Interactive analysis of the election of the European Parliament in 2019 using Jupyter Notebooks, pandas and matplotlib.
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{
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"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>DIVISION_ID</th>\n",
" <th>TYPE</th>\n",
" <th>ACRONYM</th>\n",
" <th>LABEL</th>\n",
" </tr>\n",
" <tr>\n",
" <th>ID</th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>DE01</th>\n",
" <td>DE</td>\n",
" <td>PARTY</td>\n",
" <td>CDU - CSU</td>\n",
" <td>Christlich Demokratische Union Deutschlands / ...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>DE02</th>\n",
" <td>DE</td>\n",
" <td>PARTY</td>\n",
" <td>SPD</td>\n",
" <td>Sozialdemokratische Partei Deutschlands</td>\n",
" </tr>\n",
" <tr>\n",
" <th>DE03</th>\n",
" <td>DE</td>\n",
" <td>PARTY</td>\n",
" <td>GRÜNE</td>\n",
" <td>Bündnis 90/Die Grünen</td>\n",
" </tr>\n",
" <tr>\n",
" <th>DE04</th>\n",
" <td>DE</td>\n",
" <td>PARTY</td>\n",
" <td>DIE LINKE</td>\n",
" <td>DIE LINKE</td>\n",
" </tr>\n",
" <tr>\n",
" <th>DE05</th>\n",
" <td>DE</td>\n",
" <td>PARTY</td>\n",
" <td>AfD</td>\n",
" <td>Alternative für Deutschland</td>\n",
" </tr>\n",
" <tr>\n",
" <th>DE06</th>\n",
" <td>DE</td>\n",
" <td>PARTY</td>\n",
" <td>FDP</td>\n",
" <td>Freie Demokratische Partei</td>\n",
" </tr>\n",
" <tr>\n",
" <th>DE07</th>\n",
" <td>DE</td>\n",
" <td>PARTY</td>\n",
" <td>FREIE WÄHLER</td>\n",
" <td>FREIE WÄHLER</td>\n",
" </tr>\n",
" <tr>\n",
" <th>DE08</th>\n",
" <td>DE</td>\n",
" <td>PARTY</td>\n",
" <td>PIRATEN</td>\n",
" <td>Piratenpartei Deutschland</td>\n",
" </tr>\n",
" <tr>\n",
" <th>DE09</th>\n",
" <td>DE</td>\n",
" <td>PARTY</td>\n",
" <td>Tierschutzpartei</td>\n",
" <td>PARTEI MENSCH UMWELT TIERSCHUTZ</td>\n",
" </tr>\n",
" <tr>\n",
" <th>DE10</th>\n",
" <td>DE</td>\n",
" <td>PARTY</td>\n",
" <td>NPD</td>\n",
" <td>Nationaldemokratische Partei Deutschlands</td>\n",
" </tr>\n",
" <tr>\n",
" <th>DE11</th>\n",
" <td>DE</td>\n",
" <td>PARTY</td>\n",
" <td>FAMILIE</td>\n",
" <td>Familien-Partei Deutschlands</td>\n",
" </tr>\n",
" <tr>\n",
" <th>DE12</th>\n",
" <td>DE</td>\n",
" <td>PARTY</td>\n",
" <td>ÖDP</td>\n",
" <td>Ökologisch-Demokratische Partei</td>\n",
" </tr>\n",
" <tr>\n",
" <th>DE13</th>\n",
" <td>DE</td>\n",
" <td>PARTY</td>\n",
" <td>Die PARTEI</td>\n",
" <td>Partei für Arbeit, Rechtsstaat, Tierschutz, El...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>DE14</th>\n",
" <td>DE</td>\n",
" <td>PARTY</td>\n",
" <td>VOLT</td>\n",
" <td>VOLT</td>\n",
" </tr>\n",
" <tr>\n",
" <th>DE90</th>\n",
" <td>DE</td>\n",
" <td>PARTY</td>\n",
" <td>Other parties</td>\n",
" <td>Other parties</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" DIVISION_ID TYPE ACRONYM \\\n",
"ID \n",
"DE01 DE PARTY CDU - CSU \n",
"DE02 DE PARTY SPD \n",
"DE03 DE PARTY GRÜNE \n",
"DE04 DE PARTY DIE LINKE \n",
"DE05 DE PARTY AfD \n",
"DE06 DE PARTY FDP \n",
"DE07 DE PARTY FREIE WÄHLER \n",
"DE08 DE PARTY PIRATEN \n",
"DE09 DE PARTY Tierschutzpartei \n",
"DE10 DE PARTY NPD \n",
"DE11 DE PARTY FAMILIE \n",
"DE12 DE PARTY ÖDP \n",
"DE13 DE PARTY Die PARTEI \n",
"DE14 DE PARTY VOLT \n",
"DE90 DE PARTY Other parties \n",
"\n",
" LABEL \n",
"ID \n",
"DE01 Christlich Demokratische Union Deutschlands / ... \n",
"DE02 Sozialdemokratische Partei Deutschlands \n",
"DE03 Bündnis 90/Die Grünen \n",
"DE04 DIE LINKE \n",
"DE05 Alternative für Deutschland \n",
"DE06 Freie Demokratische Partei \n",
"DE07 FREIE WÄHLER \n",
"DE08 Piratenpartei Deutschland \n",
"DE09 PARTEI MENSCH UMWELT TIERSCHUTZ \n",
"DE10 Nationaldemokratische Partei Deutschlands \n",
"DE11 Familien-Partei Deutschlands \n",
"DE12 Ökologisch-Demokratische Partei \n",
"DE13 Partei für Arbeit, Rechtsstaat, Tierschutz, El... \n",
"DE14 VOLT \n",
"DE90 Other parties "
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import pandas as pd\n",
"from download import download_get\n",
"\n",
"parties_file = download_get('https://election-results.eu/data-sheets/csv/2019-2024/election-results/parties.csv')\n",
"parties = pd.read_csv(parties_file, sep=';')\n",
"parties = parties[parties['DIVISION_ID'] == 'DE']\n",
"parties = parties.set_index('ID').dropna(axis='columns')\n",
"parties"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
"data": {
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" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>TYPE</th>\n",
" <th>VOTES_PERCENT</th>\n",
" <th>UPDATE_STATUS</th>\n",
" <th>UPDATE_TIME</th>\n",
" </tr>\n",
" <tr>\n",
" <th>PARTY_ID</th>\n",
" <th></th>\n",
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" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>DE01</th>\n",
" <td>PARTY</td>\n",
" <td>28.9</td>\n",
" <td>FINAL</td>\n",
" <td>2019-05-27 10:18</td>\n",
" </tr>\n",
" <tr>\n",
" <th>DE02</th>\n",
" <td>PARTY</td>\n",
" <td>15.8</td>\n",
" <td>FINAL</td>\n",
" <td>2019-05-27 10:18</td>\n",
" </tr>\n",
" <tr>\n",
" <th>DE03</th>\n",
" <td>PARTY</td>\n",
" <td>20.5</td>\n",
" <td>FINAL</td>\n",
" <td>2019-05-27 10:18</td>\n",
" </tr>\n",
" <tr>\n",
" <th>DE04</th>\n",
" <td>PARTY</td>\n",
" <td>5.5</td>\n",
" <td>FINAL</td>\n",
" <td>2019-05-27 10:18</td>\n",
" </tr>\n",
" <tr>\n",
" <th>DE05</th>\n",
" <td>PARTY</td>\n",
" <td>11.0</td>\n",
" <td>FINAL</td>\n",
" <td>2019-05-27 10:18</td>\n",
" </tr>\n",
" <tr>\n",
" <th>DE06</th>\n",
" <td>PARTY</td>\n",
" <td>5.4</td>\n",
" <td>FINAL</td>\n",
" <td>2019-05-27 10:18</td>\n",
" </tr>\n",
" <tr>\n",
" <th>DE07</th>\n",
" <td>PARTY</td>\n",
" <td>2.2</td>\n",
" <td>FINAL</td>\n",
" <td>2019-05-27 10:18</td>\n",
" </tr>\n",
" <tr>\n",
" <th>DE08</th>\n",
" <td>PARTY</td>\n",
" <td>0.7</td>\n",
" <td>FINAL</td>\n",
" <td>2019-05-27 10:18</td>\n",
" </tr>\n",
" <tr>\n",
" <th>DE09</th>\n",
" <td>PARTY</td>\n",
" <td>1.4</td>\n",
" <td>FINAL</td>\n",
" <td>2019-05-27 10:18</td>\n",
" </tr>\n",
" <tr>\n",
" <th>DE10</th>\n",
" <td>PARTY</td>\n",
" <td>0.3</td>\n",
" <td>FINAL</td>\n",
" <td>2019-05-27 10:18</td>\n",
" </tr>\n",
" <tr>\n",
" <th>DE11</th>\n",
" <td>PARTY</td>\n",
" <td>0.7</td>\n",
" <td>FINAL</td>\n",
" <td>2019-05-27 10:18</td>\n",
" </tr>\n",
" <tr>\n",
" <th>DE12</th>\n",
" <td>PARTY</td>\n",
" <td>1.0</td>\n",
" <td>FINAL</td>\n",
" <td>2019-05-27 10:18</td>\n",
" </tr>\n",
" <tr>\n",
" <th>DE13</th>\n",
" <td>PARTY</td>\n",
" <td>2.4</td>\n",
" <td>FINAL</td>\n",
" <td>2019-05-27 10:18</td>\n",
" </tr>\n",
" <tr>\n",
" <th>DE14</th>\n",
" <td>PARTY</td>\n",
" <td>0.7</td>\n",
" <td>FINAL</td>\n",
" <td>2019-05-27 10:18</td>\n",
" </tr>\n",
" <tr>\n",
" <th>DE90</th>\n",
" <td>PARTY</td>\n",
" <td>3.5</td>\n",
" <td>FINAL</td>\n",
" <td>2019-05-27 10:18</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" TYPE VOTES_PERCENT UPDATE_STATUS UPDATE_TIME\n",
"PARTY_ID \n",
"DE01 PARTY 28.9 FINAL 2019-05-27 10:18\n",
"DE02 PARTY 15.8 FINAL 2019-05-27 10:18\n",
"DE03 PARTY 20.5 FINAL 2019-05-27 10:18\n",
"DE04 PARTY 5.5 FINAL 2019-05-27 10:18\n",
"DE05 PARTY 11.0 FINAL 2019-05-27 10:18\n",
"DE06 PARTY 5.4 FINAL 2019-05-27 10:18\n",
"DE07 PARTY 2.2 FINAL 2019-05-27 10:18\n",
"DE08 PARTY 0.7 FINAL 2019-05-27 10:18\n",
"DE09 PARTY 1.4 FINAL 2019-05-27 10:18\n",
"DE10 PARTY 0.3 FINAL 2019-05-27 10:18\n",
"DE11 PARTY 0.7 FINAL 2019-05-27 10:18\n",
"DE12 PARTY 1.0 FINAL 2019-05-27 10:18\n",
"DE13 PARTY 2.4 FINAL 2019-05-27 10:18\n",
"DE14 PARTY 0.7 FINAL 2019-05-27 10:18\n",
"DE90 PARTY 3.5 FINAL 2019-05-27 10:18"
]
},
"execution_count": 2,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"results_file = download_get('https://election-results.eu/data-sheets/csv/2019-2024/election-results/results-parties/results-parties-de.csv')\n",
"results = pd.read_csv('data/results-parties-de.csv', sep=\";\")\n",
"results = results.set_index('PARTY_ID')\n",
"results"
]
},
{
"cell_type": "code",
"execution_count": 34,
"metadata": {},
"outputs": [
{
"data": {
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"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>DIVISION_ID</th>\n",
" <th>TYPE</th>\n",
" <th>ACRONYM</th>\n",
" <th>LABEL</th>\n",
" <th>VOTES_PERCENT</th>\n",
" <th>UPDATE_STATUS</th>\n",
" <th>UPDATE_TIME</th>\n",
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" <tr>\n",
" <th>ID</th>\n",
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" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>DE01</th>\n",
" <td>DE</td>\n",
" <td>PARTY</td>\n",
" <td>CDU - CSU</td>\n",
" <td>Christlich Demokratische Union Deutschlands / ...</td>\n",
" <td>28.9</td>\n",
" <td>FINAL</td>\n",
" <td>2019-05-27 10:18</td>\n",
" </tr>\n",
" <tr>\n",
" <th>DE02</th>\n",
" <td>DE</td>\n",
" <td>PARTY</td>\n",
" <td>SPD</td>\n",
" <td>Sozialdemokratische Partei Deutschlands</td>\n",
" <td>15.8</td>\n",
" <td>FINAL</td>\n",
" <td>2019-05-27 10:18</td>\n",
" </tr>\n",
" <tr>\n",
" <th>DE03</th>\n",
" <td>DE</td>\n",
" <td>PARTY</td>\n",
" <td>GRÜNE</td>\n",
" <td>Bündnis 90/Die Grünen</td>\n",
" <td>20.5</td>\n",
" <td>FINAL</td>\n",
" <td>2019-05-27 10:18</td>\n",
" </tr>\n",
" <tr>\n",
" <th>DE04</th>\n",
" <td>DE</td>\n",
" <td>PARTY</td>\n",
" <td>DIE LINKE</td>\n",
" <td>DIE LINKE</td>\n",
" <td>5.5</td>\n",
" <td>FINAL</td>\n",
" <td>2019-05-27 10:18</td>\n",
" </tr>\n",
" <tr>\n",
" <th>DE05</th>\n",
" <td>DE</td>\n",
" <td>PARTY</td>\n",
" <td>AfD</td>\n",
" <td>Alternative für Deutschland</td>\n",
" <td>11.0</td>\n",
" <td>FINAL</td>\n",
" <td>2019-05-27 10:18</td>\n",
" </tr>\n",
" <tr>\n",
" <th>DE06</th>\n",
" <td>DE</td>\n",
" <td>PARTY</td>\n",
" <td>FDP</td>\n",
" <td>Freie Demokratische Partei</td>\n",
" <td>5.4</td>\n",
" <td>FINAL</td>\n",
" <td>2019-05-27 10:18</td>\n",
" </tr>\n",
" <tr>\n",
" <th>DE07</th>\n",
" <td>DE</td>\n",
" <td>PARTY</td>\n",
" <td>FREIE WÄHLER</td>\n",
" <td>FREIE WÄHLER</td>\n",
" <td>2.2</td>\n",
" <td>FINAL</td>\n",
" <td>2019-05-27 10:18</td>\n",
" </tr>\n",
" <tr>\n",
" <th>DE08</th>\n",
" <td>DE</td>\n",
" <td>PARTY</td>\n",
" <td>PIRATEN</td>\n",
" <td>Piratenpartei Deutschland</td>\n",
" <td>0.7</td>\n",
" <td>FINAL</td>\n",
" <td>2019-05-27 10:18</td>\n",
" </tr>\n",
" <tr>\n",
" <th>DE09</th>\n",
" <td>DE</td>\n",
" <td>PARTY</td>\n",
" <td>Tierschutzpartei</td>\n",
" <td>PARTEI MENSCH UMWELT TIERSCHUTZ</td>\n",
" <td>1.4</td>\n",
" <td>FINAL</td>\n",
" <td>2019-05-27 10:18</td>\n",
" </tr>\n",
" <tr>\n",
" <th>DE10</th>\n",
" <td>DE</td>\n",
" <td>PARTY</td>\n",
" <td>NPD</td>\n",
" <td>Nationaldemokratische Partei Deutschlands</td>\n",
" <td>0.3</td>\n",
" <td>FINAL</td>\n",
" <td>2019-05-27 10:18</td>\n",
" </tr>\n",
" <tr>\n",
" <th>DE11</th>\n",
" <td>DE</td>\n",
" <td>PARTY</td>\n",
" <td>FAMILIE</td>\n",
" <td>Familien-Partei Deutschlands</td>\n",
" <td>0.7</td>\n",
" <td>FINAL</td>\n",
" <td>2019-05-27 10:18</td>\n",
" </tr>\n",
" <tr>\n",
" <th>DE12</th>\n",
" <td>DE</td>\n",
" <td>PARTY</td>\n",
" <td>ÖDP</td>\n",
" <td>Ökologisch-Demokratische Partei</td>\n",
" <td>1.0</td>\n",
" <td>FINAL</td>\n",
" <td>2019-05-27 10:18</td>\n",
" </tr>\n",
" <tr>\n",
" <th>DE13</th>\n",
" <td>DE</td>\n",
" <td>PARTY</td>\n",
" <td>Die PARTEI</td>\n",
" <td>Partei für Arbeit, Rechtsstaat, Tierschutz, El...</td>\n",
" <td>2.4</td>\n",
" <td>FINAL</td>\n",
" <td>2019-05-27 10:18</td>\n",
" </tr>\n",
" <tr>\n",
" <th>DE14</th>\n",
" <td>DE</td>\n",
" <td>PARTY</td>\n",
" <td>VOLT</td>\n",
" <td>VOLT</td>\n",
" <td>0.7</td>\n",
" <td>FINAL</td>\n",
" <td>2019-05-27 10:18</td>\n",
" </tr>\n",
" <tr>\n",
" <th>DE90</th>\n",
" <td>DE</td>\n",
" <td>PARTY</td>\n",
" <td>Other parties</td>\n",
" <td>Other parties</td>\n",
" <td>3.5</td>\n",
" <td>FINAL</td>\n",
" <td>2019-05-27 10:18</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" DIVISION_ID TYPE ACRONYM \\\n",
"ID \n",
"DE01 DE PARTY CDU - CSU \n",
"DE02 DE PARTY SPD \n",
"DE03 DE PARTY GRÜNE \n",
"DE04 DE PARTY DIE LINKE \n",
"DE05 DE PARTY AfD \n",
"DE06 DE PARTY FDP \n",
"DE07 DE PARTY FREIE WÄHLER \n",
"DE08 DE PARTY PIRATEN \n",
"DE09 DE PARTY Tierschutzpartei \n",
"DE10 DE PARTY NPD \n",
"DE11 DE PARTY FAMILIE \n",
"DE12 DE PARTY ÖDP \n",
"DE13 DE PARTY Die PARTEI \n",
"DE14 DE PARTY VOLT \n",
"DE90 DE PARTY Other parties \n",
"\n",
" LABEL VOTES_PERCENT \\\n",
"ID \n",
"DE01 Christlich Demokratische Union Deutschlands / ... 28.9 \n",
"DE02 Sozialdemokratische Partei Deutschlands 15.8 \n",
"DE03 Bündnis 90/Die Grünen 20.5 \n",
"DE04 DIE LINKE 5.5 \n",
"DE05 Alternative für Deutschland 11.0 \n",
"DE06 Freie Demokratische Partei 5.4 \n",
"DE07 FREIE WÄHLER 2.2 \n",
"DE08 Piratenpartei Deutschland 0.7 \n",
"DE09 PARTEI MENSCH UMWELT TIERSCHUTZ 1.4 \n",
"DE10 Nationaldemokratische Partei Deutschlands 0.3 \n",
"DE11 Familien-Partei Deutschlands 0.7 \n",
"DE12 Ökologisch-Demokratische Partei 1.0 \n",
"DE13 Partei für Arbeit, Rechtsstaat, Tierschutz, El... 2.4 \n",
"DE14 VOLT 0.7 \n",
"DE90 Other parties 3.5 \n",
"\n",
" UPDATE_STATUS UPDATE_TIME \n",
"ID \n",
"DE01 FINAL 2019-05-27 10:18 \n",
"DE02 FINAL 2019-05-27 10:18 \n",
"DE03 FINAL 2019-05-27 10:18 \n",
"DE04 FINAL 2019-05-27 10:18 \n",
"DE05 FINAL 2019-05-27 10:18 \n",
"DE06 FINAL 2019-05-27 10:18 \n",
"DE07 FINAL 2019-05-27 10:18 \n",
"DE08 FINAL 2019-05-27 10:18 \n",
"DE09 FINAL 2019-05-27 10:18 \n",
"DE10 FINAL 2019-05-27 10:18 \n",
"DE11 FINAL 2019-05-27 10:18 \n",
"DE12 FINAL 2019-05-27 10:18 \n",
"DE13 FINAL 2019-05-27 10:18 \n",
"DE14 FINAL 2019-05-27 10:18 \n",
"DE90 FINAL 2019-05-27 10:18 "
]
},
"execution_count": 34,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"party_results = parties.join(results, rsuffix='_result')\n",
"del party_results['TYPE_result']\n",
"party_results"
]
},
{
"cell_type": "code",
"execution_count": 62,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 1296x648 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"%matplotlib inline\n",
"import matplotlib.pyplot as plt\n",
"\n",
"results_bar = party_results.plot.bar('ACRONYM', 'VOTES_PERCENT', figsize=(18, 9))\n",
"results_bar.axhline(0.6, color='red')\n",
"for p in results_bar.patches:\n",
" results_bar.annotate('{} %'.format(p.get_height()), (p.get_x(), p.get_height() + 0.6))"
]
},
{
"cell_type": "code",
"execution_count": 130,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 720x720 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"eup_total_seats = 701\n",
"eup_german_seats = 96\n",
"\n",
"finished_party_results = party_results[party_results['VOTES_PERCENT'] >= 0.6].copy()\n",
"\n",
"finished_party_results['SEATS'] = round((party_results['VOTES_PERCENT'] / 100) * eup_german_seats)\n",
"finished_party_results = finished_party_results.drop('DE90')\n",
"\n",
"seats = finished_party_results.plot.pie(\n",
" y='SEATS',\n",
" labels=None,\n",
" wedgeprops=dict(width=0.6),\n",
" startangle=-10,\n",
" legend=False,\n",
" figsize=(10, 10)\n",
")\n",
"\n",
"# see https://matplotlib.org/3.1.0/gallery/pie_and_polar_charts/pie_and_donut_labels.html#sphx-glr-gallery-pie-and-polar-charts-pie-and-donut-labels-py\n",
"bbox_props = dict(boxstyle=\"square,pad=0.3\", fc=\"w\", ec=\"k\", lw=0.72)\n",
"kw = dict(arrowprops=dict(arrowstyle=\"-\"),\n",
" bbox=bbox_props, zorder=0, va=\"center\")\n",
"\n",
"for i, p in enumerate(seats.patches):\n",
" ang = (p.theta2 - p.theta1)/2. + p.theta1\n",
" y = np.sin(np.deg2rad(ang))\n",
" x = np.cos(np.deg2rad(ang))\n",
" horizontalalignment = {-1: \"right\", 1: \"left\"}[int(np.sign(x))]\n",
" connectionstyle = \"angle,angleA=0,angleB={}\".format(ang)\n",
" kw[\"arrowprops\"].update({\"connectionstyle\": connectionstyle})\n",
" \n",
" row = finished_party_results.iloc[i]\n",
" \n",
" seats.annotate(\n",
" \"{} {}%\".format(row['ACRONYM'], row['SEATS']),\n",
" xy=(x, y),\n",
" xytext=(1.35*np.sign(x), 1.4*y),\n",
" horizontalalignment=horizontalalignment,\n",
" **kw\n",
" )"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.7.3"
}
},
"nbformat": 4,
"nbformat_minor": 2
}