usa election.ipynb

{
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   "id": "aa7c0f17-40c1-4716-bfe2-297473cf4e11",
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   "outputs": [
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     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>State</th>\n",
       "      <th>ST</th>\n",
       "      <th>Fips</th>\n",
       "      <th>County</th>\n",
       "      <th>Trump</th>\n",
       "      <th>Clinton</th>\n",
       "      <th>Stein</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Georgia</td>\n",
       "      <td>GA</td>\n",
       "      <td>13089</td>\n",
       "      <td>DeKalb County, Georgia</td>\n",
       "      <td>47531</td>\n",
       "      <td>239131</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Texas</td>\n",
       "      <td>TX</td>\n",
       "      <td>48487</td>\n",
       "      <td>Wilbarger County, Texas</td>\n",
       "      <td>3166</td>\n",
       "      <td>807</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Virginia</td>\n",
       "      <td>VA</td>\n",
       "      <td>51111</td>\n",
       "      <td>Lunenburg County, Virginia</td>\n",
       "      <td>3206</td>\n",
       "      <td>2226</td>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Georgia</td>\n",
       "      <td>GA</td>\n",
       "      <td>13297</td>\n",
       "      <td>Walton County, Georgia</td>\n",
       "      <td>31093</td>\n",
       "      <td>8279</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>North Carolina</td>\n",
       "      <td>NC</td>\n",
       "      <td>37011</td>\n",
       "      <td>Avery County, North Carolina</td>\n",
       "      <td>6226</td>\n",
       "      <td>1670</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            State  ST   Fips                        County  Trump  Clinton  \\\n",
       "0         Georgia  GA  13089        DeKalb County, Georgia  47531   239131   \n",
       "1           Texas  TX  48487       Wilbarger County, Texas   3166      807   \n",
       "2        Virginia  VA  51111    Lunenburg County, Virginia   3206     2226   \n",
       "3         Georgia  GA  13297        Walton County, Georgia  31093     8279   \n",
       "4  North Carolina  NC  37011  Avery County, North Carolina   6226     1670   \n",
       "\n",
       "   Stein  \n",
       "0      0  \n",
       "1     13  \n",
       "2     25  \n",
       "3      0  \n",
       "4      0  "
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "import pandas as pd\n",
    "import pylab as pl\n",
    "pl.style.use('bmh')\n",
    "\n",
    "pd.options.mode.chained_assignment = None\n",
    "\n",
    "T=pd.read_csv(r'C:\\Users\\julia\\Documents\\python36\\datasource\\data\\benford_usa.csv', sep=';')\n",
    "T.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "57f6446e-1b33-45fb-8f3c-f7e3887780fb",
   "metadata": {},
   "outputs": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>State</th>\n",
       "      <th>ST</th>\n",
       "      <th>Fips</th>\n",
       "      <th>County</th>\n",
       "      <th>Trump</th>\n",
       "      <th>Clinton</th>\n",
       "      <th>Stein</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Michigan</td>\n",
       "      <td>MI</td>\n",
       "      <td>26037</td>\n",
       "      <td>Clinton County, Michigan</td>\n",
       "      <td>21635</td>\n",
       "      <td>16490</td>\n",
       "      <td>379</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Michigan</td>\n",
       "      <td>MI</td>\n",
       "      <td>26013</td>\n",
       "      <td>Baraga County, Michigan</td>\n",
       "      <td>2158</td>\n",
       "      <td>1156</td>\n",
       "      <td>49</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Pennsylvania</td>\n",
       "      <td>PA</td>\n",
       "      <td>42005</td>\n",
       "      <td>Armstrong County, Pennsylvania</td>\n",
       "      <td>22676</td>\n",
       "      <td>6849</td>\n",
       "      <td>136</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Wisconsin</td>\n",
       "      <td>WI</td>\n",
       "      <td>55097</td>\n",
       "      <td>Portage County, Wisconsin</td>\n",
       "      <td>17310</td>\n",
       "      <td>18524</td>\n",
       "      <td>583</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>Wisconsin</td>\n",
       "      <td>WI</td>\n",
       "      <td>55039</td>\n",
       "      <td>Fond du Lac County, Wisconsin</td>\n",
       "      <td>31044</td>\n",
       "      <td>17391</td>\n",
       "      <td>449</td>\n",
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      ],
      "text/plain": [
       "           State  ST   Fips                          County  Trump  Clinton  \\\n",
       "6       Michigan  MI  26037        Clinton County, Michigan  21635    16490   \n",
       "12      Michigan  MI  26013         Baraga County, Michigan   2158     1156   \n",
       "20  Pennsylvania  PA  42005  Armstrong County, Pennsylvania  22676     6849   \n",
       "26     Wisconsin  WI  55097       Portage County, Wisconsin  17310    18524   \n",
       "33     Wisconsin  WI  55039   Fond du Lac County, Wisconsin  31044    17391   \n",
       "\n",
       "    Stein  \n",
       "6     379  \n",
       "12     49  \n",
       "20    136  \n",
       "26    583  \n",
       "33    449  "
      ]
     },
     "execution_count": 18,
     "metadata": {},
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   ],
   "source": [
    "S=T.query('State in [\"Wisconsin\", \"Michigan\", \"Pennsylvania\"]')\n",
    "S.head()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "81a7b685-eeb8-4b52-bd57-49d58f69cd00",
   "metadata": {},
   "outputs": [],
   "source": [
    "S=S.query('Trump>=10 and Clinton>=10 and Stein>=10')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "35ea5c9d-5bfd-4035-b6c1-284c22c23f0d",
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    {
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       "220"
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     "execution_count": 29,
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   "source": [
    "len(S)"
   ]
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  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "c0e68cf7-5a64-47a5-93d5-90b73eb84730",
   "metadata": {},
   "outputs": [],
   "source": [
    "def second_chiffre(n):\n",
    "    s=str(n)\n",
    "    return int(s[1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "ab53c5fa-d670-453c-8169-260ad99b2d21",
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       "      <th></th>\n",
       "      <th>State</th>\n",
       "      <th>ST</th>\n",
       "      <th>Fips</th>\n",
       "      <th>County</th>\n",
       "      <th>Trump</th>\n",
       "      <th>Clinton</th>\n",
       "      <th>Stein</th>\n",
       "      <th>T_2</th>\n",
       "      <th>C_2</th>\n",
       "      <th>S_2</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Michigan</td>\n",
       "      <td>MI</td>\n",
       "      <td>26037</td>\n",
       "      <td>Clinton County, Michigan</td>\n",
       "      <td>21635</td>\n",
       "      <td>16490</td>\n",
       "      <td>379</td>\n",
       "      <td>1</td>\n",
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       "      <td>7</td>\n",
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       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Michigan</td>\n",
       "      <td>MI</td>\n",
       "      <td>26013</td>\n",
       "      <td>Baraga County, Michigan</td>\n",
       "      <td>2158</td>\n",
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       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>9</td>\n",
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       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Pennsylvania</td>\n",
       "      <td>PA</td>\n",
       "      <td>42005</td>\n",
       "      <td>Armstrong County, Pennsylvania</td>\n",
       "      <td>22676</td>\n",
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       "      <td>2</td>\n",
       "      <td>8</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Wisconsin</td>\n",
       "      <td>WI</td>\n",
       "      <td>55097</td>\n",
       "      <td>Portage County, Wisconsin</td>\n",
       "      <td>17310</td>\n",
       "      <td>18524</td>\n",
       "      <td>583</td>\n",
       "      <td>7</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>Wisconsin</td>\n",
       "      <td>WI</td>\n",
       "      <td>55039</td>\n",
       "      <td>Fond du Lac County, Wisconsin</td>\n",
       "      <td>31044</td>\n",
       "      <td>17391</td>\n",
       "      <td>449</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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      ],
      "text/plain": [
       "           State  ST   Fips                          County  Trump  Clinton  \\\n",
       "6       Michigan  MI  26037        Clinton County, Michigan  21635    16490   \n",
       "12      Michigan  MI  26013         Baraga County, Michigan   2158     1156   \n",
       "20  Pennsylvania  PA  42005  Armstrong County, Pennsylvania  22676     6849   \n",
       "26     Wisconsin  WI  55097       Portage County, Wisconsin  17310    18524   \n",
       "33     Wisconsin  WI  55039   Fond du Lac County, Wisconsin  31044    17391   \n",
       "\n",
       "    Stein  T_2  C_2  S_2  \n",
       "6     379    1    6    7  \n",
       "12     49    1    1    9  \n",
       "20    136    2    8    3  \n",
       "26    583    7    8    8  \n",
       "33    449    1    7    4  "
      ]
     },
     "execution_count": 31,
     "metadata": {},
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    }
   ],
   "source": [
    "S['T_2']=S['Trump'].apply(second_chiffre)\n",
    "S['C_2']=S['Clinton'].apply(second_chiffre)\n",
    "S['S_2']=S['Stein'].apply(second_chiffre)\n",
    "S.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "72cccba5-47e0-4322-b73f-6286642240c3",
   "metadata": {},
   "outputs": [],
   "source": [
    "def effectifs(L):\n",
    "    return [L.count(k) for k in range(10)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "0c280bf2-f2d9-4541-8de3-8c7c4acf390a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[22, 31, 23, 24, 25, 23, 24, 21, 14, 13]"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "effectifs(list(S['T_2']))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "a1f8de2d-e460-4296-bc71-8ce0f44a9d93",
   "metadata": {},
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    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Trump</th>\n",
       "      <th>Clinton</th>\n",
       "      <th>Stein</th>\n",
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       "      <th>1</th>\n",
       "      <td>31</td>\n",
       "      <td>25</td>\n",
       "      <td>30</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>23</td>\n",
       "      <td>27</td>\n",
       "      <td>14</td>\n",
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       "      <th>3</th>\n",
       "      <td>24</td>\n",
       "      <td>20</td>\n",
       "      <td>21</td>\n",
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       "      <th>4</th>\n",
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       "      <th>5</th>\n",
       "      <td>23</td>\n",
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       "      <th>6</th>\n",
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       "      <th>7</th>\n",
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       "      <td>14</td>\n",
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       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>14</td>\n",
       "      <td>21</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>13</td>\n",
       "      <td>14</td>\n",
       "      <td>28</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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      ],
      "text/plain": [
       "   Trump  Clinton  Stein\n",
       "0     22       19     24\n",
       "1     31       25     30\n",
       "2     23       27     14\n",
       "3     24       20     21\n",
       "4     25       23     36\n",
       "5     23       20      6\n",
       "6     24       27     24\n",
       "7     21       24     14\n",
       "8     14       21     23\n",
       "9     13       14     28"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "E=pd.DataFrame()\n",
    "E['Trump']=effectifs(list(S['T_2']))\n",
    "E['Clinton']=effectifs(list(S['C_2']))\n",
    "E['Stein']=effectifs(list(S['S_2']))\n",
    "E"
   ]
  },
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   "execution_count": null,
   "id": "6238ecc6-6798-48d8-bf4d-6447316cca91",
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   "source": [
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