15        NaN  \n",
       "\n",
       "[1512 rows x 15 columns]"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "min_wage_df = pd.read_csv(\"min_wage.csv\",encoding='cp1252')\n",
    "min_wage_df = min_wage_df[min_wage_df['Year'] >= 1993]\n",
    "min_wage_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "02193713-fd58-4404-a1c8-2ad96f15390d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\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>Year</th>\n",
       "      <th>State</th>\n",
       "      <th>State.Minimum.Wage</th>\n",
       "      <th>State.Minimum.Wage.2020.Dollars</th>\n",
       "      <th>Federal.Minimum.Wage</th>\n",
       "      <th>Federal.Minimum.Wage.2020.Dollars</th>\n",
       "      <th>Effective.Minimum.Wage</th>\n",
       "      <th>Effective.Minimum.Wage.2020.Dollars</th>\n",
       "      <th>CPI.Average</th>\n",
       "      <th>Department.Of.Labor.Uncleaned.Data</th>\n",
       "      <th>Department.Of.Labor.Cleaned.Low.Value</th>\n",
       "      <th>Department.Of.Labor.Cleaned.Low.Value.2020.Dollars</th>\n",
       "      <th>Department.Of.Labor.Cleaned.High.Value</th>\n",
       "      <th>Department.Of.Labor.Cleaned.High.Value.2020.Dollars</th>\n",
       "      <th>Footnote</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1993</td>\n",
       "      <td>AK</td>\n",
       "      <td>4.75</td>\n",
       "      <td>8.50</td>\n",
       "      <td>4.25</td>\n",
       "      <td>7.61</td>\n",
       "      <td>4.75</td>\n",
       "      <td>8.50</td>\n",
       "      <td>144.5</td>\n",
       "      <td>4.75</td>\n",
       "      <td>4.75</td>\n",
       "      <td>8.50</td>\n",
       "      <td>4.75</td>\n",
       "      <td>8.50</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1994</td>\n",
       "      <td>AK</td>\n",
       "      <td>4.75</td>\n",
       "      <td>8.29</td>\n",
       "      <td>4.25</td>\n",
       "      <td>7.42</td>\n",
       "      <td>4.75</td>\n",
       "      <td>8.29</td>\n",
       "      <td>148.2</td>\n",
       "      <td>4.75</td>\n",
       "      <td>4.75</td>\n",
       "      <td>8.29</td>\n",
       "      <td>4.75</td>\n",
       "      <td>8.29</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1995</td>\n",
       "      <td>AK</td>\n",
       "      <td>4.75</td>\n",
       "      <td>8.06</td>\n",
       "      <td>4.25</td>\n",
       "      <td>7.21</td>\n",
       "      <td>4.75</td>\n",
       "      <td>8.06</td>\n",
       "      <td>152.4</td>\n",
       "      <td>4.75</td>\n",
       "      <td>4.75</td>\n",
       "      <td>8.06</td>\n",
       "      <td>4.75</td>\n",
       "      <td>8.06</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1996</td>\n",
       "      <td>AK</td>\n",
       "      <td>4.75</td>\n",
       "      <td>7.83</td>\n",
       "      <td>4.25</td>\n",
       "      <td>7.01</td>\n",
       "      <td>4.75</td>\n",
       "      <td>7.83</td>\n",
       "      <td>156.9</td>\n",
       "      <td>4.75</td>\n",
       "      <td>4.75</td>\n",
       "      <td>7.83</td>\n",
       "      <td>4.75</td>\n",
       "      <td>7.83</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1997</td>\n",
       "      <td>AK</td>\n",
       "      <td>5.25</td>\n",
       "      <td>8.46</td>\n",
       "      <td>4.75</td>\n",
       "      <td>7.66</td>\n",
       "      <td>5.25</td>\n",
       "      <td>8.46</td>\n",
       "      <td>160.5</td>\n",
       "      <td>5.25</td>\n",
       "      <td>5.25</td>\n",
       "      <td>8.46</td>\n",
       "      <td>5.25</td>\n",
       "      <td>8.46</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Year State  State.Minimum.Wage  State.Minimum.Wage.2020.Dollars  \\\n",
       "0  1993    AK                4.75                             8.50   \n",
       "1  1994    AK                4.75                             8.29   \n",
       "2  1995    AK                4.75                             8.06   \n",
       "3  1996    AK                4.75                             7.83   \n",
       "4  1997    AK                5.25                             8.46   \n",
       "\n",
       "   Federal.Minimum.Wage  Federal.Minimum.Wage.2020.Dollars  \\\n",
       "0                  4.25                               7.61   \n",
       "1                  4.25                               7.42   \n",
       "2                  4.25                               7.21   \n",
       "3                  4.25                               7.01   \n",
       "4                  4.75                               7.66   \n",
       "\n",
       "   Effective.Minimum.Wage  Effective.Minimum.Wage.2020.Dollars  CPI.Average  \\\n",
       "0                    4.75                                 8.50        144.5   \n",
       "1                    4.75                                 8.29        148.2   \n",
       "2                    4.75                                 8.06        152.4   \n",
       "3                    4.75                                 7.83        156.9   \n",
       "4                    5.25                                 8.46        160.5   \n",
       "\n",
       "  Department.Of.Labor.Uncleaned.Data  Department.Of.Labor.Cleaned.Low.Value  \\\n",
       "0                               4.75                                   4.75   \n",
       "1                               4.75                                   4.75   \n",
       "2                               4.75                                   4.75   \n",
       "3                               4.75                                   4.75   \n",
       "4                               5.25                                   5.25   \n",
       "\n",
       "   Department.Of.Labor.Cleaned.Low.Value.2020.Dollars  \\\n",
       "0                                               8.50    \n",
       "1                                               8.29    \n",
       "2                                               8.06    \n",
       "3                                               7.83    \n",
       "4                                               8.46    \n",
       "\n",
       "   Department.Of.Labor.Cleaned.High.Value  \\\n",
       "0                                    4.75   \n",
       "1                                    4.75   \n",
       "2                                    4.75   \n",
       "3                                    4.75   \n",
       "4                                    5.25   \n",
       "\n",
       "   Department.Of.Labor.Cleaned.High.Value.2020.Dollars Footnote  \n",
       "0                                               8.50        NaN  \n",
       "1                                               8.29        NaN  \n",
       "2                                               8.06        NaN  \n",
       "3                                               7.83        NaN  \n",
       "4                                               8.46        NaN  "
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "us_state_to_abbrev_min_wage = {\"State\" : {\n",
    "    \"Alabama\": \"AL\",\n",
    "    \"Alaska\": \"AK\",\n",
    "    \"Arizona\": \"AZ\",\n",
    "    \"Arkansas\": \"AR\",\n",
    "    \"California\": \"CA\",\n",
    "    \"Colorado\": \"CO\",\n",
    "    \"Connecticut\": \"CT\",\n",
    "    \"Delaware\": \"DE\",\n",
    "    \"Florida\": \"FL\",\n",
    "    \"Georgia\": \"GA\",\n",
    "    \"Hawaii\": \"HI\",\n",
    "    \"Idaho\": \"ID\",\n",
    "    \"Illinois\": \"IL\",\n",
    "    \"Indiana\": \"IN\",\n",
    "    \"Iowa\": \"IA\",\n",
    "    \"Kansas\": \"KS\",\n",
    "    \"Kentucky\": \"KY\",\n",
    "    \"Louisiana\": \"LA\",\n",
    "    \"Maine\": \"ME\",\n",
    "    \"Maryland\": \"MD\",\n",
    "    \"Massachusetts\": \"MA\",\n",
    "    \"Michigan\": \"MI\",\n",
    "    \"Minnesota\": \"MN\",\n",
    "    \"Mississippi\": \"MS\",\n",
    "    \"Missouri\": \"MO\",\n",
    "    \"Montana\": \"MT\",\n",
    "    \"Nebraska\": \"NE\",\n",
    "    \"Nevada\": \"NV\",\n",
    "    \"New Hampshire\": \"NH\",\n",
    "    \"New Jersey\": \"NJ\",\n",
    "    \"New Mexico\": \"NM\",\n",
    "    \"New York\": \"NY\",\n",
    "    \"North Carolina\": \"NC\",\n",
    "    \"North Dakota\": \"ND\",\n",
    "    \"Ohio\": \"OH\",\n",
    "    \"Oklahoma\": \"OK\",\n",
    "    \"Oregon\": \"OR\",\n",
    "    \"Pennsylvania\": \"PA\",\n",
    "    \"Rhode Island\": \"RI\",\n",
    "    \"South Carolina\": \"SC\",\n",
    "    \"South Dakota\": \"SD\",\n",
    "    \"Tennessee\": \"TN\",\n",
    "    \"Texas\": \"TX\",\n",
    "    \"Utah\": \"UT\",\n",
    "    \"Vermont\": \"VT\",\n",
    "    \"Virginia\": \"VA\",\n",
    "    \"Washington\": \"WA\",\n",
    "    \"West Virginia\": \"WV\",\n",
    "    \"Wisconsin\": \"WI\",\n",
    "    \"Wyoming\": \"WY\",\n",
    "    \"District of Columbia\": \"DC\",\n",
    "    \"American Samoa\": \"AS\",\n",
    "    \"Guam\": \"GU\",\n",
    "    \"Northern Mariana Islands\": \"MP\",\n",
    "    \"Puerto Rico\": \"PR\",\n",
    "    \"United States Minor Outlying Islands\": \"UM\",\n",
    "    \"U.S. Virgin Islands\": \"VI\",\n",
    "}}\n",
    "min_wage_df = min_wage_df.replace(us_state_to_abbrev_min_wage)\n",
    "min_wage_df.sort_values(['State','Year'],inplace=True)\n",
    "min_wage_df = min_wage_df.reset_index().drop(columns=['index'])\n",
    "min_wage_df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1142f659-7c26-4cf7-b07c-be53654850cc",
   "metadata": {},
   "source": [
    "## Nearest States Dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "48c218b8-c34f-4685-963c-8d4913c92a49",
   "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>state</th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "      <th>Closest State #1</th>\n",
       "      <th>Distance to Closest State #1</th>\n",
       "      <th>Closest State #2</th>\n",
       "      <th>Distance to Closest State #2</th>\n",
       "      <th>Closest State #3</th>\n",
       "      <th>Distance to Closest State #3</th>\n",
       "      <th>Closest State #4</th>\n",
       "      <th>Distance to Closest State #4</th>\n",
       "      <th>Closest State #5</th>\n",
       "      <th>Distance to Closest State #5</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>AL</td>\n",
       "      <td>32.7794</td>\n",
       "      <td>-86.8287</td>\n",
       "      <td>MS</td>\n",
       "      <td>165.334460</td>\n",
       "      <td>GA</td>\n",
       "      <td>197.487904</td>\n",
       "      <td>TN</td>\n",
       "      <td>213.954618</td>\n",
       "      <td>LA</td>\n",
       "      <td>325.712907</td>\n",
       "      <td>KY</td>\n",
       "      <td>339.003175</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>AK</td>\n",
       "      <td>64.0685</td>\n",
       "      <td>-152.2782</td>\n",
       "      <td>WA</td>\n",
       "      <td>1663.916968</td>\n",
       "      <td>OR</td>\n",
       "      <td>1861.858430</td>\n",
       "      <td>MT</td>\n",
       "      <td>1985.735915</td>\n",
       "      <td>ID</td>\n",
       "      <td>1995.169309</td>\n",
       "      <td>ND</td>\n",
       "      <td>2237.421669</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>AZ</td>\n",
       "      <td>34.2744</td>\n",
       "      <td>-111.6602</td>\n",
       "      <td>NM</td>\n",
       "      <td>317.276353</td>\n",
       "      <td>UT</td>\n",
       "      <td>346.924962</td>\n",
       "      <td>NV</td>\n",
       "      <td>444.202213</td>\n",
       "      <td>CO</td>\n",
       "      <td>470.340950</td>\n",
       "      <td>CA</td>\n",
       "      <td>482.459726</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>AR</td>\n",
       "      <td>34.8938</td>\n",
       "      <td>-92.4426</td>\n",
       "      <td>MS</td>\n",
       "      <td>218.135844</td>\n",
       "      <td>MO</td>\n",
       "      <td>238.775500</td>\n",
       "      <td>LA</td>\n",
       "      <td>264.851958</td>\n",
       "      <td>OK</td>\n",
       "      <td>289.663758</td>\n",
       "      <td>TN</td>\n",
       "      <td>350.279840</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>CA</td>\n",
       "      <td>37.1841</td>\n",
       "      <td>-119.4696</td>\n",
       "      <td>NV</td>\n",
       "      <td>213.785465</td>\n",
       "      <td>UT</td>\n",
       "      <td>448.579321</td>\n",
       "      <td>OR</td>\n",
       "      <td>469.217131</td>\n",
       "      <td>AZ</td>\n",
       "      <td>482.459726</td>\n",
       "      <td>ID</td>\n",
       "      <td>556.046610</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  state  latitude  longitude Closest State #1  Distance to Closest State #1  \\\n",
       "0    AL   32.7794   -86.8287               MS                    165.334460   \n",
       "1    AK   64.0685  -152.2782               WA                   1663.916968   \n",
       "2    AZ   34.2744  -111.6602               NM                    317.276353   \n",
       "3    AR   34.8938   -92.4426               MS                    218.135844   \n",
       "4    CA   37.1841  -119.4696               NV                    213.785465   \n",
       "\n",
       "  Closest State #2  Distance to Closest State #2 Closest State #3  \\\n",
       "0               GA                    197.487904               TN   \n",
       "1               OR                   1861.858430               MT   \n",
       "2               UT                    346.924962               NV   \n",
       "3               MO                    238.775500               LA   \n",
       "4               UT                    448.579321               OR   \n",
       "\n",
       "   Distance to Closest State #3 Closest State #4  \\\n",
       "0                    213.954618               LA   \n",
       "1                   1985.735915               ID   \n",
       "2                    444.202213               CO   \n",
       "3                    264.851958               OK   \n",
       "4                    469.217131               AZ   \n",
       "\n",
       "   Distance to Closest State #4 Closest State #5  Distance to Closest State #5  \n",
       "0                    325.712907               KY                    339.003175  \n",
       "1                   1995.169309               ND                   2237.421669  \n",
       "2                    470.340950               CA                    482.459726  \n",
       "3                    289.663758               TN                    350.279840  \n",
       "4                    482.459726               ID                    556.046610  "
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "distances_df = pd.read_csv(\"distances_df.csv\")\n",
    "distances_df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ea6358c6-8b67-4675-9ebd-3c0847a2884d",
   "metadata": {},
   "source": [
    "## State Inflation Dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "5d40a48e-ba76-4d0d-ae02-4b4ecc6c2855",
   "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>state</th>\n",
       "      <th>year</th>\n",
       "      <th>pi_nt</th>\n",
       "      <th>pi_t</th>\n",
       "      <th>pi</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Alabama</td>\n",
       "      <td>1989</td>\n",
       "      <td>15.782732</td>\n",
       "      <td>18.149607</td>\n",
       "      <td>17.063328</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Alabama</td>\n",
       "      <td>1990</td>\n",
       "      <td>13.691798</td>\n",
       "      <td>16.391293</td>\n",
       "      <td>15.103246</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Alabama</td>\n",
       "      <td>1991</td>\n",
       "      <td>24.342764</td>\n",
       "      <td>5.256562</td>\n",
       "      <td>15.858694</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Alabama</td>\n",
       "      <td>1992</td>\n",
       "      <td>9.125672</td>\n",
       "      <td>-0.824136</td>\n",
       "      <td>5.000021</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Alabama</td>\n",
       "      <td>1993</td>\n",
       "      <td>13.388873</td>\n",
       "      <td>5.596229</td>\n",
       "      <td>10.185112</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     state  year      pi_nt       pi_t         pi\n",
       "0  Alabama  1989  15.782732  18.149607  17.063328\n",
       "1  Alabama  1990  13.691798  16.391293  15.103246\n",
       "2  Alabama  1991  24.342764   5.256562  15.858694\n",
       "3  Alabama  1992   9.125672  -0.824136   5.000021\n",
       "4  Alabama  1993  13.388873   5.596229  10.185112"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "state_inflation_df = pd.read_csv(\"statecpi_beta.csv\")\n",
    "for i in ['pi_nt','pi_t','pi']:\n",
    "    state_inflation_df[i + \"_prop\"] = state_inflation_df[i]/100+1\n",
    "state_inflation_df = (state_inflation_df.groupby(['state','year'])[['pi_nt_prop','pi_t_prop','pi_prop']].agg(np.prod)-1)*100\n",
    "state_inflation_df.rename(columns={'pi_nt_prop': 'pi_nt','pi_t_prop': 'pi_t','pi_prop': 'pi'},inplace=True)\n",
    "state_inflation_df.reset_index(inplace=True)\n",
    "state_inflation_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "244660d1-cd35-45f3-a91c-54063b8cc0e9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
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       "    }\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>state</th>\n",
       "      <th>year</th>\n",
       "      <th>pi_nt</th>\n",
       "      <th>pi_t</th>\n",
       "      <th>pi</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>AL</td>\n",
       "      <td>1989</td>\n",
       "      <td>15.782732</td>\n",
       "      <td>18.149607</td>\n",
       "      <td>17.063328</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>AL</td>\n",
       "      <td>1990</td>\n",
       "      <td>13.691798</td>\n",
       "      <td>16.391293</td>\n",
       "      <td>15.103246</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>AL</td>\n",
       "      <td>1991</td>\n",
       "      <td>24.342764</td>\n",
       "      <td>5.256562</td>\n",
       "      <td>15.858694</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>AL</td>\n",
       "      <td>1992</td>\n",
       "      <td>9.125672</td>\n",
       "      <td>-0.824136</td>\n",
       "      <td>5.000021</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>AL</td>\n",
       "      <td>1993</td>\n",
       "      <td>13.388873</td>\n",
       "      <td>5.596229</td>\n",
       "      <td>10.185112</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1170</th>\n",
       "      <td>WI</td>\n",
       "      <td>2013</td>\n",
       "      <td>10.199952</td>\n",
       "      <td>-1.088311</td>\n",
       "      <td>6.491816</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1171</th>\n",
       "      <td>WI</td>\n",
       "      <td>2014</td>\n",
       "      <td>8.692873</td>\n",
       "      <td>2.716131</td>\n",
       "      <td>6.835408</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1172</th>\n",
       "      <td>WI</td>\n",
       "      <td>2015</td>\n",
       "      <td>5.133358</td>\n",
       "      <td>-9.183445</td>\n",
       "      <td>-0.237336</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1173</th>\n",
       "      <td>WI</td>\n",
       "      <td>2016</td>\n",
       "      <td>2.546422</td>\n",
       "      <td>-5.558837</td>\n",
       "      <td>-0.465041</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1174</th>\n",
       "      <td>WI</td>\n",
       "      <td>2017</td>\n",
       "      <td>9.789466</td>\n",
       "      <td>4.999244</td>\n",
       "      <td>8.737010</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1175 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     state  year      pi_nt       pi_t         pi\n",
       "0       AL  1989  15.782732  18.149607  17.063328\n",
       "1       AL  1990  13.691798  16.391293  15.103246\n",
       "2       AL  1991  24.342764   5.256562  15.858694\n",
       "3       AL  1992   9.125672  -0.824136   5.000021\n",
       "4       AL  1993  13.388873   5.596229  10.185112\n",
       "...    ...   ...        ...        ...        ...\n",
       "1170    WI  2013  10.199952  -1.088311   6.491816\n",
       "1171    WI  2014   8.692873   2.716131   6.835408\n",
       "1172    WI  2015   5.133358  -9.183445  -0.237336\n",
       "1173    WI  2016   2.546422  -5.558837  -0.465041\n",
       "1174    WI  2017   9.789466   4.999244   8.737010\n",
       "\n",
       "[1175 rows x 5 columns]"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "us_state_inf_to_abbrev = {\"state\" : {\n",
    "    \"Alabama\": \"AL\",\n",
    "    \"Alaska\": \"AK\",\n",
    "    \"Arizona\": \"AZ\",\n",
    "    \"Arkansas\": \"AR\",\n",
    "    \"California\": \"CA\",\n",
    "    \"Colorado\": \"CO\",\n",
    "    \"Connecticut\": \"CT\",\n",
    "    \"Delaware\": \"DE\",\n",
    "    \"Florida\": \"FL\",\n",
    "    \"Georgia\": \"GA\",\n",
    "    \"Hawaii\": \"HI\",\n",
    "    \"Idaho\": \"ID\",\n",
    "    \"Illinois\": \"IL\",\n",
    "    \"Indiana\": \"IN\",\n",
    "    \"Iowa\": \"IA\",\n",
    "    \"Kansas\": \"KS\",\n",
    "    \"Kentucky\": \"KY\",\n",
    "    \"Louisiana\": \"LA\",\n",
    "    \"Maine\": \"ME\",\n",
    "    \"Maryland\": \"MD\",\n",
    "    \"Massachusetts\": \"MA\",\n",
    "    \"Michigan\": \"MI\",\n",
    "    \"Minnesota\": \"MN\",\n",
    "    \"Mississippi\": \"MS\",\n",
    "    \"Missouri\": \"MO\",\n",
    "    \"Montana\": \"MT\",\n",
    "    \"Nebraska\": \"NE\",\n",
    "    \"Nevada\": \"NV\",\n",
    "    \"New Hampshire\": \"NH\",\n",
    "    \"New Jersey\": \"NJ\",\n",
    "    \"New Mexico\": \"NM\",\n",
    "    \"New York\": \"NY\",\n",
    "    \"North Carolina\": \"NC\",\n",
    "    \"North Dakota\": \"ND\",\n",
    "    \"Ohio\": \"OH\",\n",
    "    \"Oklahoma\": \"OK\",\n",
    "    \"Oregon\": \"OR\",\n",
    "    \"Pennsylvania\": \"PA\",\n",
    "    \"Rhode Island\": \"RI\",\n",
    "    \"South Carolina\": \"SC\",\n",
    "    \"South Dakota\": \"SD\",\n",
    "    \"Tennessee\": \"TN\",\n",
    "    \"Texas\": \"TX\",\n",
    "    \"Utah\": \"UT\",\n",
    "    \"Vermont\": \"VT\",\n",
    "    \"Virginia\": \"VA\",\n",
    "    \"Washington\": \"WA\",\n",
    "    \"West Virginia\": \"WV\",\n",
    "    \"Wisconsin\": \"WI\",\n",
    "    \"Wyoming\": \"WY\",\n",
    "    \"District of Columbia\": \"DC\",\n",
    "    \"American Samoa\": \"AS\",\n",
    "    \"Guam\": \"GU\",\n",
    "    \"Northern Mariana Islands\": \"MP\",\n",
    "    \"Puerto Rico\": \"PR\",\n",
    "    \"United States Minor Outlying Islands\": \"UM\",\n",
    "    \"U.S. Virgin Islands\": \"VI\",\n",
    "}}\n",
    "state_inflation_df = state_inflation_df.replace(us_state_inf_to_abbrev)\n",
    "state_inflation_df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c5f46704-7823-4ab4-869a-429349eacbf6",
   "metadata": {},
   "source": [
    "## US Inflation Dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "1edc010f-1bb3-449e-9b84-0cc9225eb6c2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\n",
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       "\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Year</th>\n",
       "      <th>Jan</th>\n",
       "      <th>Feb</th>\n",
       "      <th>Mar</th>\n",
       "      <th>Apr</th>\n",
       "      <th>May</th>\n",
       "      <th>Jun</th>\n",
       "      <th>Jul</th>\n",
       "      <th>Aug</th>\n",
       "      <th>Sep</th>\n",
       "      <th>Oct</th>\n",
       "      <th>Nov</th>\n",
       "      <th>Dec</th>\n",
       "      <th>Annual</th>\n",
       "      <th>HALF1</th>\n",
       "      <th>HALF2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1993</td>\n",
       "      <td>3.5</td>\n",
       "      <td>3.6</td>\n",
       "      <td>3.4</td>\n",
       "      <td>3.5</td>\n",
       "      <td>3.4</td>\n",
       "      <td>3.3</td>\n",
       "      <td>3.2</td>\n",
       "      <td>3.3</td>\n",
       "      <td>3.2</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.1</td>\n",
       "      <td>3.2</td>\n",
       "      <td>3.3</td>\n",
       "      <td>3.4</td>\n",
       "      <td>3.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1994</td>\n",
       "      <td>2.9</td>\n",
       "      <td>2.8</td>\n",
       "      <td>2.9</td>\n",
       "      <td>2.8</td>\n",
       "      <td>2.8</td>\n",
       "      <td>2.9</td>\n",
       "      <td>2.9</td>\n",
       "      <td>2.9</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.9</td>\n",
       "      <td>2.8</td>\n",
       "      <td>2.6</td>\n",
       "      <td>2.8</td>\n",
       "      <td>2.8</td>\n",
       "      <td>2.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1995</td>\n",
       "      <td>2.9</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.1</td>\n",
       "      <td>3.1</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.9</td>\n",
       "      <td>2.9</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1996</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.9</td>\n",
       "      <td>2.8</td>\n",
       "      <td>2.7</td>\n",
       "      <td>2.7</td>\n",
       "      <td>2.7</td>\n",
       "      <td>2.7</td>\n",
       "      <td>2.6</td>\n",
       "      <td>2.7</td>\n",
       "      <td>2.6</td>\n",
       "      <td>2.6</td>\n",
       "      <td>2.6</td>\n",
       "      <td>2.7</td>\n",
       "      <td>2.7</td>\n",
       "      <td>2.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1997</td>\n",
       "      <td>2.5</td>\n",
       "      <td>2.5</td>\n",
       "      <td>2.5</td>\n",
       "      <td>2.7</td>\n",
       "      <td>2.5</td>\n",
       "      <td>2.4</td>\n",
       "      <td>2.4</td>\n",
       "      <td>2.3</td>\n",
       "      <td>2.2</td>\n",
       "      <td>2.3</td>\n",
       "      <td>2.2</td>\n",
       "      <td>2.2</td>\n",
       "      <td>2.4</td>\n",
       "      <td>2.6</td>\n",
       "      <td>2.2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Year  Jan  Feb  Mar  Apr  May  Jun  Jul  Aug  Sep  Oct  Nov  Dec  Annual  \\\n",
       "0  1993  3.5  3.6  3.4  3.5  3.4  3.3  3.2  3.3  3.2  3.0  3.1  3.2     3.3   \n",
       "1  1994  2.9  2.8  2.9  2.8  2.8  2.9  2.9  2.9  3.0  2.9  2.8  2.6     2.8   \n",
       "2  1995  2.9  3.0  3.0  3.1  3.1  3.0  3.0  2.9  2.9  3.0  3.0  3.0     3.0   \n",
       "3  1996  3.0  2.9  2.8  2.7  2.7  2.7  2.7  2.6  2.7  2.6  2.6  2.6     2.7   \n",
       "4  1997  2.5  2.5  2.5  2.7  2.5  2.4  2.4  2.3  2.2  2.3  2.2  2.2     2.4   \n",
       "\n",
       "   HALF1  HALF2  \n",
       "0    3.4    3.2  \n",
       "1    2.8    2.9  \n",
       "2    3.0    3.0  \n",
       "3    2.7    2.7  \n",
       "4    2.6    2.2  "
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "us_inf = pd.read_excel(\"us_inf.xlsx\")\n",
    "us_inf.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8ae9ab85-f719-4df7-a7c0-9f3cfe6bcc6e",
   "metadata": {},
   "source": [
    "## Combining BLS and FMCS Datasets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "fc5bde7a-d0e7-44bc-a5f2-ea9ee3aaeb95",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['AK', 'AL', 'AR', 'AZ', 'CA', 'CO', 'CT', 'DC', 'DE', 'FL', 'GA', 'HI', 'IA', 'ID', 'IL', 'IN', 'KS', 'KY', 'LA', 'MA', 'MD', 'ME', 'MI', 'MN', 'MO', 'MS', 'MT', 'NC', 'ND', 'NE', 'NH', 'NJ', 'NM', 'NV', 'NY', 'OH', 'OK', 'OR', 'PA', 'RI', 'SC', 'TN', 'TX', 'UT', 'VA', 'VT', 'WA', 'WI', 'WV', 'VI', 'SD', 'WY']\n"
     ]
    }
   ],
   "source": [
    "lst = []\n",
    "for x in grouped_bls_df['States'].unique():\n",
    "    lst = lst + [x]\n",
    "for x in grouped_fmcs_df['State'].unique():\n",
    "    if x not in lst:\n",
    "        lst = lst + [x]\n",
    "for x in union_df_priv['State'].unique():\n",
    "    if x not in lst:\n",
    "        lst = lst + [x]\n",
    "for x in full_poli_df['state_po'].unique():\n",
    "    if x not in lst:\n",
    "        lst = lst + [x]\n",
    "print(lst)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "e7787c65-5558-47b7-a3fa-5b749fe30a6f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\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>State</th>\n",
       "      <th>Year</th>\n",
       "      <th>Strikers</th>\n",
       "      <th>FMCS Interest</th>\n",
       "      <th>valid strikers</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>AK</td>\n",
       "      <td>1993</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>AK</td>\n",
       "      <td>1994</td>\n",
       "      <td>2900.0</td>\n",
       "      <td>0</td>\n",
       "      <td>2900.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>AK</td>\n",
       "      <td>1995</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>AK</td>\n",
       "      <td>1996</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>AK</td>\n",
       "      <td>1997</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  State  Year Strikers FMCS Interest valid strikers\n",
       "1    AK  1993        0             0              0\n",
       "2    AK  1994   2900.0             0         2900.0\n",
       "3    AK  1995        0             0              0\n",
       "4    AK  1996        0             0              0\n",
       "5    AK  1997        0             0              0"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "new_df = pd.DataFrame(columns=['State','Year','Strikers','FMCS Interest'])\n",
    "new_df.loc[0,:] = ['AL',1990,1500,1950]\n",
    "for state in lst:\n",
    "    for year in np.arange(1993,2021):\n",
    "        striking_workers = 0\n",
    "        fmcs_workers = 0\n",
    "        if len(grouped_bls_df[(grouped_bls_df['States'] == state) & (grouped_bls_df['start_year'] == year)]) == 1:\n",
    "            striking_workers = grouped_bls_df[(grouped_bls_df['States'] == state) & (grouped_bls_df['start_year'] == year)]['Number of workers[2]'].iloc[0]\n",
    "        elif len(grouped_bls_df[(grouped_bls_df['States'] == state) & (grouped_bls_df['start_year'] == year)]) > 1:\n",
    "            print(state,year)\n",
    "        if len(grouped_fmcs_df[(grouped_fmcs_df['State'] == state) & (grouped_fmcs_df['start_year'] == year)]) == 1:\n",
    "            fmcs_workers = grouped_fmcs_df[(grouped_fmcs_df['State'] == state) & (grouped_fmcs_df['start_year'] == year)]['# Idled'].iloc[0]\n",
    "        elif len(grouped_fmcs_df[(grouped_fmcs_df['State'] == state) & (grouped_fmcs_df['start_year'] == year)]) > 1:\n",
    "            print(state,year)\n",
    "        new_df.loc[new_df.index.max()+1,:] = [state,year,striking_workers,fmcs_workers]\n",
    "new_df = new_df.iloc[1:,:]\n",
    "new_df['valid strikers'] = new_df['Strikers'] - new_df['FMCS Interest']\n",
    "new_df.head()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "c8f55968-22f4-40a9-b847-7eede1b77130",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "    }\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>State</th>\n",
       "      <th>Year</th>\n",
       "      <th>Strikers</th>\n",
       "      <th>FMCS Interest</th>\n",
       "      <th>valid strikers</th>\n",
       "      <th>Priv Union Members (%)</th>\n",
       "      <th>Employed Workers</th>\n",
       "      <th>Employed Workers not on strike</th>\n",
       "      <th>prop not on strike</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>AK</td>\n",
       "      <td>1993</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>10.3</td>\n",
       "      <td>165000.0</td>\n",
       "      <td>165000.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>AK</td>\n",
       "      <td>1994</td>\n",
       "      <td>2900.0</td>\n",
       "      <td>0</td>\n",
       "      <td>2900.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>163000.0</td>\n",
       "      <td>160100.0</td>\n",
       "      <td>0.982209</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>AK</td>\n",
       "      <td>1995</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>11.4</td>\n",
       "      <td>151000.0</td>\n",
       "      <td>151000.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>AK</td>\n",
       "      <td>1996</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>12.4</td>\n",
       "      <td>165000.0</td>\n",
       "      <td>165000.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>AK</td>\n",
       "      <td>1997</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>9.6</td>\n",
       "      <td>169000.0</td>\n",
       "      <td>169000.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  State  Year Strikers FMCS Interest valid strikers  Priv Union Members (%)  \\\n",
       "1    AK  1993        0             0              0                    10.3   \n",
       "2    AK  1994   2900.0             0         2900.0                    10.0   \n",
       "3    AK  1995        0             0              0                    11.4   \n",
       "4    AK  1996        0             0              0                    12.4   \n",
       "5    AK  1997        0             0              0                     9.6   \n",
       "\n",
       "   Employed Workers Employed Workers not on strike prop not on strike  \n",
       "1          165000.0                       165000.0                1.0  \n",
       "2          163000.0                       160100.0           0.982209  \n",
       "3          151000.0                       151000.0                1.0  \n",
       "4          165000.0                       165000.0                1.0  \n",
       "5          169000.0                       169000.0                1.0  "
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "union_list = []\n",
    "emplyed_workers_list = []\n",
    "for state in lst:\n",
    "    for year in np.arange(1993,2021):\n",
    "        sub_df = union_df_priv.loc[(union_df_priv['State'] == state) & (union_df_priv['Year'] == year)]\n",
    "        if len(sub_df) > 1:\n",
    "            print(state, year)\n",
    "        if len(sub_df) == 1:\n",
    "            num = float((union_df_priv.loc[(union_df_priv['State'] == state) & (union_df_priv['Year'] == year)]['% Mem'].iloc[0])[:-1])\n",
    "            num_2 = 1000*float((union_df_priv.loc[(union_df_priv['State'] == state) & (union_df_priv['Year'] == year)]['Employment (in 1000s)'].iloc[0]).replace(\",\",\"\"))\n",
    "        if len(sub_df) == 0:\n",
    "            num = np.nan\n",
    "            num_2 = np.nan\n",
    "        union_list = union_list + [num]\n",
    "        emplyed_workers_list = emplyed_workers_list + [num_2]\n",
    "new_df['Priv Union Members (%)'] = union_list\n",
    "new_df['Employed Workers'] = emplyed_workers_list\n",
    "new_df['Employed Workers not on strike'] = new_df['Employed Workers'] - new_df['valid strikers']\n",
    "new_df['prop not on strike'] = new_df['Employed Workers not on strike']/new_df['Employed Workers']\n",
    "new_df.head()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "d181304d-361b-4467-8354-bfb0169486c2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "    }\n",
       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>State</th>\n",
       "      <th>Year</th>\n",
       "      <th>Strikers</th>\n",
       "      <th>FMCS Interest</th>\n",
       "      <th>valid strikers</th>\n",
       "      <th>Priv Union Members (%)</th>\n",
       "      <th>Employed Workers</th>\n",
       "      <th>Employed Workers not on strike</th>\n",
       "      <th>prop not on strike</th>\n",
       "      <th>prop_rep</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>AK</td>\n",
       "      <td>1993</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>10.3</td>\n",
       "      <td>165000.0</td>\n",
       "      <td>165000.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>AK</td>\n",
       "      <td>1994</td>\n",
       "      <td>2900.0</td>\n",
       "      <td>0</td>\n",
       "      <td>2900.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>163000.0</td>\n",
       "      <td>160100.0</td>\n",
       "      <td>0.982209</td>\n",
       "      <td>0.569233</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>AK</td>\n",
       "      <td>1995</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>11.4</td>\n",
       "      <td>151000.0</td>\n",
       "      <td>151000.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.569233</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>AK</td>\n",
       "      <td>1996</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>12.4</td>\n",
       "      <td>165000.0</td>\n",
       "      <td>165000.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.594069</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>AK</td>\n",
       "      <td>1997</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>9.6</td>\n",
       "      <td>169000.0</td>\n",
       "      <td>169000.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.594069</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  State  Year Strikers FMCS Interest valid strikers  Priv Union Members (%)  \\\n",
       "1    AK  1993        0             0              0                    10.3   \n",
       "2    AK  1994   2900.0             0         2900.0                    10.0   \n",
       "3    AK  1995        0             0              0                    11.4   \n",
       "4    AK  1996        0             0              0                    12.4   \n",
       "5    AK  1997        0             0              0                     9.6   \n",
       "\n",
       "   Employed Workers Employed Workers not on strike prop not on strike  \\\n",
       "1          165000.0                       165000.0                1.0   \n",
       "2          163000.0                       160100.0           0.982209   \n",
       "3          151000.0                       151000.0                1.0   \n",
       "4          165000.0                       165000.0                1.0   \n",
       "5          169000.0                       169000.0                1.0   \n",
       "\n",
       "   prop_rep  \n",
       "1       NaN  \n",
       "2  0.569233  \n",
       "3  0.569233  \n",
       "4  0.594069  \n",
       "5  0.594069  "
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "poli_list = []\n",
    "for state in lst:\n",
    "    for year in np.arange(1993,2021):\n",
    "        sub_df = full_poli_df.loc[(full_poli_df['state_po'] == state) & (full_poli_df['year'] == year)]\n",
    "        if len(sub_df) > 1:\n",
    "            print(state, year)\n",
    "        try:\n",
    "            if len(sub_df) == 1:\n",
    "                num = float((sub_df['prop_rep_votes'].iloc[0]))\n",
    "            if len(sub_df) == 0:\n",
    "                num = np.nan\n",
    "        except:\n",
    "            print(state, year)\n",
    "        poli_list = poli_list + [num]\n",
    "new_df['prop_rep'] = poli_list\n",
    "new_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "ff5ccd5c-2924-4631-9aaf-88c6ff916a62",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "    }\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>State</th>\n",
       "      <th>Year</th>\n",
       "      <th>Strikers</th>\n",
       "      <th>FMCS Interest</th>\n",
       "      <th>valid strikers</th>\n",
       "      <th>Priv Union Members (%)</th>\n",
       "      <th>Employed Workers</th>\n",
       "      <th>Employed Workers not on strike</th>\n",
       "      <th>prop not on strike</th>\n",
       "      <th>prop_rep</th>\n",
       "      <th>Min Wage</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>AK</td>\n",
       "      <td>1993</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>10.3</td>\n",
       "      <td>165000.0</td>\n",
       "      <td>165000.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>AK</td>\n",
       "      <td>1994</td>\n",
       "      <td>2900.0</td>\n",
       "      <td>0</td>\n",
       "      <td>2900.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>163000.0</td>\n",
       "      <td>160100.0</td>\n",
       "      <td>0.982209</td>\n",
       "      <td>0.569233</td>\n",
       "      <td>4.75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>AK</td>\n",
       "      <td>1995</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>11.4</td>\n",
       "      <td>151000.0</td>\n",
       "      <td>151000.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.569233</td>\n",
       "      <td>4.75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>AK</td>\n",
       "      <td>1996</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>12.4</td>\n",
       "      <td>165000.0</td>\n",
       "      <td>165000.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.594069</td>\n",
       "      <td>4.75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>AK</td>\n",
       "      <td>1997</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>9.6</td>\n",
       "      <td>169000.0</td>\n",
       "      <td>169000.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.594069</td>\n",
       "      <td>5.25</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  State  Year Strikers FMCS Interest valid strikers  Priv Union Members (%)  \\\n",
       "1    AK  1993        0             0              0                    10.3   \n",
       "2    AK  1994   2900.0             0         2900.0                    10.0   \n",
       "3    AK  1995        0             0              0                    11.4   \n",
       "4    AK  1996        0             0              0                    12.4   \n",
       "5    AK  1997        0             0              0                     9.6   \n",
       "\n",
       "   Employed Workers Employed Workers not on strike prop not on strike  \\\n",
       "1          165000.0                       165000.0                1.0   \n",
       "2          163000.0                       160100.0           0.982209   \n",
       "3          151000.0                       151000.0                1.0   \n",
       "4          165000.0                       165000.0                1.0   \n",
       "5          169000.0                       169000.0                1.0   \n",
       "\n",
       "   prop_rep  Min Wage  \n",
       "1       NaN      4.75  \n",
       "2  0.569233      4.75  \n",
       "3  0.569233      4.75  \n",
       "4  0.594069      4.75  \n",
       "5  0.594069      5.25  "
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "min_wage_list = []\n",
    "for state in lst:\n",
    "    for year in np.arange(1993,2021):\n",
    "        sub_df = min_wage_df.loc[(min_wage_df['State'] == state) & (min_wage_df['Year'] == year)]\n",
    "        if len(sub_df) > 1:\n",
    "            print(state, year)\n",
    "        try:\n",
    "            if len(sub_df) == 1:\n",
    "                num = float((sub_df['State.Minimum.Wage'].iloc[0]))\n",
    "            if len(sub_df) == 0:\n",
    "                num = np.nan\n",
    "        except:\n",
    "            print(state, year)\n",
    "        min_wage_list = min_wage_list + [num]\n",
    "new_df['Min Wage'] = min_wage_list\n",
    "new_df.head()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "503d13dd-6adb-4730-bfcb-0e37668d9b30",
   "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",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>State</th>\n",
       "      <th>Year</th>\n",
       "      <th>Strikers</th>\n",
       "      <th>FMCS Interest</th>\n",
       "      <th>valid strikers</th>\n",
       "      <th>Priv Union Members (%)</th>\n",
       "      <th>Employed Workers</th>\n",
       "      <th>Employed Workers not on strike</th>\n",
       "      <th>prop not on strike</th>\n",
       "      <th>prop_rep</th>\n",
       "      <th>Min Wage</th>\n",
       "      <th>us_inf</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>AK</td>\n",
       "      <td>1993</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>10.3</td>\n",
       "      <td>165000.0</td>\n",
       "      <td>165000.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.75</td>\n",
       "      <td>3.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>AK</td>\n",
       "      <td>1994</td>\n",
       "      <td>2900.0</td>\n",
       "      <td>0</td>\n",
       "      <td>2900.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>163000.0</td>\n",
       "      <td>160100.0</td>\n",
       "      <td>0.982209</td>\n",
       "      <td>0.569233</td>\n",
       "      <td>4.75</td>\n",
       "      <td>2.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>AK</td>\n",
       "      <td>1995</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>11.4</td>\n",
       "      <td>151000.0</td>\n",
       "      <td>151000.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.569233</td>\n",
       "      <td>4.75</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>AK</td>\n",
       "      <td>1996</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>12.4</td>\n",
       "      <td>165000.0</td>\n",
       "      <td>165000.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.594069</td>\n",
       "      <td>4.75</td>\n",
       "      <td>2.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>AK</td>\n",
       "      <td>1997</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>9.6</td>\n",
       "      <td>169000.0</td>\n",
       "      <td>169000.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.594069</td>\n",
       "      <td>5.25</td>\n",
       "      <td>2.4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  State  Year Strikers FMCS Interest valid strikers  Priv Union Members (%)  \\\n",
       "1    AK  1993        0             0              0                    10.3   \n",
       "2    AK  1994   2900.0             0         2900.0                    10.0   \n",
       "3    AK  1995        0             0              0                    11.4   \n",
       "4    AK  1996        0             0              0                    12.4   \n",
       "5    AK  1997        0             0              0                     9.6   \n",
       "\n",
       "   Employed Workers Employed Workers not on strike prop not on strike  \\\n",
       "1          165000.0                       165000.0                1.0   \n",
       "2          163000.0                       160100.0           0.982209   \n",
       "3          151000.0                       151000.0                1.0   \n",
       "4          165000.0                       165000.0                1.0   \n",
       "5          169000.0                       169000.0                1.0   \n",
       "\n",
       "   prop_rep  Min Wage  us_inf  \n",
       "1       NaN      4.75     3.3  \n",
       "2  0.569233      4.75     2.8  \n",
       "3  0.569233      4.75     3.0  \n",
       "4  0.594069      4.75     2.7  \n",
       "5  0.594069      5.25     2.4  "
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "us_inf_list = []\n",
    "for state in lst:\n",
    "    for year in np.arange(1993,2021):\n",
    "        us_inf_list = us_inf_list+ [us_inf.loc[(us_inf['Year']==year), 'Annual'].iloc[0]]\n",
    "new_df['us_inf'] =   us_inf_list\n",
    "new_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "d5f92b74-bf21-4528-94bd-3807143ac47f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\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>State</th>\n",
       "      <th>Year</th>\n",
       "      <th>Strikers</th>\n",
       "      <th>FMCS Interest</th>\n",
       "      <th>valid strikers</th>\n",
       "      <th>Priv Union Members (%)</th>\n",
       "      <th>Employed Workers</th>\n",
       "      <th>Employed Workers not on strike</th>\n",
       "      <th>prop not on strike</th>\n",
       "      <th>prop_rep</th>\n",
       "      <th>Min Wage</th>\n",
       "      <th>us_inf</th>\n",
       "      <th>state_inf</th>\n",
       "      <th>state_inf_t</th>\n",
       "      <th>state_inf_nt</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>AK</td>\n",
       "      <td>1993</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>10.3</td>\n",
       "      <td>165000.0</td>\n",
       "      <td>165000.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.75</td>\n",
       "      <td>3.3</td>\n",
       "      <td>9.708451</td>\n",
       "      <td>0.526923</td>\n",
       "      <td>16.330164</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>AK</td>\n",
       "      <td>1994</td>\n",
       "      <td>2900.0</td>\n",
       "      <td>0</td>\n",
       "      <td>2900.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>163000.0</td>\n",
       "      <td>160100.0</td>\n",
       "      <td>0.982209</td>\n",
       "      <td>0.569233</td>\n",
       "      <td>4.75</td>\n",
       "      <td>2.8</td>\n",
       "      <td>6.019952</td>\n",
       "      <td>0.004207</td>\n",
       "      <td>10.459492</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>AK</td>\n",
       "      <td>1995</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>11.4</td>\n",
       "      <td>151000.0</td>\n",
       "      <td>151000.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.569233</td>\n",
       "      <td>4.75</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.812813</td>\n",
       "      <td>6.326159</td>\n",
       "      <td>9.473906</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>AK</td>\n",
       "      <td>1996</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>12.4</td>\n",
       "      <td>165000.0</td>\n",
       "      <td>165000.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.594069</td>\n",
       "      <td>4.75</td>\n",
       "      <td>2.7</td>\n",
       "      <td>12.149973</td>\n",
       "      <td>8.822973</td>\n",
       "      <td>14.476239</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>AK</td>\n",
       "      <td>1997</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>9.6</td>\n",
       "      <td>169000.0</td>\n",
       "      <td>169000.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.594069</td>\n",
       "      <td>5.25</td>\n",
       "      <td>2.4</td>\n",
       "      <td>8.288585</td>\n",
       "      <td>2.779384</td>\n",
       "      <td>11.776124</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  State  Year Strikers FMCS Interest valid strikers  Priv Union Members (%)  \\\n",
       "1    AK  1993        0             0              0                    10.3   \n",
       "2    AK  1994   2900.0             0         2900.0                    10.0   \n",
       "3    AK  1995        0             0              0                    11.4   \n",
       "4    AK  1996        0             0              0                    12.4   \n",
       "5    AK  1997        0             0              0                     9.6   \n",
       "\n",
       "   Employed Workers Employed Workers not on strike prop not on strike  \\\n",
       "1          165000.0                       165000.0                1.0   \n",
       "2          163000.0                       160100.0           0.982209   \n",
       "3          151000.0                       151000.0                1.0   \n",
       "4          165000.0                       165000.0                1.0   \n",
       "5          169000.0                       169000.0                1.0   \n",
       "\n",
       "   prop_rep  Min Wage  us_inf  state_inf  state_inf_t  state_inf_nt  \n",
       "1       NaN      4.75     3.3   9.708451     0.526923     16.330164  \n",
       "2  0.569233      4.75     2.8   6.019952     0.004207     10.459492  \n",
       "3  0.569233      4.75     3.0   7.812813     6.326159      9.473906  \n",
       "4  0.594069      4.75     2.7  12.149973     8.822973     14.476239  \n",
       "5  0.594069      5.25     2.4   8.288585     2.779384     11.776124  "
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "state_inf_list = []\n",
    "state_inf_t_list = []\n",
    "state_inf_nt_list = []\n",
    "for state in lst:\n",
    "    for year in np.arange(1993,2021):\n",
    "        sub_df = state_inflation_df.loc[(state_inflation_df['state'] == state) & (state_inflation_df['year'] == year)]\n",
    "        if len(sub_df) > 1:\n",
    "            print(state, year)\n",
    "        try:\n",
    "            if len(sub_df) == 1:\n",
    "                num = float((sub_df['pi'].iloc[0]))\n",
    "                num_2 = float((sub_df['pi_t'].iloc[0]))\n",
    "                num_3 = float((sub_df['pi_nt'].iloc[0]))\n",
    "            if len(sub_df) == 0:\n",
    "                num, num_2, num_3 = np.nan, np.nan, np.nan\n",
    "        except:\n",
    "            print(state, year)\n",
    "        state_inf_list = state_inf_list + [num]\n",
    "        state_inf_t_list = state_inf_t_list + [num_2]\n",
    "        state_inf_nt_list = state_inf_nt_list + [num_3]\n",
    "        \n",
    "new_df['state_inf'] = state_inf_list\n",
    "new_df['state_inf_t'] = state_inf_t_list\n",
    "new_df['state_inf_nt'] = state_inf_nt_list\n",
    "\n",
    "new_df.head()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "db613d99-921b-4da5-9c12-3ecd608c6d6c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['AK', 'AL', 'AR', 'AZ', 'CA', 'CO', 'CT', 'DC', 'DE', 'FL', 'GA', 'HI',\n",
       "       'IA', 'ID', 'IL', 'IN', 'KS', 'KY', 'LA', 'MA', 'MD', 'ME', 'MI', 'MN',\n",
       "       'MO', 'MS', 'MT', 'NC', 'ND', 'NE', 'NH', 'NJ', 'NM', 'NV', 'NY', 'OH',\n",
       "       'OK', 'OR', 'PA', 'RI', 'SC', 'SD', 'TN', 'TX', 'UT', 'VA', 'VI', 'VT',\n",
       "       'WA', 'WI', 'WV', 'WY'],\n",
       "      dtype='object', name='State')"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "new_df[new_df['state_inf'].isna()].groupby('State').size().index\n",
    "#so many missing states"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "3ff0246b-1518-4bc9-aa2b-4ad60dcfd579",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>State</th>\n",
       "      <th>Year</th>\n",
       "      <th>Strikers</th>\n",
       "      <th>FMCS Interest</th>\n",
       "      <th>valid strikers</th>\n",
       "      <th>Priv Union Members (%)</th>\n",
       "      <th>Employed Workers</th>\n",
       "      <th>Employed Workers not on strike</th>\n",
       "      <th>prop not on strike</th>\n",
       "      <th>prop_rep</th>\n",
       "      <th>Min Wage</th>\n",
       "      <th>us_inf</th>\n",
       "      <th>state_inf</th>\n",
       "      <th>state_inf_t</th>\n",
       "      <th>state_inf_nt</th>\n",
       "      <th>strikers_diff</th>\n",
       "      <th>union_mem_diff</th>\n",
       "      <th>change_prop_not_on_strike</th>\n",
       "      <th>change_prop_not_on_strike_indicator</th>\n",
       "      <th>Wage_Increase_Indicator</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>AK</td>\n",
       "      <td>1993</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>10.3</td>\n",
       "      <td>165000.0</td>\n",
       "      <td>165000.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.75</td>\n",
       "      <td>3.3</td>\n",
       "      <td>9.708451</td>\n",
       "      <td>0.526923</td>\n",
       "      <td>16.330164</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>AK</td>\n",
       "      <td>1994</td>\n",
       "      <td>2900.0</td>\n",
       "      <td>0</td>\n",
       "      <td>2900.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>163000.0</td>\n",
       "      <td>160100.0</td>\n",
       "      <td>0.982209</td>\n",
       "      <td>0.569233</td>\n",
       "      <td>4.75</td>\n",
       "      <td>2.8</td>\n",
       "      <td>6.019952</td>\n",
       "      <td>0.004207</td>\n",
       "      <td>10.459492</td>\n",
       "      <td>2899.000000</td>\n",
       "      <td>-0.029126</td>\n",
       "      <td>-0.017791</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>AK</td>\n",
       "      <td>1995</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>11.4</td>\n",
       "      <td>151000.0</td>\n",
       "      <td>151000.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.569233</td>\n",
       "      <td>4.75</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.812813</td>\n",
       "      <td>6.326159</td>\n",
       "      <td>9.473906</td>\n",
       "      <td>-0.999655</td>\n",
       "      <td>0.140000</td>\n",
       "      <td>0.018114</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>AK</td>\n",
       "      <td>1996</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>12.4</td>\n",
       "      <td>165000.0</td>\n",
       "      <td>165000.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.594069</td>\n",
       "      <td>4.75</td>\n",
       "      <td>2.7</td>\n",
       "      <td>12.149973</td>\n",
       "      <td>8.822973</td>\n",
       "      <td>14.476239</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.087719</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>AK</td>\n",
       "      <td>1997</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>9.6</td>\n",
       "      <td>169000.0</td>\n",
       "      <td>169000.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.594069</td>\n",
       "      <td>5.25</td>\n",
       "      <td>2.4</td>\n",
       "      <td>8.288585</td>\n",
       "      <td>2.779384</td>\n",
       "      <td>11.776124</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.225806</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  State  Year Strikers FMCS Interest valid strikers  Priv Union Members (%)  \\\n",
       "1    AK  1993        0             0              0                    10.3   \n",
       "2    AK  1994   2900.0             0         2900.0                    10.0   \n",
       "3    AK  1995        0             0              0                    11.4   \n",
       "4    AK  1996        0             0              0                    12.4   \n",
       "5    AK  1997        0             0              0                     9.6   \n",
       "\n",
       "   Employed Workers Employed Workers not on strike prop not on strike  \\\n",
       "1          165000.0                       165000.0                1.0   \n",
       "2          163000.0                       160100.0           0.982209   \n",
       "3          151000.0                       151000.0                1.0   \n",
       "4          165000.0                       165000.0                1.0   \n",
       "5          169000.0                       169000.0                1.0   \n",
       "\n",
       "   prop_rep  Min Wage  us_inf  state_inf  state_inf_t  state_inf_nt  \\\n",
       "1       NaN      4.75     3.3   9.708451     0.526923     16.330164   \n",
       "2  0.569233      4.75     2.8   6.019952     0.004207     10.459492   \n",
       "3  0.569233      4.75     3.0   7.812813     6.326159      9.473906   \n",
       "4  0.594069      4.75     2.7  12.149973     8.822973     14.476239   \n",
       "5  0.594069      5.25     2.4   8.288585     2.779384     11.776124   \n",
       "\n",
       "   strikers_diff  union_mem_diff  change_prop_not_on_strike  \\\n",
       "1            NaN             NaN                        NaN   \n",
       "2    2899.000000       -0.029126                  -0.017791   \n",
       "3      -0.999655        0.140000                   0.018114   \n",
       "4       0.000000        0.087719                   0.000000   \n",
       "5       0.000000       -0.225806                   0.000000   \n",
       "\n",
       "   change_prop_not_on_strike_indicator  Wage_Increase_Indicator  \n",
       "1                                    0                        0  \n",
       "2                                    1                        0  \n",
       "3                                    0                        0  \n",
       "4                                    0                        0  \n",
       "5                                    0                        1  "
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "strikers_list = []\n",
    "fmcs_list = []\n",
    "union_mem_list = []\n",
    "minwages_list = []\n",
    "propworkers_list = []\n",
    "prop_strike_delta_list = []\n",
    "for state in lst:\n",
    "    sub_df = new_df[new_df['State'] == state][['Priv Union Members (%)','prop not on strike']].pct_change()\n",
    "    strikers_list = strikers_list + new_df[new_df['State'] == state]['valid strikers'].replace(0,1).pct_change().tolist()\n",
    "    union_mem_list = union_mem_list + sub_df['Priv Union Members (%)'].tolist()\n",
    "    minwages_list = minwages_list + new_df[new_df['State'] == state]['Min Wage'].diff().tolist()\n",
    "    propworkers_list = propworkers_list + sub_df['prop not on strike'].tolist()\n",
    "    \n",
    "new_df['strikers_diff'] = strikers_list\n",
    "new_df['union_mem_diff'] = union_mem_list\n",
    "new_df['change_prop_not_on_strike'] = propworkers_list\n",
    "new_df['change_prop_not_on_strike_indicator'] = ([int(x < 0) for x in propworkers_list])\n",
    "new_df['Wage_Increase_Indicator'] = ([int(x > 0) for x in minwages_list])\n",
    "new_df.head()\n",
    "# Should I clean FMCS df?\n",
    "# Yes\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "78519381-afc6-499e-942b-b2f6d6c92f2a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>State</th>\n",
       "      <th>Year</th>\n",
       "      <th>Strikers</th>\n",
       "      <th>FMCS Interest</th>\n",
       "      <th>valid strikers</th>\n",
       "      <th>Priv Union Members (%)</th>\n",
       "      <th>Employed Workers</th>\n",
       "      <th>Employed Workers not on strike</th>\n",
       "      <th>prop not on strike</th>\n",
       "      <th>prop_rep</th>\n",
       "      <th>Min Wage</th>\n",
       "      <th>us_inf</th>\n",
       "      <th>state_inf</th>\n",
       "      <th>state_inf_t</th>\n",
       "      <th>state_inf_nt</th>\n",
       "      <th>strikers_diff</th>\n",
       "      <th>union_mem_diff</th>\n",
       "      <th>change_prop_not_on_strike</th>\n",
       "      <th>change_prop_not_on_strike_indicator</th>\n",
       "      <th>Wage_Increase_Indicator</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>AL</td>\n",
       "      <td>1993</td>\n",
       "      <td>1200.0</td>\n",
       "      <td>6700</td>\n",
       "      <td>-5500.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>1381000.0</td>\n",
       "      <td>1386500.0</td>\n",
       "      <td>1.003983</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.00</td>\n",
       "      <td>3.3</td>\n",
       "      <td>10.185112</td>\n",
       "      <td>5.596229</td>\n",
       "      <td>13.388873</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>AL</td>\n",
       "      <td>1994</td>\n",
       "      <td>3200.0</td>\n",
       "      <td>2000</td>\n",
       "      <td>1200.0</td>\n",
       "      <td>9.8</td>\n",
       "      <td>1399000.0</td>\n",
       "      <td>1397800.0</td>\n",
       "      <td>0.999142</td>\n",
       "      <td>0.500832</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2.8</td>\n",
       "      <td>8.066068</td>\n",
       "      <td>4.430973</td>\n",
       "      <td>10.584267</td>\n",
       "      <td>-1.218182</td>\n",
       "      <td>-0.183333</td>\n",
       "      <td>-0.004821</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>AL</td>\n",
       "      <td>1995</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>10.2</td>\n",
       "      <td>1436000.0</td>\n",
       "      <td>1436000.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.500832</td>\n",
       "      <td>0.00</td>\n",
       "      <td>3.0</td>\n",
       "      <td>9.118135</td>\n",
       "      <td>2.915190</td>\n",
       "      <td>13.601187</td>\n",
       "      <td>-0.999167</td>\n",
       "      <td>0.040816</td>\n",
       "      <td>0.000858</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>AL</td>\n",
       "      <td>1996</td>\n",
       "      <td>1100.0</td>\n",
       "      <td>1100</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.3</td>\n",
       "      <td>1470000.0</td>\n",
       "      <td>1470000.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.534838</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2.7</td>\n",
       "      <td>13.689258</td>\n",
       "      <td>8.739596</td>\n",
       "      <td>17.238443</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.186275</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>AL</td>\n",
       "      <td>1997</td>\n",
       "      <td>1100.0</td>\n",
       "      <td>1000</td>\n",
       "      <td>100.0</td>\n",
       "      <td>7.3</td>\n",
       "      <td>1524000.0</td>\n",
       "      <td>1523900.0</td>\n",
       "      <td>0.999934</td>\n",
       "      <td>0.534838</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2.4</td>\n",
       "      <td>6.505301</td>\n",
       "      <td>3.322887</td>\n",
       "      <td>8.276711</td>\n",
       "      <td>99.000000</td>\n",
       "      <td>-0.120482</td>\n",
       "      <td>-0.000066</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1452</th>\n",
       "      <td>WY</td>\n",
       "      <td>2016</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4.7</td>\n",
       "      <td>183000.0</td>\n",
       "      <td>183000.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.603490</td>\n",
       "      <td>5.15</td>\n",
       "      <td>2.2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.078431</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1453</th>\n",
       "      <td>WY</td>\n",
       "      <td>2017</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4.4</td>\n",
       "      <td>182000.0</td>\n",
       "      <td>182000.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.603490</td>\n",
       "      <td>5.15</td>\n",
       "      <td>1.8</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.063830</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1454</th>\n",
       "      <td>WY</td>\n",
       "      <td>2018</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4.5</td>\n",
       "      <td>179000.0</td>\n",
       "      <td>179000.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.635857</td>\n",
       "      <td>5.15</td>\n",
       "      <td>2.1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.022727</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1455</th>\n",
       "      <td>WY</td>\n",
       "      <td>2019</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5.1</td>\n",
       "      <td>181000.0</td>\n",
       "      <td>181000.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.635857</td>\n",
       "      <td>5.15</td>\n",
       "      <td>2.2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.133333</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1456</th>\n",
       "      <td>WY</td>\n",
       "      <td>2020</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5.1</td>\n",
       "      <td>174000.0</td>\n",
       "      <td>174000.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.666894</td>\n",
       "      <td>5.15</td>\n",
       "      <td>1.7</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1372 rows × 20 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     State  Year Strikers FMCS Interest valid strikers  \\\n",
       "29      AL  1993   1200.0          6700        -5500.0   \n",
       "30      AL  1994   3200.0          2000         1200.0   \n",
       "31      AL  1995        0             0              0   \n",
       "32      AL  1996   1100.0          1100            0.0   \n",
       "33      AL  1997   1100.0          1000          100.0   \n",
       "...    ...   ...      ...           ...            ...   \n",
       "1452    WY  2016        0             0              0   \n",
       "1453    WY  2017        0             0              0   \n",
       "1454    WY  2018        0             0              0   \n",
       "1455    WY  2019        0             0              0   \n",
       "1456    WY  2020        0             0              0   \n",
       "\n",
       "      Priv Union Members (%)  Employed Workers Employed Workers not on strike  \\\n",
       "29                      12.0         1381000.0                      1386500.0   \n",
       "30                       9.8         1399000.0                      1397800.0   \n",
       "31                      10.2         1436000.0                      1436000.0   \n",
       "32                       8.3         1470000.0                      1470000.0   \n",
       "33                       7.3         1524000.0                      1523900.0   \n",
       "...                      ...               ...                            ...   \n",
       "1452                     4.7          183000.0                       183000.0   \n",
       "1453                     4.4          182000.0                       182000.0   \n",
       "1454                     4.5          179000.0                       179000.0   \n",
       "1455                     5.1          181000.0                       181000.0   \n",
       "1456                     5.1          174000.0                       174000.0   \n",
       "\n",
       "     prop not on strike  prop_rep  Min Wage  us_inf  state_inf  state_inf_t  \\\n",
       "29             1.003983       NaN      0.00     3.3  10.185112     5.596229   \n",
       "30             0.999142  0.500832      0.00     2.8   8.066068     4.430973   \n",
       "31                  1.0  0.500832      0.00     3.0   9.118135     2.915190   \n",
       "32                  1.0  0.534838      0.00     2.7  13.689258     8.739596   \n",
       "33             0.999934  0.534838      0.00     2.4   6.505301     3.322887   \n",
       "...                 ...       ...       ...     ...        ...          ...   \n",
       "1452                1.0  0.603490      5.15     2.2        NaN          NaN   \n",
       "1453                1.0  0.603490      5.15     1.8        NaN          NaN   \n",
       "1454                1.0  0.635857      5.15     2.1        NaN          NaN   \n",
       "1455                1.0  0.635857      5.15     2.2        NaN          NaN   \n",
       "1456                1.0  0.666894      5.15     1.7        NaN          NaN   \n",
       "\n",
       "      state_inf_nt  strikers_diff  union_mem_diff  change_prop_not_on_strike  \\\n",
       "29       13.388873            NaN             NaN                        NaN   \n",
       "30       10.584267      -1.218182       -0.183333                  -0.004821   \n",
       "31       13.601187      -0.999167        0.040816                   0.000858   \n",
       "32       17.238443       0.000000       -0.186275                   0.000000   \n",
       "33        8.276711      99.000000       -0.120482                  -0.000066   \n",
       "...            ...            ...             ...                        ...   \n",
       "1452           NaN       0.000000       -0.078431                   0.000000   \n",
       "1453           NaN       0.000000       -0.063830                   0.000000   \n",
       "1454           NaN       0.000000        0.022727                   0.000000   \n",
       "1455           NaN       0.000000        0.133333                   0.000000   \n",
       "1456           NaN       0.000000        0.000000                   0.000000   \n",
       "\n",
       "      change_prop_not_on_strike_indicator  Wage_Increase_Indicator  \n",
       "29                                      0                        0  \n",
       "30                                      1                        0  \n",
       "31                                      0                        0  \n",
       "32                                      0                        0  \n",
       "33                                      1                        0  \n",
       "...                                   ...                      ...  \n",
       "1452                                    0                        0  \n",
       "1453                                    0                        0  \n",
       "1454                                    0                        0  \n",
       "1455                                    0                        0  \n",
       "1456                                    0                        0  \n",
       "\n",
       "[1372 rows x 20 columns]"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "testing_df = new_df.copy()\n",
    "testing_df = testing_df[~testing_df['State'].isin(['AK','HI','VI'])]\n",
    "testing_df\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "624aa0e7-f1b4-4c79-900b-7f29dc2b1e32",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>State</th>\n",
       "      <th>Year</th>\n",
       "      <th>Strikers</th>\n",
       "      <th>FMCS Interest</th>\n",
       "      <th>valid strikers</th>\n",
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       "      <th>state_inf</th>\n",
       "      <th>state_inf_t</th>\n",
       "      <th>state_inf_nt</th>\n",
       "      <th>strikers_diff</th>\n",
       "      <th>union_mem_diff</th>\n",
       "      <th>change_prop_not_on_strike</th>\n",
       "      <th>change_prop_not_on_strike_indicator</th>\n",
       "      <th>Wage_Increase_Indicator</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>786</th>\n",
       "      <td>ND</td>\n",
       "      <td>1994</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>196000.0</td>\n",
       "      <td>196000.0</td>\n",
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       "      <td>0.450267</td>\n",
       "      <td>4.25</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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      "text/plain": [
       "    State  Year Strikers FMCS Interest valid strikers  Priv Union Members (%)  \\\n",
       "786    ND  1994        0             0              0                     5.0   \n",
       "\n",
       "     Employed Workers Employed Workers not on strike prop not on strike  \\\n",
       "786          196000.0                       196000.0                1.0   \n",
       "\n",
       "     prop_rep  Min Wage  us_inf  state_inf  state_inf_t  state_inf_nt  \\\n",
       "786  0.450267      4.25     2.8        NaN          NaN           NaN   \n",
       "\n",
       "     strikers_diff  union_mem_diff  change_prop_not_on_strike  \\\n",
       "786            0.0        0.162791                        0.0   \n",
       "\n",
       "     change_prop_not_on_strike_indicator  Wage_Increase_Indicator  \n",
       "786                                    0                        0  "
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sub_df_year = testing_df[testing_df['Year'] == 1994]\n",
    "distances_df.loc[distances_df['state'] == state, :]['Closest State #' + str(2)].iloc[0]\n",
    "sub_df_year[sub_df_year['State']=='ND']#['strikers_diff']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "27e5ebc2-c5b3-4890-bc91-08994bbc770b",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>State</th>\n",
       "      <th>Year</th>\n",
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       "      <th>instrument_calc</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>AL</td>\n",
       "      <td>1994</td>\n",
       "      <td>3200.0</td>\n",
       "      <td>2000</td>\n",
       "      <td>1200.0</td>\n",
       "      <td>9.8</td>\n",
       "      <td>1399000.0</td>\n",
       "      <td>1397800.0</td>\n",
       "      <td>0.999142</td>\n",
       "      <td>0.500832</td>\n",
       "      <td>...</td>\n",
       "      <td>2.8</td>\n",
       "      <td>8.066068</td>\n",
       "      <td>4.430973</td>\n",
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       "      <td>-1.218182</td>\n",
       "      <td>-0.183333</td>\n",
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       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>5.999579e+05</td>\n",
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       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>AL</td>\n",
       "      <td>1995</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>10.2</td>\n",
       "      <td>1436000.0</td>\n",
       "      <td>1436000.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.500832</td>\n",
       "      <td>...</td>\n",
       "      <td>3.0</td>\n",
       "      <td>9.118135</td>\n",
       "      <td>2.915190</td>\n",
       "      <td>13.601187</td>\n",
       "      <td>-0.999167</td>\n",
       "      <td>0.040816</td>\n",
       "      <td>0.000858</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>9.766157e+05</td>\n",
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       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>AL</td>\n",
       "      <td>1996</td>\n",
       "      <td>1100.0</td>\n",
       "      <td>1100</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.3</td>\n",
       "      <td>1470000.0</td>\n",
       "      <td>1470000.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.534838</td>\n",
       "      <td>...</td>\n",
       "      <td>2.7</td>\n",
       "      <td>13.689258</td>\n",
       "      <td>8.739596</td>\n",
       "      <td>17.238443</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.186275</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1.255837e+06</td>\n",
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       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>AL</td>\n",
       "      <td>1997</td>\n",
       "      <td>1100.0</td>\n",
       "      <td>1000</td>\n",
       "      <td>100.0</td>\n",
       "      <td>7.3</td>\n",
       "      <td>1524000.0</td>\n",
       "      <td>1523900.0</td>\n",
       "      <td>0.999934</td>\n",
       "      <td>0.534838</td>\n",
       "      <td>...</td>\n",
       "      <td>2.4</td>\n",
       "      <td>6.505301</td>\n",
       "      <td>3.322887</td>\n",
       "      <td>8.276711</td>\n",
       "      <td>99.000000</td>\n",
       "      <td>-0.120482</td>\n",
       "      <td>-0.000066</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>-1.653127e+02</td>\n",
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       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>AL</td>\n",
       "      <td>1998</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>6.2</td>\n",
       "      <td>1543000.0</td>\n",
       "      <td>1543000.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.547759</td>\n",
       "      <td>...</td>\n",
       "      <td>2.3</td>\n",
       "      <td>2.477222</td>\n",
       "      <td>-5.147837</td>\n",
       "      <td>7.581546</td>\n",
       "      <td>-0.990000</td>\n",
       "      <td>-0.150685</td>\n",
       "      <td>0.000066</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1.750401e+06</td>\n",
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       "      <td>...</td>\n",
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       "      <td>...</td>\n",
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       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>1452</th>\n",
       "      <td>WY</td>\n",
       "      <td>2016</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4.7</td>\n",
       "      <td>183000.0</td>\n",
       "      <td>183000.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.603490</td>\n",
       "      <td>...</td>\n",
       "      <td>2.2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.078431</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1453</th>\n",
       "      <td>WY</td>\n",
       "      <td>2017</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4.4</td>\n",
       "      <td>182000.0</td>\n",
       "      <td>182000.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.603490</td>\n",
       "      <td>...</td>\n",
       "      <td>1.8</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.063830</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1454</th>\n",
       "      <td>WY</td>\n",
       "      <td>2018</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4.5</td>\n",
       "      <td>179000.0</td>\n",
       "      <td>179000.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.635857</td>\n",
       "      <td>...</td>\n",
       "      <td>2.1</td>\n",
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       "      <td>0.000000</td>\n",
       "      <td>0.022727</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1.859135e+07</td>\n",
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       "    <tr>\n",
       "      <th>1455</th>\n",
       "      <td>WY</td>\n",
       "      <td>2019</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5.1</td>\n",
       "      <td>181000.0</td>\n",
       "      <td>181000.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.635857</td>\n",
       "      <td>...</td>\n",
       "      <td>2.2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.133333</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-2.768370e+02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1456</th>\n",
       "      <td>WY</td>\n",
       "      <td>2020</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5.1</td>\n",
       "      <td>174000.0</td>\n",
       "      <td>174000.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.666894</td>\n",
       "      <td>...</td>\n",
       "      <td>1.7</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-2.950298e+02</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1323 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     State  Year Strikers FMCS Interest valid strikers  \\\n",
       "30      AL  1994   3200.0          2000         1200.0   \n",
       "31      AL  1995        0             0              0   \n",
       "32      AL  1996   1100.0          1100            0.0   \n",
       "33      AL  1997   1100.0          1000          100.0   \n",
       "34      AL  1998        0             0              0   \n",
       "...    ...   ...      ...           ...            ...   \n",
       "1452    WY  2016        0             0              0   \n",
       "1453    WY  2017        0             0              0   \n",
       "1454    WY  2018        0             0              0   \n",
       "1455    WY  2019        0             0              0   \n",
       "1456    WY  2020        0             0              0   \n",
       "\n",
       "      Priv Union Members (%)  Employed Workers Employed Workers not on strike  \\\n",
       "30                       9.8         1399000.0                      1397800.0   \n",
       "31                      10.2         1436000.0                      1436000.0   \n",
       "32                       8.3         1470000.0                      1470000.0   \n",
       "33                       7.3         1524000.0                      1523900.0   \n",
       "34                       6.2         1543000.0                      1543000.0   \n",
       "...                      ...               ...                            ...   \n",
       "1452                     4.7          183000.0                       183000.0   \n",
       "1453                     4.4          182000.0                       182000.0   \n",
       "1454                     4.5          179000.0                       179000.0   \n",
       "1455                     5.1          181000.0                       181000.0   \n",
       "1456                     5.1          174000.0                       174000.0   \n",
       "\n",
       "     prop not on strike  prop_rep  ...  us_inf  state_inf  state_inf_t  \\\n",
       "30             0.999142  0.500832  ...     2.8   8.066068     4.430973   \n",
       "31                  1.0  0.500832  ...     3.0   9.118135     2.915190   \n",
       "32                  1.0  0.534838  ...     2.7  13.689258     8.739596   \n",
       "33             0.999934  0.534838  ...     2.4   6.505301     3.322887   \n",
       "34                  1.0  0.547759  ...     2.3   2.477222    -5.147837   \n",
       "...                 ...       ...  ...     ...        ...          ...   \n",
       "1452                1.0  0.603490  ...     2.2        NaN          NaN   \n",
       "1453                1.0  0.603490  ...     1.8        NaN          NaN   \n",
       "1454                1.0  0.635857  ...     2.1        NaN          NaN   \n",
       "1455                1.0  0.635857  ...     2.2        NaN          NaN   \n",
       "1456                1.0  0.666894  ...     1.7        NaN          NaN   \n",
       "\n",
       "      state_inf_nt  strikers_diff  union_mem_diff  change_prop_not_on_strike  \\\n",
       "30       10.584267      -1.218182       -0.183333                  -0.004821   \n",
       "31       13.601187      -0.999167        0.040816                   0.000858   \n",
       "32       17.238443       0.000000       -0.186275                   0.000000   \n",
       "33        8.276711      99.000000       -0.120482                  -0.000066   \n",
       "34        7.581546      -0.990000       -0.150685                   0.000066   \n",
       "...            ...            ...             ...                        ...   \n",
       "1452           NaN       0.000000       -0.078431                   0.000000   \n",
       "1453           NaN       0.000000       -0.063830                   0.000000   \n",
       "1454           NaN       0.000000        0.022727                   0.000000   \n",
       "1455           NaN       0.000000        0.133333                   0.000000   \n",
       "1456           NaN       0.000000        0.000000                   0.000000   \n",
       "\n",
       "      change_prop_not_on_strike_indicator  Wage_Increase_Indicator  \\\n",
       "30                                      1                        0   \n",
       "31                                      0                        0   \n",
       "32                                      0                        0   \n",
       "33                                      1                        0   \n",
       "34                                      0                        0   \n",
       "...                                   ...                      ...   \n",
       "1452                                    0                        0   \n",
       "1453                                    0                        0   \n",
       "1454                                    0                        0   \n",
       "1455                                    0                        0   \n",
       "1456                                    0                        0   \n",
       "\n",
       "      instrument_calc  \n",
       "30       5.999579e+05  \n",
       "31       9.766157e+05  \n",
       "32       1.255837e+06  \n",
       "33      -1.653127e+02  \n",
       "34       1.750401e+06  \n",
       "...               ...  \n",
       "1452     0.000000e+00  \n",
       "1453     0.000000e+00  \n",
       "1454     1.859135e+07  \n",
       "1455    -2.768370e+02  \n",
       "1456    -2.950298e+02  \n",
       "\n",
       "[1323 rows x 21 columns]"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_states = testing_df['State'].unique().tolist()\n",
    "testing_df['instrument_calc'] = np.nan\n",
    "for year in np.arange(1994,2021):\n",
    "    sub_df_year = testing_df[testing_df['Year'] == year]\n",
    "    for state in all_states:\n",
    "        sub_df_state = distances_df.loc[distances_df['state'] == state, :]\n",
    "        instrument_calc = 0\n",
    "        for i in range(5):\n",
    "            closest_state_i = sub_df_state['Closest State #' + str(i + 1)].iloc[0]\n",
    "            dist_to_closest_state_i = sub_df_state['Distance to Closest State #' + str(i + 1)].iloc[0]\n",
    "            try:\n",
    "                instrument_calc += dist_to_closest_state_i*sub_df_year[sub_df_year['State']==closest_state_i]['strikers_diff'].iloc[0]\n",
    "            except:\n",
    "                print(state, year)\n",
    "        testing_df.loc[(testing_df['State'] == state) & (testing_df['Year'] == year),'instrument_calc'] = instrument_calc\n",
    "testing_df = testing_df[testing_df['Year'] > 1993]\n",
    "testing_df\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "7aec5cfe-f596-47bf-aae5-252b0275c1e0",
   "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>State</th>\n",
       "      <th>Year</th>\n",
       "      <th>Strikers</th>\n",
       "      <th>FMCS Interest</th>\n",
       "      <th>valid strikers</th>\n",
       "      <th>Priv Union Members (%)</th>\n",
       "      <th>Employed Workers</th>\n",
       "      <th>Employed Workers not on strike</th>\n",
       "      <th>prop not on strike</th>\n",
       "      <th>prop_rep</th>\n",
       "      <th>...</th>\n",
       "      <th>us_inf</th>\n",
       "      <th>state_inf</th>\n",
       "      <th>state_inf_t</th>\n",
       "      <th>state_inf_nt</th>\n",
       "      <th>strikers_diff</th>\n",
       "      <th>union_mem_diff</th>\n",
       "      <th>change_prop_not_on_strike</th>\n",
       "      <th>change_prop_not_on_strike_indicator</th>\n",
       "      <th>Wage_Increase_Indicator</th>\n",
       "      <th>instrument_calc</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>58</th>\n",
       "      <td>AR</td>\n",
       "      <td>1994</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>6.6</td>\n",
       "      <td>815000.0</td>\n",
       "      <td>815000.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.525928</td>\n",
       "      <td>...</td>\n",
       "      <td>2.8</td>\n",
       "      <td>9.261872</td>\n",
       "      <td>8.117365</td>\n",
       "      <td>9.712796</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.120000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1.811185e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>AR</td>\n",
       "      <td>1995</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>6.5</td>\n",
       "      <td>837000.0</td>\n",
       "      <td>837000.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.525928</td>\n",
       "      <td>...</td>\n",
       "      <td>3.0</td>\n",
       "      <td>8.460396</td>\n",
       "      <td>4.543085</td>\n",
       "      <td>11.004751</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.015152</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>7.942910e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60</th>\n",
       "      <td>AR</td>\n",
       "      <td>1996</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5.7</td>\n",
       "      <td>882000.0</td>\n",
       "      <td>882000.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.528233</td>\n",
       "      <td>...</td>\n",
       "      <td>2.7</td>\n",
       "      <td>11.403650</td>\n",
       "      <td>5.368576</td>\n",
       "      <td>15.706264</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.123077</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1.656710e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61</th>\n",
       "      <td>AR</td>\n",
       "      <td>1997</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4.5</td>\n",
       "      <td>836000.0</td>\n",
       "      <td>836000.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.528233</td>\n",
       "      <td>...</td>\n",
       "      <td>2.4</td>\n",
       "      <td>9.892886</td>\n",
       "      <td>-2.294520</td>\n",
       "      <td>18.751516</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.210526</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4.130359e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>AR</td>\n",
       "      <td>1998</td>\n",
       "      <td>1200.0</td>\n",
       "      <td>1200</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.5</td>\n",
       "      <td>827000.0</td>\n",
       "      <td>827000.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.608904</td>\n",
       "      <td>...</td>\n",
       "      <td>2.3</td>\n",
       "      <td>-0.291438</td>\n",
       "      <td>-6.662638</td>\n",
       "      <td>5.208307</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1.284137e+06</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>1424</th>\n",
       "      <td>SD</td>\n",
       "      <td>2016</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2.5</td>\n",
       "      <td>316000.0</td>\n",
       "      <td>316000.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.641028</td>\n",
       "      <td>...</td>\n",
       "      <td>2.2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.038462</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>8.751774e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1425</th>\n",
       "      <td>SD</td>\n",
       "      <td>2017</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2.5</td>\n",
       "      <td>315000.0</td>\n",
       "      <td>315000.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.641028</td>\n",
       "      <td>...</td>\n",
       "      <td>1.8</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>-3.146988e+02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1426</th>\n",
       "      <td>SD</td>\n",
       "      <td>2018</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>327000.0</td>\n",
       "      <td>327000.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.603468</td>\n",
       "      <td>...</td>\n",
       "      <td>2.1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.200000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1427</th>\n",
       "      <td>SD</td>\n",
       "      <td>2019</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2.6</td>\n",
       "      <td>333000.0</td>\n",
       "      <td>333000.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.603468</td>\n",
       "      <td>...</td>\n",
       "      <td>2.2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.133333</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1428</th>\n",
       "      <td>SD</td>\n",
       "      <td>2020</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2.7</td>\n",
       "      <td>327000.0</td>\n",
       "      <td>327000.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.809550</td>\n",
       "      <td>...</td>\n",
       "      <td>1.7</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.038462</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1.133008e+06</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>891 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     State  Year Strikers FMCS Interest valid strikers  \\\n",
       "58      AR  1994        0             0              0   \n",
       "59      AR  1995        0             0              0   \n",
       "60      AR  1996        0             0              0   \n",
       "61      AR  1997        0             0              0   \n",
       "62      AR  1998   1200.0          1200            0.0   \n",
       "...    ...   ...      ...           ...            ...   \n",
       "1424    SD  2016        0             0              0   \n",
       "1425    SD  2017        0             0              0   \n",
       "1426    SD  2018        0             0              0   \n",
       "1427    SD  2019        0             0              0   \n",
       "1428    SD  2020        0             0              0   \n",
       "\n",
       "      Priv Union Members (%)  Employed Workers Employed Workers not on strike  \\\n",
       "58                       6.6          815000.0                       815000.0   \n",
       "59                       6.5          837000.0                       837000.0   \n",
       "60                       5.7          882000.0                       882000.0   \n",
       "61                       4.5          836000.0                       836000.0   \n",
       "62                       4.5          827000.0                       827000.0   \n",
       "...                      ...               ...                            ...   \n",
       "1424                     2.5          316000.0                       316000.0   \n",
       "1425                     2.5          315000.0                       315000.0   \n",
       "1426                     3.0          327000.0                       327000.0   \n",
       "1427                     2.6          333000.0                       333000.0   \n",
       "1428                     2.7          327000.0                       327000.0   \n",
       "\n",
       "     prop not on strike  prop_rep  ...  us_inf  state_inf  state_inf_t  \\\n",
       "58                  1.0  0.525928  ...     2.8   9.261872     8.117365   \n",
       "59                  1.0  0.525928  ...     3.0   8.460396     4.543085   \n",
       "60                  1.0  0.528233  ...     2.7  11.403650     5.368576   \n",
       "61                  1.0  0.528233  ...     2.4   9.892886    -2.294520   \n",
       "62                  1.0  0.608904  ...     2.3  -0.291438    -6.662638   \n",
       "...                 ...       ...  ...     ...        ...          ...   \n",
       "1424                1.0  0.641028  ...     2.2        NaN          NaN   \n",
       "1425                1.0  0.641028  ...     1.8        NaN          NaN   \n",
       "1426                1.0  0.603468  ...     2.1        NaN          NaN   \n",
       "1427                1.0  0.603468  ...     2.2        NaN          NaN   \n",
       "1428                1.0  0.809550  ...     1.7        NaN          NaN   \n",
       "\n",
       "      state_inf_nt  strikers_diff  union_mem_diff  change_prop_not_on_strike  \\\n",
       "58        9.712796            0.0       -0.120000                        0.0   \n",
       "59       11.004751            0.0       -0.015152                        0.0   \n",
       "60       15.706264            0.0       -0.123077                        0.0   \n",
       "61       18.751516            0.0       -0.210526                        0.0   \n",
       "62        5.208307            0.0        0.000000                        0.0   \n",
       "...            ...            ...             ...                        ...   \n",
       "1424           NaN            0.0       -0.038462                        0.0   \n",
       "1425           NaN            0.0        0.000000                        0.0   \n",
       "1426           NaN            0.0        0.200000                        0.0   \n",
       "1427           NaN            0.0       -0.133333                        0.0   \n",
       "1428           NaN            0.0        0.038462                        0.0   \n",
       "\n",
       "      change_prop_not_on_strike_indicator  Wage_Increase_Indicator  \\\n",
       "58                                      0                        1   \n",
       "59                                      0                        0   \n",
       "60                                      0                        0   \n",
       "61                                      0                        0   \n",
       "62                                      0                        1   \n",
       "...                                   ...                      ...   \n",
       "1424                                    0                        1   \n",
       "1425                                    0                        1   \n",
       "1426                                    0                        1   \n",
       "1427                                    0                        1   \n",
       "1428                                    0                        0   \n",
       "\n",
       "      instrument_calc  \n",
       "58       1.811185e+06  \n",
       "59       7.942910e+05  \n",
       "60       1.656710e+06  \n",
       "61       4.130359e+06  \n",
       "62       1.284137e+06  \n",
       "...               ...  \n",
       "1424     8.751774e+05  \n",
       "1425    -3.146988e+02  \n",
       "1426     0.000000e+00  \n",
       "1427     0.000000e+00  \n",
       "1428     1.133008e+06  \n",
       "\n",
       "[891 rows x 21 columns]"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "testing_df = testing_df[testing_df['State'].isin(min_wage_df[min_wage_df['Effective.Minimum.Wage'] > min_wage_df['Federal.Minimum.Wage']]['State'].unique().tolist())]\n",
    "testing_df\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "2191a1e8-dfa8-4bc0-bf49-0d047b0ef3b5",
   "metadata": {},
   "outputs": [],
   "source": [
    "testing_df['prop_rep'] = testing_df['prop_rep']*100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "671fe398-b256-4ce9-89a1-670172eddf90",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['AR', 'AZ', 'CA', 'CO', 'CT', 'DC', 'DE', 'FL', 'IA', 'IL', 'MA', 'MD',\n",
       "       'ME', 'MI', 'MN', 'MO', 'MT', 'NC', 'NE', 'NH', 'NJ', 'NM', 'NV', 'NY',\n",
       "       'OH', 'OR', 'PA', 'RI', 'SD', 'VT', 'WA', 'WI', 'WV'],\n",
       "      dtype='object', name='State')"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "index_2 = testing_df[testing_df['Wage_Increase_Indicator']>0].groupby('State').size().index\n",
    "index_2\n",
    "\n",
    "# 45 states have atleast 1 min wage increase\n",
    "# 16 of them don't have info on state inflation \n",
    "# Run 2 regressions\n",
    "\n",
    "# Acc run 3, to also account for DC not having poli_lean \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "caa7338e-3560-496d-b6c9-257a58cdfbae",
   "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>State</th>\n",
       "      <th>Year</th>\n",
       "      <th>strikers_diff</th>\n",
       "      <th>Priv Union Members (%)</th>\n",
       "      <th>prop_rep</th>\n",
       "      <th>Wage_Increase_Indicator</th>\n",
       "      <th>change_prop_not_on_strike</th>\n",
       "      <th>change_prop_not_on_strike_indicator</th>\n",
       "      <th>instrument_calc</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>58</th>\n",
       "      <td>AR</td>\n",
       "      <td>1994</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.6</td>\n",
       "      <td>52.592763</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1.811185e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>AR</td>\n",
       "      <td>1995</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.5</td>\n",
       "      <td>52.592763</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>7.942910e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60</th>\n",
       "      <td>AR</td>\n",
       "      <td>1996</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.7</td>\n",
       "      <td>52.823293</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1.656710e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61</th>\n",
       "      <td>AR</td>\n",
       "      <td>1997</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.5</td>\n",
       "      <td>52.823293</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>4.130359e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>AR</td>\n",
       "      <td>1998</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.5</td>\n",
       "      <td>60.890447</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1.284137e+06</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1424</th>\n",
       "      <td>SD</td>\n",
       "      <td>2016</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.5</td>\n",
       "      <td>64.102786</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>8.751774e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1425</th>\n",
       "      <td>SD</td>\n",
       "      <td>2017</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.5</td>\n",
       "      <td>64.102786</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>-3.146988e+02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1426</th>\n",
       "      <td>SD</td>\n",
       "      <td>2018</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>60.346796</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1427</th>\n",
       "      <td>SD</td>\n",
       "      <td>2019</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.6</td>\n",
       "      <td>60.346796</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1428</th>\n",
       "      <td>SD</td>\n",
       "      <td>2020</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.7</td>\n",
       "      <td>80.955015</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1.133008e+06</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>891 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     State  Year  strikers_diff  Priv Union Members (%)   prop_rep  \\\n",
       "58      AR  1994            0.0                     6.6  52.592763   \n",
       "59      AR  1995            0.0                     6.5  52.592763   \n",
       "60      AR  1996            0.0                     5.7  52.823293   \n",
       "61      AR  1997            0.0                     4.5  52.823293   \n",
       "62      AR  1998            0.0                     4.5  60.890447   \n",
       "...    ...   ...            ...                     ...        ...   \n",
       "1424    SD  2016            0.0                     2.5  64.102786   \n",
       "1425    SD  2017            0.0                     2.5  64.102786   \n",
       "1426    SD  2018            0.0                     3.0  60.346796   \n",
       "1427    SD  2019            0.0                     2.6  60.346796   \n",
       "1428    SD  2020            0.0                     2.7  80.955015   \n",
       "\n",
       "      Wage_Increase_Indicator  change_prop_not_on_strike  \\\n",
       "58                          1                        0.0   \n",
       "59                          0                        0.0   \n",
       "60                          0                        0.0   \n",
       "61                          0                        0.0   \n",
       "62                          1                        0.0   \n",
       "...                       ...                        ...   \n",
       "1424                        1                        0.0   \n",
       "1425                        1                        0.0   \n",
       "1426                        1                        0.0   \n",
       "1427                        1                        0.0   \n",
       "1428                        0                        0.0   \n",
       "\n",
       "      change_prop_not_on_strike_indicator  instrument_calc  \n",
       "58                                      0     1.811185e+06  \n",
       "59                                      0     7.942910e+05  \n",
       "60                                      0     1.656710e+06  \n",
       "61                                      0     4.130359e+06  \n",
       "62                                      0     1.284137e+06  \n",
       "...                                   ...              ...  \n",
       "1424                                    0     8.751774e+05  \n",
       "1425                                    0    -3.146988e+02  \n",
       "1426                                    0     0.000000e+00  \n",
       "1427                                    0     0.000000e+00  \n",
       "1428                                    0     1.133008e+06  \n",
       "\n",
       "[891 rows x 9 columns]"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "testing_df[['State','Year','strikers_diff','Priv Union Members (%)','prop_rep','Wage_Increase_Indicator','change_prop_not_on_strike','change_prop_not_on_strike_indicator','instrument_calc']]\n",
    "# Change in proportion of private sector workers not on strike is very small\n",
    "# Weak instrument, it is what it is\n",
    "# Instead, take whether or not there is a change as your instrument\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "e3db578e-a9cd-4620-be99-d3d7ce2982f6",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_1 = testing_df[['State','Year','strikers_diff','Priv Union Members (%)','state_inf','state_inf_t','state_inf_nt','prop_rep','Wage_Increase_Indicator','change_prop_not_on_strike','change_prop_not_on_strike_indicator','instrument_calc','us_inf']]\n",
    "df_1 = df_1[df_1['State'].isin(index_2.tolist())]\n",
    "df_1 = df_1[~df_1['state_inf'].isna()]\n",
    "df_1 = df_1[~df_1['prop_rep'].isna()]\n",
    "df_1 = pd.concat([df_1, pd.get_dummies(df_1['Year']).drop(columns=[1994])],axis=1)\n",
    "df_1.columns = [x for x in df_1.columns.tolist() if type(x)!=int] + ['yr'+str(x) for x in df_1.columns.tolist() if type(x)==int]\n",
    "df_1\n",
    "#All states with inflation data, 1994-2017\n",
    "\n",
    "df_1[['Priv Union Members (%)','state_inf','prop_rep','change_prop_not_on_strike_indicator',\n",
    "      'Wage_Increase_Indicator','instrument_calc']].to_csv(\"all_states_w_inflation.csv\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "b4bca08e-0914-4eed-9534-4895651901f0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "456"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(df_1['state_inf'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "aa6ab33b-12f7-45b0-bcb5-28ea3a6542cc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "8.874986323857703"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "((df_1['state_inf']/100+1).prod()**(1/len(df_1['state_inf']))-1)*100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "95073f0f-c9d1-464a-8e7a-227b16921206",
   "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>Priv Union Members (%)</th>\n",
       "      <th>state_inf</th>\n",
       "      <th>prop_rep</th>\n",
       "      <th>change_prop_not_on_strike_indicator</th>\n",
       "      <th>Wage_Increase_Indicator</th>\n",
       "      <th>instrument_calc</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>456.000000</td>\n",
       "      <td>456.000000</td>\n",
       "      <td>456.000000</td>\n",
       "      <td>456.000000</td>\n",
       "      <td>456.000000</td>\n",
       "      <td>4.560000e+02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>9.114254</td>\n",
       "      <td>8.985010</td>\n",
       "      <td>45.082164</td>\n",
       "      <td>0.280702</td>\n",
       "      <td>0.375000</td>\n",
       "      <td>2.801256e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>3.910835</td>\n",
       "      <td>4.880890</td>\n",
       "      <td>10.001281</td>\n",
       "      <td>0.449836</td>\n",
       "      <td>0.484655</td>\n",
       "      <td>1.303664e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.200000</td>\n",
       "      <td>-9.742371</td>\n",
       "      <td>8.848690</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-1.693096e+03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>6.900000</td>\n",
       "      <td>6.408922</td>\n",
       "      <td>41.367813</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-1.418277e+02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>9.100000</td>\n",
       "      <td>9.098480</td>\n",
       "      <td>46.318302</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.233087e+02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>11.700000</td>\n",
       "      <td>11.996805</td>\n",
       "      <td>51.105978</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>6.206984e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>18.400000</td>\n",
       "      <td>27.903131</td>\n",
       "      <td>71.161461</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.607391e+08</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Priv Union Members (%)   state_inf    prop_rep  \\\n",
       "count              456.000000  456.000000  456.000000   \n",
       "mean                 9.114254    8.985010   45.082164   \n",
       "std                  3.910835    4.880890   10.001281   \n",
       "min                  1.200000   -9.742371    8.848690   \n",
       "25%                  6.900000    6.408922   41.367813   \n",
       "50%                  9.100000    9.098480   46.318302   \n",
       "75%                 11.700000   11.996805   51.105978   \n",
       "max                 18.400000   27.903131   71.161461   \n",
       "\n",
       "       change_prop_not_on_strike_indicator  Wage_Increase_Indicator  \\\n",
       "count                           456.000000               456.000000   \n",
       "mean                              0.280702                 0.375000   \n",
       "std                               0.449836                 0.484655   \n",
       "min                               0.000000                 0.000000   \n",
       "25%                               0.000000                 0.000000   \n",
       "50%                               0.000000                 0.000000   \n",
       "75%                               1.000000                 1.000000   \n",
       "max                               1.000000                 1.000000   \n",
       "\n",
       "       instrument_calc  \n",
       "count     4.560000e+02  \n",
       "mean      2.801256e+06  \n",
       "std       1.303664e+07  \n",
       "min      -1.693096e+03  \n",
       "25%      -1.418277e+02  \n",
       "50%       3.233087e+02  \n",
       "75%       6.206984e+05  \n",
       "max       1.607391e+08  "
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_1.describe()[['Priv Union Members (%)','state_inf','prop_rep','change_prop_not_on_strike_indicator','Wage_Increase_Indicator','instrument_calc']]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "b3aab876-f472-44ca-8a61-900659829d72",
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   "outputs": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>strikers_diff</th>\n",
       "      <th>Priv Union Members (%)</th>\n",
       "      <th>state_inf</th>\n",
       "      <th>state_inf_t</th>\n",
       "      <th>state_inf_nt</th>\n",
       "      <th>prop_rep</th>\n",
       "      <th>Wage_Increase_Indicator</th>\n",
       "      <th>change_prop_not_on_strike</th>\n",
       "      <th>change_prop_not_on_strike_indicator</th>\n",
       "      <th>instrument_calc</th>\n",
       "      <th>...</th>\n",
       "      <th>yr2008</th>\n",
       "      <th>yr2009</th>\n",
       "      <th>yr2010</th>\n",
       "      <th>yr2011</th>\n",
       "      <th>yr2012</th>\n",
       "      <th>yr2013</th>\n",
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       "      <th>yr2015</th>\n",
       "      <th>yr2016</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>strikers_diff</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.154183</td>\n",
       "      <td>0.283765</td>\n",
       "      <td>0.690667</td>\n",
       "      <td>0.040011</td>\n",
       "      <td>-0.128816</td>\n",
       "      <td>0.260445</td>\n",
       "      <td>0.687359</td>\n",
       "      <td>-0.284422</td>\n",
       "      <td>0.127987</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>Priv Union Members (%)</th>\n",
       "      <td>-0.154183</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.270695</td>\n",
       "      <td>-0.035479</td>\n",
       "      <td>0.178884</td>\n",
       "      <td>-0.318064</td>\n",
       "      <td>0.139784</td>\n",
       "      <td>-0.281236</td>\n",
       "      <td>0.721259</td>\n",
       "      <td>0.234832</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>state_inf</th>\n",
       "      <td>0.283765</td>\n",
       "      <td>0.270695</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.688964</td>\n",
       "      <td>0.887592</td>\n",
       "      <td>-0.032799</td>\n",
       "      <td>0.382842</td>\n",
       "      <td>0.104800</td>\n",
       "      <td>0.174437</td>\n",
       "      <td>0.484394</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>state_inf_t</th>\n",
       "      <td>0.690667</td>\n",
       "      <td>-0.035479</td>\n",
       "      <td>0.688964</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.411220</td>\n",
       "      <td>-0.161151</td>\n",
       "      <td>0.539590</td>\n",
       "      <td>0.522675</td>\n",
       "      <td>-0.097559</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>state_inf_nt</th>\n",
       "      <td>0.040011</td>\n",
       "      <td>0.178884</td>\n",
       "      <td>0.887592</td>\n",
       "      <td>0.411220</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.097719</td>\n",
       "      <td>0.354825</td>\n",
       "      <td>-0.074772</td>\n",
       "      <td>0.100773</td>\n",
       "      <td>0.351747</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>prop_rep</th>\n",
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       "      <td>-0.161151</td>\n",
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       "      <td>1.000000</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wage_Increase_Indicator</th>\n",
       "      <td>0.260445</td>\n",
       "      <td>0.139784</td>\n",
       "      <td>0.382842</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>change_prop_not_on_strike</th>\n",
       "      <td>0.687359</td>\n",
       "      <td>-0.281236</td>\n",
       "      <td>0.104800</td>\n",
       "      <td>0.522675</td>\n",
       "      <td>-0.074772</td>\n",
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       "      <td>1.000000</td>\n",
       "      <td>-0.347962</td>\n",
       "      <td>0.185929</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>change_prop_not_on_strike_indicator</th>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>instrument_calc</th>\n",
       "      <td>0.127987</td>\n",
       "      <td>0.234832</td>\n",
       "      <td>0.484394</td>\n",
       "      <td>0.487353</td>\n",
       "      <td>0.351747</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>us_inf</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>yr1995</th>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>yr1996</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>yr2001</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>yr2002</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>yr2005</th>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>yr2006</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>yr2007</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>yr2008</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>yr2009</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>yr2010</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>yr2011</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>yr2012</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>yr2013</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>yr2014</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>yr2015</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>yr2016</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>yr2017</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>34 rows × 34 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                     strikers_diff  Priv Union Members (%)  \\\n",
       "strikers_diff                             1.000000               -0.154183   \n",
       "Priv Union Members (%)                   -0.154183                1.000000   \n",
       "state_inf                                 0.283765                0.270695   \n",
       "state_inf_t                               0.690667               -0.035479   \n",
       "state_inf_nt                              0.040011                0.178884   \n",
       "prop_rep                                 -0.128816               -0.318064   \n",
       "Wage_Increase_Indicator                   0.260445                0.139784   \n",
       "change_prop_not_on_strike                 0.687359               -0.281236   \n",
       "change_prop_not_on_strike_indicator      -0.284422                0.721259   \n",
       "instrument_calc                           0.127987                0.234832   \n",
       "us_inf                                         NaN                     NaN   \n",
       "yr1995                                         NaN                     NaN   \n",
       "yr1996                                         NaN                     NaN   \n",
       "yr1997                                         NaN                     NaN   \n",
       "yr1998                                         NaN                     NaN   \n",
       "yr1999                                         NaN                     NaN   \n",
       "yr2000                                         NaN                     NaN   \n",
       "yr2001                                         NaN                     NaN   \n",
       "yr2002                                         NaN                     NaN   \n",
       "yr2003                                         NaN                     NaN   \n",
       "yr2004                                         NaN                     NaN   \n",
       "yr2005                                         NaN                     NaN   \n",
       "yr2006                                         NaN                     NaN   \n",
       "yr2007                                         NaN                     NaN   \n",
       "yr2008                                         NaN                     NaN   \n",
       "yr2009                                         NaN                     NaN   \n",
       "yr2010                                         NaN                     NaN   \n",
       "yr2011                                         NaN                     NaN   \n",
       "yr2012                                         NaN                     NaN   \n",
       "yr2013                                         NaN                     NaN   \n",
       "yr2014                                         NaN                     NaN   \n",
       "yr2015                                         NaN                     NaN   \n",
       "yr2016                                         NaN                     NaN   \n",
       "yr2017                                         NaN                     NaN   \n",
       "\n",
       "                                     state_inf  state_inf_t  state_inf_nt  \\\n",
       "strikers_diff                         0.283765     0.690667      0.040011   \n",
       "Priv Union Members (%)                0.270695    -0.035479      0.178884   \n",
       "state_inf                             1.000000     0.688964      0.887592   \n",
       "state_inf_t                           0.688964     1.000000      0.411220   \n",
       "state_inf_nt                          0.887592     0.411220      1.000000   \n",
       "prop_rep                             -0.032799    -0.161151      0.097719   \n",
       "Wage_Increase_Indicator               0.382842     0.539590      0.354825   \n",
       "change_prop_not_on_strike             0.104800     0.522675     -0.074772   \n",
       "change_prop_not_on_strike_indicator   0.174437    -0.097559      0.100773   \n",
       "instrument_calc                       0.484394     0.487353      0.351747   \n",
       "us_inf                                     NaN          NaN           NaN   \n",
       "yr1995                                     NaN          NaN           NaN   \n",
       "yr1996                                     NaN          NaN           NaN   \n",
       "yr1997                                     NaN          NaN           NaN   \n",
       "yr1998                                     NaN          NaN           NaN   \n",
       "yr1999                                     NaN          NaN           NaN   \n",
       "yr2000                                     NaN          NaN           NaN   \n",
       "yr2001                                     NaN          NaN           NaN   \n",
       "yr2002                                     NaN          NaN           NaN   \n",
       "yr2003                                     NaN          NaN           NaN   \n",
       "yr2004                                     NaN          NaN           NaN   \n",
       "yr2005                                     NaN          NaN           NaN   \n",
       "yr2006                                     NaN          NaN           NaN   \n",
       "yr2007                                     NaN          NaN           NaN   \n",
       "yr2008                                     NaN          NaN           NaN   \n",
       "yr2009                                     NaN          NaN           NaN   \n",
       "yr2010                                     NaN          NaN           NaN   \n",
       "yr2011                                     NaN          NaN           NaN   \n",
       "yr2012                                     NaN          NaN           NaN   \n",
       "yr2013                                     NaN          NaN           NaN   \n",
       "yr2014                                     NaN          NaN           NaN   \n",
       "yr2015                                     NaN          NaN           NaN   \n",
       "yr2016                                     NaN          NaN           NaN   \n",
       "yr2017                                     NaN          NaN           NaN   \n",
       "\n",
       "                                     prop_rep  Wage_Increase_Indicator  \\\n",
       "strikers_diff                       -0.128816                 0.260445   \n",
       "Priv Union Members (%)              -0.318064                 0.139784   \n",
       "state_inf                           -0.032799                 0.382842   \n",
       "state_inf_t                         -0.161151                 0.539590   \n",
       "state_inf_nt                         0.097719                 0.354825   \n",
       "prop_rep                             1.000000                -0.220108   \n",
       "Wage_Increase_Indicator             -0.220108                 1.000000   \n",
       "change_prop_not_on_strike            0.093953                 0.101174   \n",
       "change_prop_not_on_strike_indicator -0.169498                 0.099478   \n",
       "instrument_calc                     -0.137249                 0.591030   \n",
       "us_inf                                    NaN                      NaN   \n",
       "yr1995                                    NaN                      NaN   \n",
       "yr1996                                    NaN                      NaN   \n",
       "yr1997                                    NaN                      NaN   \n",
       "yr1998                                    NaN                      NaN   \n",
       "yr1999                                    NaN                      NaN   \n",
       "yr2000                                    NaN                      NaN   \n",
       "yr2001                                    NaN                      NaN   \n",
       "yr2002                                    NaN                      NaN   \n",
       "yr2003                                    NaN                      NaN   \n",
       "yr2004                                    NaN                      NaN   \n",
       "yr2005                                    NaN                      NaN   \n",
       "yr2006                                    NaN                      NaN   \n",
       "yr2007                                    NaN                      NaN   \n",
       "yr2008                                    NaN                      NaN   \n",
       "yr2009                                    NaN                      NaN   \n",
       "yr2010                                    NaN                      NaN   \n",
       "yr2011                                    NaN                      NaN   \n",
       "yr2012                                    NaN                      NaN   \n",
       "yr2013                                    NaN                      NaN   \n",
       "yr2014                                    NaN                      NaN   \n",
       "yr2015                                    NaN                      NaN   \n",
       "yr2016                                    NaN                      NaN   \n",
       "yr2017                                    NaN                      NaN   \n",
       "\n",
       "                                     change_prop_not_on_strike  \\\n",
       "strikers_diff                                         0.687359   \n",
       "Priv Union Members (%)                               -0.281236   \n",
       "state_inf                                             0.104800   \n",
       "state_inf_t                                           0.522675   \n",
       "state_inf_nt                                         -0.074772   \n",
       "prop_rep                                              0.093953   \n",
       "Wage_Increase_Indicator                               0.101174   \n",
       "change_prop_not_on_strike                             1.000000   \n",
       "change_prop_not_on_strike_indicator                  -0.347962   \n",
       "instrument_calc                                       0.185929   \n",
       "us_inf                                                     NaN   \n",
       "yr1995                                                     NaN   \n",
       "yr1996                                                     NaN   \n",
       "yr1997                                                     NaN   \n",
       "yr1998                                                     NaN   \n",
       "yr1999                                                     NaN   \n",
       "yr2000                                                     NaN   \n",
       "yr2001                                                     NaN   \n",
       "yr2002                                                     NaN   \n",
       "yr2003                                                     NaN   \n",
       "yr2004                                                     NaN   \n",
       "yr2005                                                     NaN   \n",
       "yr2006                                                     NaN   \n",
       "yr2007                                                     NaN   \n",
       "yr2008                                                     NaN   \n",
       "yr2009                                                     NaN   \n",
       "yr2010                                                     NaN   \n",
       "yr2011                                                     NaN   \n",
       "yr2012                                                     NaN   \n",
       "yr2013                                                     NaN   \n",
       "yr2014                                                     NaN   \n",
       "yr2015                                                     NaN   \n",
       "yr2016                                                     NaN   \n",
       "yr2017                                                     NaN   \n",
       "\n",
       "                                     change_prop_not_on_strike_indicator  \\\n",
       "strikers_diff                                                  -0.284422   \n",
       "Priv Union Members (%)                                          0.721259   \n",
       "state_inf                                                       0.174437   \n",
       "state_inf_t                                                    -0.097559   \n",
       "state_inf_nt                                                    0.100773   \n",
       "prop_rep                                                       -0.169498   \n",
       "Wage_Increase_Indicator                                         0.099478   \n",
       "change_prop_not_on_strike                                      -0.347962   \n",
       "change_prop_not_on_strike_indicator                             1.000000   \n",
       "instrument_calc                                                 0.387642   \n",
       "us_inf                                                               NaN   \n",
       "yr1995                                                               NaN   \n",
       "yr1996                                                               NaN   \n",
       "yr1997                                                               NaN   \n",
       "yr1998                                                               NaN   \n",
       "yr1999                                                               NaN   \n",
       "yr2000                                                               NaN   \n",
       "yr2001                                                               NaN   \n",
       "yr2002                                                               NaN   \n",
       "yr2003                                                               NaN   \n",
       "yr2004                                                               NaN   \n",
       "yr2005                                                               NaN   \n",
       "yr2006                                                               NaN   \n",
       "yr2007                                                               NaN   \n",
       "yr2008                                                               NaN   \n",
       "yr2009                                                               NaN   \n",
       "yr2010                                                               NaN   \n",
       "yr2011                                                               NaN   \n",
       "yr2012                                                               NaN   \n",
       "yr2013                                                               NaN   \n",
       "yr2014                                                               NaN   \n",
       "yr2015                                                               NaN   \n",
       "yr2016                                                               NaN   \n",
       "yr2017                                                               NaN   \n",
       "\n",
       "                                     instrument_calc  ...  yr2008  yr2009  \\\n",
       "strikers_diff                               0.127987  ...     NaN     NaN   \n",
       "Priv Union Members (%)                      0.234832  ...     NaN     NaN   \n",
       "state_inf                                   0.484394  ...     NaN     NaN   \n",
       "state_inf_t                                 0.487353  ...     NaN     NaN   \n",
       "state_inf_nt                                0.351747  ...     NaN     NaN   \n",
       "prop_rep                                   -0.137249  ...     NaN     NaN   \n",
       "Wage_Increase_Indicator                     0.591030  ...     NaN     NaN   \n",
       "change_prop_not_on_strike                   0.185929  ...     NaN     NaN   \n",
       "change_prop_not_on_strike_indicator         0.387642  ...     NaN     NaN   \n",
       "instrument_calc                             1.000000  ...     NaN     NaN   \n",
       "us_inf                                           NaN  ...     NaN     NaN   \n",
       "yr1995                                           NaN  ...     NaN     NaN   \n",
       "yr1996                                           NaN  ...     NaN     NaN   \n",
       "yr1997                                           NaN  ...     NaN     NaN   \n",
       "yr1998                                           NaN  ...     NaN     NaN   \n",
       "yr1999                                           NaN  ...     NaN     NaN   \n",
       "yr2000                                           NaN  ...     NaN     NaN   \n",
       "yr2001                                           NaN  ...     NaN     NaN   \n",
       "yr2002                                           NaN  ...     NaN     NaN   \n",
       "yr2003                                           NaN  ...     NaN     NaN   \n",
       "yr2004                                           NaN  ...     NaN     NaN   \n",
       "yr2005                                           NaN  ...     NaN     NaN   \n",
       "yr2006                                           NaN  ...     NaN     NaN   \n",
       "yr2007                                           NaN  ...     NaN     NaN   \n",
       "yr2008                                           NaN  ...     NaN     NaN   \n",
       "yr2009                                           NaN  ...     NaN     NaN   \n",
       "yr2010                                           NaN  ...     NaN     NaN   \n",
       "yr2011                                           NaN  ...     NaN     NaN   \n",
       "yr2012                                           NaN  ...     NaN     NaN   \n",
       "yr2013                                           NaN  ...     NaN     NaN   \n",
       "yr2014                                           NaN  ...     NaN     NaN   \n",
       "yr2015                                           NaN  ...     NaN     NaN   \n",
       "yr2016                                           NaN  ...     NaN     NaN   \n",
       "yr2017                                           NaN  ...     NaN     NaN   \n",
       "\n",
       "                                     yr2010  yr2011  yr2012  yr2013  yr2014  \\\n",
       "strikers_diff                           NaN     NaN     NaN     NaN     NaN   \n",
       "Priv Union Members (%)                  NaN     NaN     NaN     NaN     NaN   \n",
       "state_inf                               NaN     NaN     NaN     NaN     NaN   \n",
       "state_inf_t                             NaN     NaN     NaN     NaN     NaN   \n",
       "state_inf_nt                            NaN     NaN     NaN     NaN     NaN   \n",
       "prop_rep                                NaN     NaN     NaN     NaN     NaN   \n",
       "Wage_Increase_Indicator                 NaN     NaN     NaN     NaN     NaN   \n",
       "change_prop_not_on_strike               NaN     NaN     NaN     NaN     NaN   \n",
       "change_prop_not_on_strike_indicator     NaN     NaN     NaN     NaN     NaN   \n",
       "instrument_calc                         NaN     NaN     NaN     NaN     NaN   \n",
       "us_inf                                  NaN     NaN     NaN     NaN     NaN   \n",
       "yr1995                                  NaN     NaN     NaN     NaN     NaN   \n",
       "yr1996                                  NaN     NaN     NaN     NaN     NaN   \n",
       "yr1997                                  NaN     NaN     NaN     NaN     NaN   \n",
       "yr1998                                  NaN     NaN     NaN     NaN     NaN   \n",
       "yr1999                                  NaN     NaN     NaN     NaN     NaN   \n",
       "yr2000                                  NaN     NaN     NaN     NaN     NaN   \n",
       "yr2001                                  NaN     NaN     NaN     NaN     NaN   \n",
       "yr2002                                  NaN     NaN     NaN     NaN     NaN   \n",
       "yr2003                                  NaN     NaN     NaN     NaN     NaN   \n",
       "yr2004                                  NaN     NaN     NaN     NaN     NaN   \n",
       "yr2005                                  NaN     NaN     NaN     NaN     NaN   \n",
       "yr2006                                  NaN     NaN     NaN     NaN     NaN   \n",
       "yr2007                                  NaN     NaN     NaN     NaN     NaN   \n",
       "yr2008                                  NaN     NaN     NaN     NaN     NaN   \n",
       "yr2009                                  NaN     NaN     NaN     NaN     NaN   \n",
       "yr2010                                  NaN     NaN     NaN     NaN     NaN   \n",
       "yr2011                                  NaN     NaN     NaN     NaN     NaN   \n",
       "yr2012                                  NaN     NaN     NaN     NaN     NaN   \n",
       "yr2013                                  NaN     NaN     NaN     NaN     NaN   \n",
       "yr2014                                  NaN     NaN     NaN     NaN     NaN   \n",
       "yr2015                                  NaN     NaN     NaN     NaN     NaN   \n",
       "yr2016                                  NaN     NaN     NaN     NaN     NaN   \n",
       "yr2017                                  NaN     NaN     NaN     NaN     NaN   \n",
       "\n",
       "                                     yr2015  yr2016  yr2017  \n",
       "strikers_diff                           NaN     NaN     NaN  \n",
       "Priv Union Members (%)                  NaN     NaN     NaN  \n",
       "state_inf                               NaN     NaN     NaN  \n",
       "state_inf_t                             NaN     NaN     NaN  \n",
       "state_inf_nt                            NaN     NaN     NaN  \n",
       "prop_rep                                NaN     NaN     NaN  \n",
       "Wage_Increase_Indicator                 NaN     NaN     NaN  \n",
       "change_prop_not_on_strike               NaN     NaN     NaN  \n",
       "change_prop_not_on_strike_indicator     NaN     NaN     NaN  \n",
       "instrument_calc                         NaN     NaN     NaN  \n",
       "us_inf                                  NaN     NaN     NaN  \n",
       "yr1995                                  NaN     NaN     NaN  \n",
       "yr1996                                  NaN     NaN     NaN  \n",
       "yr1997                                  NaN     NaN     NaN  \n",
       "yr1998                                  NaN     NaN     NaN  \n",
       "yr1999                                  NaN     NaN     NaN  \n",
       "yr2000                                  NaN     NaN     NaN  \n",
       "yr2001                                  NaN     NaN     NaN  \n",
       "yr2002                                  NaN     NaN     NaN  \n",
       "yr2003                                  NaN     NaN     NaN  \n",
       "yr2004                                  NaN     NaN     NaN  \n",
       "yr2005                                  NaN     NaN     NaN  \n",
       "yr2006                                  NaN     NaN     NaN  \n",
       "yr2007                                  NaN     NaN     NaN  \n",
       "yr2008                                  NaN     NaN     NaN  \n",
       "yr2009                                  NaN     NaN     NaN  \n",
       "yr2010                                  NaN     NaN     NaN  \n",
       "yr2011                                  NaN     NaN     NaN  \n",
       "yr2012                                  NaN     NaN     NaN  \n",
       "yr2013                                  NaN     NaN     NaN  \n",
       "yr2014                                  NaN     NaN     NaN  \n",
       "yr2015                                  NaN     NaN     NaN  \n",
       "yr2016                                  NaN     NaN     NaN  \n",
       "yr2017                                  NaN     NaN     NaN  \n",
       "\n",
       "[34 rows x 34 columns]"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_1.groupby('State').mean().corr()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "27fd2945-3252-4a96-a558-3c7007b8be20",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 2500x2000 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(25,20));\n",
    "sns.lmplot(data = df_1.groupby('State').mean(),\n",
    "           x = 'instrument_calc', y='change_prop_not_on_strike_indicator', fit_reg=True,ci=50);\n",
    "#plt.title('The Average Instrumental Variable vs Average Endogenous Variable by State');\n",
    "plt.xlabel('Avg Spillover Effects',labelpad=20);\n",
    "plt.ylabel('Average Indicator for Increase in Proportional Strike Activity');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "74e47bef-3fa5-4e9c-9d1d-8be61475843e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "19"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(df_1['State'].unique())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "41f428b8-907b-45c5-80db-6ca7dea4dfef",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_2 = testing_df[['State','Year','strikers_diff','Priv Union Members (%)','prop_rep','Wage_Increase_Indicator','change_prop_not_on_strike','change_prop_not_on_strike_indicator','instrument_calc','us_inf']]\n",
    "df_2 = df_2[df_2['State'].isin(index_2.tolist())]\n",
    "df_2 = df_2[~df_2['prop_rep'].isna()]\n",
    "df_2 = pd.concat([df_2, pd.get_dummies(df_2['Year']).drop(columns=[1994])],axis=1)\n",
    "df_2.columns = [x for x in df_2.columns.tolist() if type(x)!=int] + ['yr'+str(x) for x in df_2.columns.tolist() if type(x)==int]\n",
    "df_2\n",
    "#All states without inflation data, 1994-2020\n",
    "\n",
    "df_2[['Priv Union Members (%)','us_inf','prop_rep','change_prop_not_on_strike_indicator','Wage_Increase_Indicator',\n",
    "      'instrument_calc']].to_csv(\"all_states_no_inflation.csv\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "f9204dc7-f298-4b51-8545-af9a6d93980c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2.110169712145993"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "((df_2['us_inf']/100+1).prod()**(1/len(df_2['us_inf']))-1)*100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "5c367122-2f23-44f7-bf8d-421f1b1101cf",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "        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>Priv Union Members (%)</th>\n",
       "      <th>us_inf</th>\n",
       "      <th>prop_rep</th>\n",
       "      <th>change_prop_not_on_strike_indicator</th>\n",
       "      <th>Wage_Increase_Indicator</th>\n",
       "      <th>instrument_calc</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>864.000000</td>\n",
       "      <td>864.000000</td>\n",
       "      <td>864.000000</td>\n",
       "      <td>864.000000</td>\n",
       "      <td>864.000000</td>\n",
       "      <td>8.640000e+02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>7.926736</td>\n",
       "      <td>2.111111</td>\n",
       "      <td>46.161226</td>\n",
       "      <td>0.221065</td>\n",
       "      <td>0.364583</td>\n",
       "      <td>3.219565e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>3.726034</td>\n",
       "      <td>0.438545</td>\n",
       "      <td>12.274142</td>\n",
       "      <td>0.415204</td>\n",
       "      <td>0.481592</td>\n",
       "      <td>1.471033e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.200000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-9.663032e+03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>4.900000</td>\n",
       "      <td>1.800000</td>\n",
       "      <td>40.115674</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-1.833559e+02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>7.800000</td>\n",
       "      <td>2.200000</td>\n",
       "      <td>46.594214</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.232298e+02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>10.300000</td>\n",
       "      <td>2.400000</td>\n",
       "      <td>53.909956</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>7.317261e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>18.400000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>81.649972</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.150895e+08</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Priv Union Members (%)      us_inf    prop_rep  \\\n",
       "count              864.000000  864.000000  864.000000   \n",
       "mean                 7.926736    2.111111   46.161226   \n",
       "std                  3.726034    0.438545   12.274142   \n",
       "min                  1.200000    1.000000    0.000000   \n",
       "25%                  4.900000    1.800000   40.115674   \n",
       "50%                  7.800000    2.200000   46.594214   \n",
       "75%                 10.300000    2.400000   53.909956   \n",
       "max                 18.400000    3.000000   81.649972   \n",
       "\n",
       "       change_prop_not_on_strike_indicator  Wage_Increase_Indicator  \\\n",
       "count                           864.000000               864.000000   \n",
       "mean                              0.221065                 0.364583   \n",
       "std                               0.415204                 0.481592   \n",
       "min                               0.000000                 0.000000   \n",
       "25%                               0.000000                 0.000000   \n",
       "50%                               0.000000                 0.000000   \n",
       "75%                               0.000000                 1.000000   \n",
       "max                               1.000000                 1.000000   \n",
       "\n",
       "       instrument_calc  \n",
       "count     8.640000e+02  \n",
       "mean      3.219565e+06  \n",
       "std       1.471033e+07  \n",
       "min      -9.663032e+03  \n",
       "25%      -1.833559e+02  \n",
       "50%       3.232298e+02  \n",
       "75%       7.317261e+05  \n",
       "max       2.150895e+08  "
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_2.describe()[['Priv Union Members (%)','us_inf','prop_rep','change_prop_not_on_strike_indicator','Wage_Increase_Indicator','instrument_calc']]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "f6d01dfb-5da7-4097-b1ba-094ea932afd5",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_3 = testing_df[['State','Year','strikers_diff','Priv Union Members (%)','Wage_Increase_Indicator','change_prop_not_on_strike','change_prop_not_on_strike_indicator','instrument_calc','us_inf']]\n",
    "df_3 = df_3[df_3['State'].isin(index_2.tolist())]\n",
    "df_3 = pd.concat([df_3, pd.get_dummies(df_3['Year']).drop(columns=[1994])],axis=1)\n",
    "df_3.columns = [x for x in df_3.columns.tolist() if type(x)!=int] + ['yr'+str(x) for x in df_3.columns.tolist() if type(x)==int]\n",
    "df_3\n",
    "#All states without political lean data (including DC), 1994-2020\n",
    "\n",
    "df_3[['Priv Union Members (%)','us_inf','change_prop_not_on_strike_indicator',\n",
    "      'Wage_Increase_Indicator','instrument_calc']].to_csv(\"all_states_no_poli.csv\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "3d64dee7-43f0-45c6-9197-c733707a469e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2.110169712145993"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "((df_3['us_inf']/100+1).prod()**(1/len(df_3['us_inf']))-1)*100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "25cc1a2e-0cb3-4e74-86a6-e533356edd70",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\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>Priv Union Members (%)</th>\n",
       "      <th>us_inf</th>\n",
       "      <th>change_prop_not_on_strike_indicator</th>\n",
       "      <th>Wage_Increase_Indicator</th>\n",
       "      <th>instrument_calc</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>891.000000</td>\n",
       "      <td>891.000000</td>\n",
       "      <td>891.000000</td>\n",
       "      <td>891.000000</td>\n",
       "      <td>8.910000e+02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>7.914366</td>\n",
       "      <td>2.111111</td>\n",
       "      <td>0.218855</td>\n",
       "      <td>0.368126</td>\n",
       "      <td>3.164306e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>3.686385</td>\n",
       "      <td>0.438537</td>\n",
       "      <td>0.413702</td>\n",
       "      <td>0.482567</td>\n",
       "      <td>1.451806e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.200000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-9.663032e+03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>4.950000</td>\n",
       "      <td>1.800000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-1.769628e+02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>7.800000</td>\n",
       "      <td>2.200000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.307819e+02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>10.200000</td>\n",
       "      <td>2.400000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>7.209879e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>18.400000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.150895e+08</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Priv Union Members (%)      us_inf  \\\n",
       "count              891.000000  891.000000   \n",
       "mean                 7.914366    2.111111   \n",
       "std                  3.686385    0.438537   \n",
       "min                  1.200000    1.000000   \n",
       "25%                  4.950000    1.800000   \n",
       "50%                  7.800000    2.200000   \n",
       "75%                 10.200000    2.400000   \n",
       "max                 18.400000    3.000000   \n",
       "\n",
       "       change_prop_not_on_strike_indicator  Wage_Increase_Indicator  \\\n",
       "count                           891.000000               891.000000   \n",
       "mean                              0.218855                 0.368126   \n",
       "std                               0.413702                 0.482567   \n",
       "min                               0.000000                 0.000000   \n",
       "25%                               0.000000                 0.000000   \n",
       "50%                               0.000000                 0.000000   \n",
       "75%                               0.000000                 1.000000   \n",
       "max                               1.000000                 1.000000   \n",
       "\n",
       "       instrument_calc  \n",
       "count     8.910000e+02  \n",
       "mean      3.164306e+06  \n",
       "std       1.451806e+07  \n",
       "min      -9.663032e+03  \n",
       "25%      -1.769628e+02  \n",
       "50%       3.307819e+02  \n",
       "75%       7.209879e+05  \n",
       "max       2.150895e+08  "
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_3.describe()[['Priv Union Members (%)','us_inf','change_prop_not_on_strike_indicator','Wage_Increase_Indicator','instrument_calc']]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5f0433c0-65d9-4d08-810a-6a949a8cdd96",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c63e0771-e4bb-4902-948b-76ed3eb4bf17",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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