stembureau-meting/jupyter/.ipynb_checkpoints/stembureau_data-checkpoint.ipynb
2022-04-13 15:08:29 +02:00

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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Data gemeenteraadsverkiezingen 2022 Nederland\n",
"\n",
"Dit notebook is voor het verwerken van de data van de gemeenteraadsverkiezingen van 2022. Er zal hier stap voor stap door de data gelopen worden om het proces reproduceerbaar te maken voor latere verkiezingen. De eerste stap was de data ophalen van de bronnen, zowel de overheid als waar is mijn stemlokaal (voor geografische data van de stemlokalen). De bronnen gebruikt voor de data zijn voor de verkiezingen van 2022 is als volgt:\n",
"\n",
"- [Verkiezingsuitslagen Gemeenteraad 2022](https://data.overheid.nl/dataset/08b04bec-3332-4c76-bb0c-68bfaeb5df43)\n",
" - [Directe link naar uitslagen per gemeente CSV](https://data.overheid.nl/sites/default/files/dataset/08b04bec-3332-4c76-bb0c-68bfaeb5df43/resources/GR2022_2022-03-29T15.14.zip)\n",
" - [Directe link naar kandidatenlijst met uitslagen CSV](https://data.overheid.nl/sites/default/files/dataset/08b04bec-3332-4c76-bb0c-68bfaeb5df43/resources/GR2022_alle-kandidaten_2022-02-22T08.34.csv)\n",
"- [Waar is mijn stemlokaal stembureau data](https://waarismijnstemlokaal.nl/data)\n",
" - [Directe link naar waar is mijn stemlokaal gemeenteraad 2022 CSV (CKAN)](https://ckan.dataplatform.nl/datastore/dump/d6a1b4c4-73c8-457b-9b75-a38428bded68)\n",
" - [Verkiezingsuitslagen gemeenteraadsverkiezingen 2022 geodata (Volkskrant)](https://data.openstate.eu/dataset/verkiezingsuitslagen-gemeenteraadsverkiezingen-2022)\n",
" - [Directe link naar GEOJSON bestand](https://data.openstate.eu/dataset/a1767f1b-bf0c-409b-b3b1-3af9954b57f4/resource/413be255-5070-48f4-b631-895097976abb/download/2022gr.geo.json)\n",
"- [CBS Wijk- en buurtkaart 2021](https://www.cbs.nl/nl-nl/dossier/nederland-regionaal/geografische-data/wijk-en-buurtkaart-2021)\n",
" - [Directe link naar zip bestand met SHP bestand er in](https://www.cbs.nl/-/media/cbs/dossiers/nederland-regionaal/wijk-en-buurtstatistieken/wijkbuurtkaart_2021_v1.zip)\n",
"- [CBS bevolkingsdichtheid kaart 100 bij 100 meter](https://www.cbs.nl/nl-nl/dossier/nederland-regionaal/geografische-data/kaart-van-100-meter-bij-100-meter-met-statistieken)\n",
" - [Directe link naar 7z bestand met SHP bestand er in](https://www.cbs.nl/-/media/cbs/dossiers/nederland-regionaal/vierkanten/100/nl_vierkant_100meter_bij_100meter.7z)\n",
"- [CBS bevolkingsdichtheid kaart 500 bij 500 meter](https://www.cbs.nl/nl-nl/dossier/nederland-regionaal/geografische-data/kaart-van-500-meter-bij-500-meter-met-statistieken)\n",
" - [Directe link naar 7z bestand met SHP bestand er in](https://www.cbs.nl/-/media/cbs/dossiers/nederland-regionaal/vierkanten/500/2021-cbs_vk500_2020_v1.zip)\n",
"\n",
"De eerste stap die we moeten maken is de data importeren voor de analyse, daarna kunnen we kijken hoe goed de data is, hoe we het aan kunnen vullen, en wat er mee te doen. De makkelijkste structuur die we vonden was het geojson bestand van open state en de Volkskrant, daar staan alle stembureaus al in een lijst, en we hebben een makkelijk framework om het te importeren; geopandas. We laden deze dan ook als eerste in."
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/lillian/.local/lib/python3.9/site-packages/fiona/collection.py:208: FeatureWarning: Empty field name at index 61\n",
" self._schema = self.session.get_schema()\n",
"/home/lillian/anaconda3/lib/python3.9/site-packages/geopandas/geodataframe.py:600: UserWarning: Empty field name at index 61\n",
" for feature in features_lst:\n"
]
}
],
"source": [
"import pandas as pd\n",
"import geopandas as gpd\n",
"\n",
"crs = {'init':'EPSG:4326'}\n",
"df_geojson = gpd.read_file(r'../data/2022gr.geo.json', crs=crs)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We importeren nu de gemeente shapefile kaart van het CBS, om de overlay van onze stemlokalen eroverheen te kunnen doen. "
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<AxesSubplot:>"
]
},
"execution_count": 2,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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azq2FZF29Nl3U7TGuQsmoyVw/bDfSeloB+QwyF8vy/33hDh6HjM9pnYMaBdN6Kue7aqJZjWj2wQfK71IYafficshWs7hD4osPsVU0TRiIeLm9VBsUV+YS+F0Kw20eJteyNR/iSpZ1b7efu0upugCIZzV2dvq21MPa7ndyf5PkSsCt0F7uItqIi9NxRtu9m75eNevLLQ9LKyCfQdYyRVZTBY4Phrm/kmElvbVm62JpY7EngFS+ZH+oBDDc7mVsJEI6rzVdedbjdcp1j40NR7i9lNrwpnFvJY0kRF0muKJOsBkBl4LbIXF6JEJe07mxkKxrB+wLuekJuTi3BS0et0NmLr7xTW49mwlqbUYry/oMohsmfqdCIqcRzxU5NRzeUp+nQ64PlI3Y3+snli1yZiKK07HxcxVJ2H2sjWYHs1qpYRa1Gk036wSmDvQGthSMEa/KSLuXl++s8sZElEyhxJEGZzm/S9lSMAL0hd0YW8zqVmj3qZT0h3xSFa2AfMYwTZP/9qV7DLV5mVjNEPaonJ2MEctuHpilh/x0KZJkJ3EabXcrhDwOhts8jHZ4OTkUZjlZ37omCauovr8nwEDY3fS1Ls7EOdDrr3neZvSH3cQyxZoxqvEVa8j62GCo5mdX0wUi3o2TORXCHoedId4KIY+Dj7979JGGmVtb1meMP7s8z1qmaBeoR9q9LKcKaOVOFIcsODUcZmotWzfvuP7rzXAqEj6nTLqgk9xgdVNlyZrUB6Dxeav6bHVqOMxMOWuqKhL7uv1WwAvIFnSWk3mG2zx4nTKTaxuf31RFwlnunFmPW5VZSuYZG47Y2j2r6SJ9IReKVNq0t/XsZAxJWO2AUxuUho4PhpiN5fjOkwOPrFbXCshniOVUnp/+y1uEPSqBcubxjYkoh/uCdpKkOjCrP4hgSW5UAmwzVFmwmi6S1wyOD4bQdJOj5bax9VvIoTbPloN9Z6fXrv21eVX8LqVuQLg/7GY2lqNkmDjkjVebHR3eps3shmkyuZYlrxns7wnY/bZz8Tx+l7Kpqp31GtAZcNUF5M4OL20+J/OJHBem47gcEru6Hl1kuRWQzwimafITf3KV3pCLeyuZmjKA01H/odV0kzOTUfZ2+7i1+KAUMhjxbCk50+l3spIqUDJMu+FbFqCbVjbUrcqosoQswWv3ooy2eykZBtPRHF1+Z01ppZrx5QxjwxEM02RiNdMwyVOpOTpkwcmhCF+9v9b0Oj1q44/wiaGwrc+zmMyTyGt0+p32jaM74CKVry0RHeoLkNMMsoUSHX4nCFhKFOpkQk4Nh7k4Ha/aFUBeM9jT7edRaQXkM8KfXZ5nNVPkYoMZw41WPFmqPfv5NimGA4TcCqMdPl65W1vuqCQsby3WBvTJoTA3FpJ0+p20+1Si2SI9TYSsnIrg2lycdr/TDphGuFWZvpCL1++vMTYStpIrwpJsrG5+mG9QutjT5efCdK3eTq6oc6AnQNDjwOdUmIvlGIi46Q64ODsZw+2QuTr3YKSruo91IOxirKwW4FZlXr7TuCb7z//kKr/3D1/AtUkCbCNaAfkMsJzK87Ofu9M0S7nRJPv1+SS7On1MRbMc6Q9yf2XjBm6AvT2BumDciHNlrdXq1U4Soi4oK+ULh0xd43c1fSE3hmkwvmytQGcmHmRFe4JOdnb6GF9O141rVQi6lYbiVxemY6w/Ns5Ec5wcCnNuKkbI42jYiZTTDK7NW7/HqYim290L0/FHFt1qZVmfAX7q0zfp8KlNA3L9Krget2o1EJydjNkCUs1o9zoQCHvM6c3idyl2MEoCdnV6bZ0ahyyVjXMslbr1dAdcLCQab3mtx02GIm6Wks22xWm7N7Yaw7SCXanKgh7oDTC1luH4YIjuQOMMdWUWE+Bgb6jp2VOVJdwN3s/D0ArIbc5sLMu5ySiXmnSAHBkIcmdx4zPhldmEPTHRjJNDId69K0JHwIVmWEmQR6GS+h8bDiMJa4rCpcj4VJkDPQFKhknApZAr6hzpDzI2EmZsJMLYcITz083rhEKAQ5LoDrrpDbkaBnQ0q7G/t/H1m6bJcJuHXZ0+To9EuL+SZiVtHQUqAsvVjI1E7P7bwYgHsEau3A22pUXdoLCF5ouNaG1Ztzm/9dUp+sIe5hrIUkjC0p3RtiBN0WjFACtR89LO9pot6onBUNOf3yoeVebEoLUVrFxeJRN8dirG7i6fPf/YUIaxAU5FYn9voOYcPdrh5X7DkS7rl54cDiMLQV7TuTybwK3KLCTydR01JnBmXcYaoFBeHSVhlVjOl3/33m5/3VkaYCGeZ7jdu6X304gtrZBCiEkhxFUhxCUhxLnyY/9OCHGl/Njnyp4ejZ77QSHEbSHEuBDin73pK31O+ez1RXLFxlukk0MRewt6YjDE6ZGItcqMRBiM1BbfL88mGCrP8FUIumRODUfqzov3VzMkcm9+bnIo4qFYMrixkOT4YLju+5LAVkbfCkG3g1PDYfwupS6plWhw5hPCavsbafcws5bljYkoTsVa0ZK5UtP2tpJhcnMxyUs72jgxGOb4YIi75Wb9I/2hmsZ9p0Oq2fpWaJRkehieqKW5EEIGfgX4ADALnBVC/Jlpmjce6aqfI0wTVlK1wTHU5qHT7+T8VJS+kBu/S7Hv3BUUSXB6JMLF6RhF3cSlSAy0ue1RpIGIm6BL5fUGbWmxrMbII9zl3apsr3rnpmJ1Po6GaakbbKVH9VBfAMMwm84tdgXqs7Vhj8obEzEUCXugOZYr2nONG+W1NN3k3FSMHZ1esgXDVmJfTNYG2v3lNN5y+2I1jzrt8abPkFu0NB8Dxk3TvG+aZhH4feBb3uzvfB6RBJiYuB0yqiIRcCkUNJ2zkzGODIQYjLgbbp1KhskbE1FCHpXekIt8yeDV8TX6Q2729/jxOGSuzTffKl6eiTc8J22F9ZnGs5MxTgzVrpSZor6hG8/J4bBlyDOX3FAlIJHT6oxio5kiOzt9Nc+7u2Q1rm82EQPWSNXEahaHLJCF4GBfsC7JlCro7G7QCDCzwfD2VnjSluZ9wEzV17PA6Td/uc8Ppmnyyt1Vopkiw+1eopkkh/qCaLrBjYUUY8NhzkzGcClS03Q91LbLmSbs6PRyeSZOfIOyA8C+nnp3qq2wt9vfMPWfaSBY1QiXQ2Jvd6CmAVzboFl7Lp63V1qXInGoP4jLIfPlddvwA71+uzyzFXJFy+m53e9sWPttZhb7qGfvra6QL5mmeRz4BuAHhBDvBjBN8ydM0xwAfhf4wQbPa9T31PC+KIT4uBDinBDi3MrK1oZh346YpsmX767w7f/1Nf7dn18nmS9R0g0O9wW5t5xmOVVgd5ePM+UPbL5ksLtzax0iln7M6pamPtJbDKBqxobDzMVzdbOQYDUTnKxaJSVhNXpXIwnrrFYtIXm4L7hpW965ySjv3tWOQ5Y4OxlrqBvkdW6toRxgMOJmbDjMaKcX3TAJuuuDzGyyvH/46KPJQG4pIE3TnC///zLwKaytaDW/B3x7g6fOAgNVX/cD801+xydM0zxpmubJjo6OrVzW25KSYfI9v36GydUMK+kip0ciuFWZGwtJEvkSS8lCXe/mxZkY7b6NpxLesaONs5MxijpbOh9OrmUZbvNs+nPVrGaKTWt0vUEXV2bj9td+l0LEp7Kr04dTkegLuTnYF7RXnZ6gi+E2D1fmEpveHAzT2rpWZCN9rtoAGmn3cnGDUgpYJrCnhsN0BZxMR3OcmYxxeSbBdDTLUFv936vRLmBfT4CeYPNJlq2waUAKIbxCCH/l31i25NeEELuqfqyhpTlwFtglhBgRQqjAR4A/e6QrfpujSIKxkQjRrMa+ngDpvMZauohHVXDIghdGI0TW1RQ13aTN17io7VSs6Y/X7j3oB63WltmIh7Xy3uin5xN55LJGDVidOucmY9xdTlMoWaJXlYkQt0PCo8pbOu9thE+VCbgsW7tGviUhj4Ox4QjHBkME3NYYW6NmgyuzljBzNY0C8mv2PvpCspUVsgv4ihDiMnAG+HTZlvynhRDXhBBXsIL0R8CyNBdCfMa6aLOEtZX9LHAT+EPTNK8/8lW/jRFC8D8+dooPH+nh2myc6wsp2n1WJlHTTbJFnei68+Jwm4fb6xI7AbdCl9/Jjg5fXYZyfCVDX8i14XX0h90sJOozhh6HxNhIuOGKXN3R0ojcFqbpTwyGEELYxfj+sBtfAwWCanZ1+WpqmbcWkoyNhNnbE2C43dd01W7zWnpEF6fjG4qDgRWU1XOciw1mPj+wv3vD19gKm55ATdO8Dxxp8HijLWple/uhqq8/A3zmEa7xucOjKszHLUdggHxV90ej5Ei7z8nkWha/U2ZPd4ClZJ50oUR/xM35da7HFfqbNBtUWEsXKK1bVQ72BlhM5jkzYZUyKjXQgbAbVZE2lIescHMhSV/I+vk2r4qmGyTzJSZWM4wNhxECskWdnR1enA6Z6/NJTgyFWUzkCHkcCCFYSRbsaZL+kJuCVpv0SeZLnJmI4XcqpAqlmtGrakKbdC9VUygZKLJEd9DFYMTD1XWWDB861M3RgdCWX68ZrU6dbYhumDVuvtWD/muZIi+MhHm93HAdcCt2Z8n+3mBN5m98OV2jkbr+d2xEXrOcjCvnsl1dPu4sp+2C/qWZOCeGwsxEs/aw8Vaw+kldjK+kbZU5hywYjHg4MxlDkQQnhywPjsoA8fkpq2xyvpwl9agye7r8+MoloGbZ4Mq1LyRy7O8J4HbIxHNFJlYzGCYPbb83sZphIOJmNpatWe29qsy//Kb9D/VazWj1sm5D7q+ka7Z/1dIbuzp9nJ2K844dbYy2e9jbHUCVRLkMUpuGT+RKHFinUQNWguX2Uqpp0uZIf5DBNk+Nt4YiiZruGk03OT9V78K8ES6HdYacj+eJZh5suzXdtFfXkmEV5qun+YcinpqEULaoM76SrrGX24hYVuPGQpLz0zHurWRs49WtDCivp6gZLK4bK/vHH9j9yMmcCq0VchsS8qj8p28/zHQ0y9W5OJmCTqffSa5Y4vp8Et0wee3eGkG3wzK2EcIug6zn4nSsZlzIo8rIsiCVt7ZyjXRYr84l6saUJGG1pL3Z8SJFEoy2e2tW/q2wt9tPPKfVBV5lhQ+4FU6PRJiLN7ZHb0Slu2Y2lkUS1L3XjRhq89YMX+/t9vP33jG89RfYhNYKuQ3p8Dv5zlMD/D9fv4dSqcS58kq0uytAtmqrlMhpXJ7ZuCyg6Sb7ypMbQsDODp9tHXBvJY1/XSE7XdA5NRyxFeQq/bE+p+ORZv1ODIW3LCMJVnb45FCYW4upuhWpmiuzlgP0w+hK3V9Jc3okwqmhCEe2eO7r9DsZG7H+Lh1VQmL//m8d3FAA7GFpBeQ2JlMokSk+2CY+ZBXC5upsgr6Qi1PDkZpJhtV0sWFN8o2JKMcHw/ZM5Gws27Arxa3KHO4P1hT8G9HuU7k0s/UumeE2D10B95Y6ayoS//PxHG6HvKkGD1g3qTcmopQMk5lodlMJzdMjEZZTBc5MRHl9IkrY40CWBB97adje/j4uWgG5jTk7GUVRHqT8by8m6Qm6Nm0CWE9O09nR6WvYyH1lLsE7drTVPX5uKsZQm4fpaIb5eJ6eoJNTw2H7Az82EiFX1Lkym2AmmuXkcJixkTA7O7x1s5Sj7T47cCp0+Jz0VpVeFMk6K44NW9vPZp0wzSgZoBvGlle8gYibm4tJVtNFAm6lYVA6ZKsmXH1+BbizlObEYJgP7Ot6qGvcCq2A3Ma8cmelZruWKugsJPL0hx6ugwaa65vu7fZzeSZmF+wr7O8JsJDI203VCwnLKcpdNpo5WxXcblWmpBssJwvMxLLcWEjahXS3KjO+XLtVPToQIl0o1QRBV8DFVDTLmckomm5S0s1Nh6rXU9TNLdvt9QRc9rl6fDlDoaTX3Eh2dvro8rs4MxElp9X30l6ciTHS8eYnYprRSupsY67OJRomKi7Nxm1dmUfhUF+QW4uW3P5sLGursq0vO1STzJVI5h78XiEs1fD12jZnJ2Ps6/bT7ndybyUN5WaG6lGsSzMJdnb6yGl6XRlmIWFps0pCbCiGtR6/a/OPtCRgYV1hP5Erkc4ny05W8qZjYR8+0vfYMqvVtAJym7KczNcV5qt5mKI2gL7utboDTlZSOTt7mciV2NnpZLTd23BGcj09QRe9ITd+l8yXbjcWxMoWdc5MRFFly2rO5ZDqu4Y2uKlMrmXZ2+0nminWbGBdDqv31SFLNaNnzrJossshkW+wqoF1Pm33ORueT3UTUnmt5pzdjPU7isdFa8u6TfnLa4sbSv8/zMQ9UGMlDpaRan+4dus7vpxpanneH3Zzcsiaou/wOVlI5Lk+l+DGfPPM6VQ0y44OL3t7/ORLeo3M4lZpdDUHeoPcW8ngdyns7PTR4XdyvKyYcHYy1nT6xV0eNt4oWdS+BY8UePQxq2a0Vshtymv3Vpt+gA/2BZjcokVab3kla3SEvDybYGeHt0bwtzJMvJIq0BVwUtJNptayzMbq63yH+0N1zQjrqZQ6FAlbbnGr9IfdrKULdUEZK29hK6utJKz/9QSsLWRRN4h4HZR0k5ym27uAAz2BTX//Vs+g3icUkK0VchsyH89tuAJqJbNh7XG03UtfyE3Eq+J3Kuzq9GFidb5MlSfgAfxOmYO9AboCLpwOuW7eL18s0RN0cX4qxsWZONFs4w/pZr4b1ZSMB3Iem9UMO/1OTgyFiWWKDJdHnyQBYyNhdnTU+zUaJvSHPFwqZ0NvLaYoaFaP7KFyp9Lh/uCWbgZtW8xgN7Lcexy0AnIbcnkmzsSqpRXaiNtLqbra3/HBEPdXM8zFc+zs9JIqlLi7nLazpPOJPHu7A+zs9LGry8+1+SSzsRyqLNVZwLlVhTcmogy3exmKNE9cGG+iU+DsZIxjDYSvqlEVifNTMTJFnVRe41BfgHfvaufMRMyeAlmPsq7+WOnf1XSD/rB7y+JTmS34nsCT27K2AnIbcmPBCpYL0/GaOTxZEuzqtHRc7pQbx6F++j6e1RrOJl6dSzC+nK7JiCqysDt3qn8PWLL98wlLIqPR623WoN6MZip6FWZjOfaWfTJuL6VZSRdsychmJPONJUyuziXpDbo2FYiuEG+yG1hPa8v6HLGUzNtnvovTVoEerML5YjLPCyMRdpcn7Q/0Bjg+FGa6HFQHeq2pho1CpdPvZGw4zLHBEF5VYTVdoKsqmVFd7tB0kzMTUXZ2+ugP1a6WbzIeubNBY3uFagFkn6rUeG2sx63KRDcIuDOTMU4OhRnYYLWv0GzQez3hh/CNfBhaAbkNWauacC8ZlrR+xKvS7neSypd4YzLK9fkk0azGjfkkXodsn8uyRb2p8HDEozI2EqEn6OLMZIyL03Fi2SI+p0KwqoySbzBofHfZWqnGqlrF3uwKuZUE8dW5BK5y695SMl82xnHWTe4DlHSDiE8tj1g1/kifm4rRu4W64VbbEx+27LRVWgG5DanuXwVLUXukzcPVcqCZ5oMC+KmRCBNrWdvpd/0H0udUyi1pYVIFjTMTUS7PJjg2EGJsOEKHz8mBXj9+p8KLoxHCbrmph0ihZJQt7vz0BJ0MhN1lTZyHb7LtCmysWOBUZI4Phu2h60y+xGITLw9NN7m5kOLGQpKcZjDWIGhha2feK7OJuob79bgc0iM5XG1Eq+yxzSjpBvq6mqEJLKcLSML6MBzuC3GjrKk6E82ykMjjkAXHBkPMxSw3p/GVNLs6fczHc3hUuW486+JMHK8q0xN01ZQ9Ak6ZnR0+ekNuwCSvGSSzGovJPPny0nZrMWUN+2Y1cprx0OWMnZ1eYtkisiQarrI7OrwUdYPz5dGxc1MxnIrE2HCEpWSedp9KwOWoy7ZWuLeSsVyao1lKhslA2INDlvBsMTPaFXSR2qBh4UltV6EVkNuOtUyxTlwq7HGgGyamabK7y2/X/nZ0eO2so6abtn5oZWh4LV1kLp5njnxD67a93QGKeu32NFnQOTcVpTvoZHy5dlZyX48fryqjG3B3Kcne3iDnJmMb2uE1omIzNzYcZi1d4N6q9XsqVucl3bATTYXy2bCyOisSCITVa5vMN9TpWcsUWcsUeWlnG6+Or9UkdPrDbroCLq7PJewbjCwJQm4Ha5kiTkWi3acyF5ObagQF3U9muwqtgNx2zMbqdWl6Q257sNdRPiwe7g9S0HTb/ns9e7r9OGRBd8CF3yXX6d2cHolwbTbO3t56RYF0QSedKxFwySTzDz6UNxdSnB6JcG4qiiwJYpki79zZxtlNmgMa4VZlErkS+Xyed4yEuDyX4uxkjK6Ak6lo8wSOFUMmK+kC7V6VuKQ1nPw/ORTm1fF65+VKg8O+Hj/3ljP8+289yEs72+kLuZlay9AVcFHSTbxOmS/eXuZnP3eHNp+Td+xo48t3V3h1fM1Osj0JWgG5zZiOZmsszRzrtnXnp+P0hlxMrWVI50scHwo3DMjeoIsv3l7BpUhoJZkdnT7ShRI7OqxtrG4YqA7Z1qlZz2KqyOmRMG9M1H7/wnSMgYibmWiOeysZSoaJy6FQKDU+d1bjcyrs6fKjGQaryTwht4zfFeS1qt/R7nM29X2soEiCe8tpirppq5Z3+p0k8xoOWSKVL216XizpJr/4kaN88FCP/Zitv1peAL9mbxdfs/fBiNX3v2eH3SX0pGgF5DZjOVmw7/gOWeBSZKbWMjXb0/kqtbi1dJGjAyFmY1kiXpU7S2kUSdjOTPmSQb5k4Ixl8Thky1TUIXOuiRpdNW9MxNjT7eP24oPzlKabeNUHH5uptSzv39tZUwfUdPNBttK03ofPpZAt6OiGgU9VmNNNLswk6grsNxaSOGSxoVbOSLvXdqVaTOQ4ORzm9mKKAz1BlpJ5+kKuTacp7y6nefnuak1AboWw98mdH6EVkNuO2VjO9uk43B+0ZRybGd9MrWXY2xMgV9QJd6js7PQRdDtI5DX29/jtXtKAW8XjNLlYJdO/FYolA1lYkxAV7q2kOTYQxKFILCTypAolbs4nbdnK9+1u48xkjFzR4MRwGNM0+Ztb9fYQzdyvDvUFG1qVV856vSE3sWyR1XSR6WjOrsFuZPTaiN7gxpnep0ErILcZC4kc0UyRHR1eXIpMh99JrqhbyuWSqDNnPTwQspM5umEN9d5ZStMfdpPMlxht9+J1KnU6oltlYjXLsYGQHche1XIvRgjOlLeaM9EcQli9tO0+laxmWPYAQRcFrdS07iiwVPSWknmS5V2BacLtxRSH+gL4VAUDa7g6p+lMrWVYyxR5+c4KL4xGMMw0qiwRcCubdvI0YiGZxzBMpIcR5HnCtAJym6GWNUrvrWRq+jYTuWJdMA63ebhVJRx1biqGLKyEzvRallShxNGB4COLMFXs3twOiYGIl1uLqTp7OdO0jF6rSxHRbIk9XX4iTbZ5ZyejGOaDlVJVJAzDpGSYXJ1LMjYc4cxk1B6YrmY6mrXVxheTVpKqULJKRqoiUdLNTZ2Zf++NaRI5jZ/9jiNPrK74sLQCchuRLVrF70YK4OMrGQ72BpiNP9jSVhTLqzk6+EBQ+PRIhJymc2k6XnMGfRjGhiOML6cYinhwOWR7IDi2xZ7P20spDvcFiHgcdRYIhmmNZcnCUiDvCDhxyBK6blLQdWbj1ntLF+oTRvPxfM17Wi/CFfY4mko8VsS7vvPkAO/Z3UEypz1bASmEmARSgA6UTNM8KYT4GeCbgSJwD/iYaZrxrTz3sVz525D7K5m61exIf5BUvkTI4+DKbBy3quBSJI4Ohnj9fv35q7omeH81QyxTwO2QyRRKtrT+VpEFzCVyZIsGa5nawN/Is3E9V+aSvGM0wmsNrjfssdoBZ+O5hu7DgxEPtxYbb0fbvM6mN5lYVmNXp89O/lQjCcHLP/Zegm6HbXW+XXiYvcz7TNM8WhVQfw0cNE3zMHAH+PGHeG6LBtxbSeNRZU4MhTkxFObUcJiA2+pIuTAdx6nIeBwSRwZCxLNaXbP0ni7LWGYw4qYn6GQlVWB/T5A93QEWk4WHFmVq9zvp8DkbFsjX+2lsxnqX4wor6cKGq9NGCntLDQxvqmm2Vc5pOp98Y2bbBSM8wpbVNM3PVX35OvC3H/1ynm8uTMW4uU4Y+ORwGFkSdPpVHLLMUMTDl8cfaNiMtHsIeVQ03cRZniN0yIKDvZYNdyxbtFu9rswmmmY2G7GaKtDRZPrhYWchZUlwsC/Ajflk3TaymWwIWCtdI3Z2eu3sajNuLiSbOh1vZOf+NNnqClmxND8vhPh4g+//feAv3+RzW2BtNePZIl5V5uhAiJNDYQ70Brg2m2Ck3UN30M10NMvKOtfhidUsF6fjuMrBCFbmspIVXUjkWUkXONJvdeScKzeHb4ZTFhzsCzY1sskUdXsaYyskcyWuzSU5tU5Y+MXRCJOrGfv61tNslVuI5zfdNifzJd6YiHKwN0Bb1evIwhpl2448kqU5gBDiJ4ASlq35Qz23mufd0vzCVIxETiPkVknlNc5Nxbg+n2RXl4/VVNEubcxEs4wNR2omEgYibkzT5GBvAFlYzQCnhsMc6gvy4miEXLHE5FqWDp8Tw4SVVGFDzdNjAyHCPueGWcpcUWffFpXXjg2EbDu4a+Wxql2dPk4Oh/nqfWvW8vJsoqFCQrLJ5EmmqDPYJKhcisShviBH+oOcHolQMgzb2/HkUJiwV23a2P60eSRLcyHE3wO+Cfhus0mH8Rbs0Cs/91xammu6wT/6nXN8z6+/QU4zyGkl7q1k6Ao46fQ7cTlk4lUfykxR58xklJDHwcmhMAf7AnQHXJyfjhP2qBwbDHN/JcPZyRipvEYsp5Ep6BQ0nTafisBqvu4Juupm/7wOieODVs1xIz8NhyzY2+2zbxIbIUuCDr9KoVyMzBR12nxOxlfSXCiv6Bem4zgkwYXpOCfLo1Mhj4N372rH7bCavRtZBDjXrdA+Veb4YAhVkbg6l+DybII3JqLcWkzjUCROj0RYSRdYTRf5vTem+c5ffY1rW6zPTq9lHyqR9WbZ9AxZtjGXTNNMVVma/1shxAeBfwq8xzTNhk6dzZ77+C7/2adYMnj9fpS9PQFi2SL3y1nDpWSBd+5s46sNMpNg+XKspQtkNQN/eawoX9JrxqA6/E7OTsbY2ekl6FaZiWY53B/k8myCG+VG8cr5am+3j1hWa9ghsx5NN3GrW0s/vDga4fpCiqE2D4uJPJmizlw5m1q5g3f4nSwm8vicsi3ulcqXuDqXqDlDjrZ7ccgSt5es0kvIrbKvx8/Nci32QF+Q20spu8mg4tbldypcmonXtOPt6w1wZiLKt/zKq7xjRxvtPie6YSIJ+BfftJ/2qrOzaZr80Ccv8APv28nXHXh0l+SN2MpftQv4VHkkSAF+zzTNvxJCjANO4K/L33vdNM3vF0L0Ar9mmuaHmj33CbyPZxavU+FLP/pevv+3L3BxJl7jMPWV8TVODVt1xfW7q5yms7vLx52lNG5VIdVAnKliY7cYz9sjT9XOTW9MRDnUF8CtKpydjDZ0txpp99rGqtUoW+hu6fA70Uo6c7EcsoCA21FnHuuQBTs7vEQ8KjcWktxbTlsDxkKg6wbnq24Q91czNdIfZyajHOi1zsM+p8JyqkBv0EWn30m2qONzymSLOvGcRsijslIeSzs5FOZ6eWXUDZMv360Vev7zKwucGAzzbcf7+MD+Lr5wc4nLswk+c3Xh6QfkBpbmO5v8vG1p3uy5LWqJZjRKhoFLsRTgJlYzhDwq8azl9ntyKIxHtT5cmaLOdDRLKl+izefkqKqg6TrLqQKSEPQGXaiKxOSa5bHRFXCiKBKUA+H6fJL+kJvZeI4dHV4MEyZXM3XBKAk4ORTh/FSUowOhmk4ZITbXLx2MeOgKuLhT9vXQTeuxWLZ2i3ikP8RXqsakMkW93JYXRQjLxk4rGdxbSZMp6kyuZRlp99Dpd1Es6bgcMu/e1c65yWjDGwdQNrN9sHOQJdHQVbrC8cEQmm7wiVfu84lX7jOfsFb01+6tsZYubFl3583Q6tTZBvzvi3PkNJ2cZnC2LMg0n8gR9qhkiyXOTMbsIKrQF3IxG8syE83hd8qMDUeYjWZtMaj+sJvhNmtS/ou3V3DIguODYUxM8kWdnpCLO0tpEjkNhyw4NRxmOpplKVmg3afS6XfZg9CXZ+IcHQhyaeaBhEiH34mmGywk8rYoVoffyUibp3w2FVydS9T4WV5eV3Y5MdhYaaBUPquZJnbmeDDiJlMuc0ysZplYfXBK2tPtJ9ugLjoYcdMddNcNMW9WspmL5RqKai2nCvziF+7yb77l4IbPfxRamjpPGd0wubmQwFUlWCxJgvl4npDHwVx51Kon5MJTpZczF8/bU/WpgpXomav6EGWLOneW0lyfT9IddDEY8fDGRBStZDBeTvpUtHM03eTsZIy1VIH37u4gX9TtrChYZ71rcwnbz+LYYIhzk1FmYjlGO7xEvA5ODYeJZQpcnrH6aQ3TZH9PoE6Uai1dwO9SeNeu9qaekZmCXiemHNhgSj/QwGDn9EiE6WjOWmnLjwXdDqv/dzFlZ10bMbBBSeR/nZ/lZz5766FVErZKKyCfMq/cXSGeK3FuMoYiSRzuCzBT7mWdWsvaY1dnJ2P0bVI7c8jClk/c2eEjmikw3OYhndeYWM1wesRKsGQbbNcGwm52dfv50p0Ve4yqmpJh+VOODYe5PBO3x7EcsoQsLBOd0YiT4XY/r92PcXYyxrmpGNfmkzXnPmuW0uT8ZLSpYHK6UKo5M58qS300wuWQGsp4VJc0rswleOfONmQhmCsbu/a8ydGrbFHnV754jwsPOeq1VVoB+ZT5nden7LPPaIcXl0NhobzSDbd5atrWNnLDAivRcmoozI52L1dno+zpLntZmOBVZa7NJZpaFKQKpU1b0UqGpXHqKstOdgecGEaJzoDKicEQc8mSnQGtkCvq1nnXq9IXcjG+kiaV18lqlunNni6fLffvdykcHwzV2CTs7wnUKLBXc2o4TLFk1DUvjLR767bCmm4SzRbRdJPlVIGLM/GaBFc16//KHlXmYF+ATr+TnqCLY4OhNz3OthmtgHyKLCXzrKWLdvYvmdOQJMtEVRLU+TNu5tad0ww0w6Q76CLic6IbBoYJIx0+UgWd4Qb25RXiWY2+0Oa6pV5Vpivg5NRQGK9DoMoK1+dTnJ+Oc2CdJUGFtUyRoNuBQ5HqVufbS2muziU43BekK+AiU9RrZCjThVLD5oCg28G5yfrsM8BMNFMnBbm6boXVdNPetsrCMjDyOxX6Qu665JCqSFyfS7KSKrCQyHNxOk4iu/Um/YehFZBPkd95fcpOMHT4ndxeShPPakytZXlhtK3OzGYqmm0oFFzh2ECI1++vYZjQ5XdhmiZdfifRdJ7TI+GGxfVqrs4lN3x9gJEOLxOrWe6vZQn5XFyucuiaj+ea/o6lZJ5krvmH+MpcAkUS3F6sXWGno1m8ToXD61rriiWjzs+jguXKVbtCNlKKcyqWnMnRgTDX5pKkCiXm4jn7BlmhYt9QiX2vKvNtx/uavpdHoRWQT4lCSef2QpJU+e4/Ul693A4Zv0vhtXtrRDO1K4OmW05WL462cXIozL4eS1nOyoo6casSJ4cj3FlKEfQ4iPicZDWdhWQBw7QsBE4Oha0kzFCY9+5u53B/sKZj5/JMfMOEx7W5JCf6A+zv9nN5JsH+ngd9sYZhyVQ2Il8yNhRUHoq46W4inpzKl+okTHKazsFyksmnyuzu8hF0KxzpDxLNFBmKeKhu5Fkv/nx8MMS5qRjdQVfDecuQx8HR/hDv2d3O7aVUzTb2Gw71bJj4eRRaAfmU+NNL88TzJSbWsuzvCeAQ1ofErcq2rmojTNMa2D03FePmQgpNN9lZ9vl47V6UMxNRgm4H6YLOV+9Z/z4xZNmI31pMkcoVSeY05hN5zLJj8NH+EHu7fPSF3PSHPfRssnUN+Zx8ZXyVroDT7vhxyAJZElyfT3KiQbLm+GCo4TmwQlfQKutUr7AOWXByOEx3wCqxrF993apCp99JupxRTuRK3FhIMrmWZSqaZU93wL4JrB/xUiQJTTeZWM2wkirwwmiEkXYryCJelZDbwaXZOC/fWaXNW3vW/MaHFMZ6GFp1yKeAYZj87utT3CkPz94ojwmtd7tqRFfAid9Vu/3KawZCCATWtipf0u1Zv9lYDkUSuB0y09EcEa+DiNdJX9jNQiLPfDxPT9BNm1ehWDJ5ZXytqSI4WPXN1XQR3cQuybwxEWW4zWOrF8jrahb7e/x1VubrmVzNsFwODN0wyRV1bi+lOFd+3mKyYK2iZX8Otyrzpdv1QwjV7XHX55OMtlt+krcWU5watvp8B9s8XJmLc6A3wPX5JOlCiUROwywr5I12eLlZThTJkqg5fx7uD/Ke3U+u17oVkE+Bv765hMsh2+n6Nq/KWqZQ1httHgwOWdATcDNXpcN6ZCDIpRlr/Or4UAhZEuVAMXlhJEIiq5Eqauzs8jG9liWa0SyznfJKenTAsh/o8KuosuDdu9t55c5q02sYbvNQKBl1jQrVUiKZdXZz84l8Q4Gu7qCLdL5EulDCUd5fvn4/yq4uH3cbiFZNRXNMlWuvm924hts8+JwK+bLGrWlaQV5RNQfrJvDOnW1MrGXtfth2n8q5yVjZTsGFbpg1QtBHB0JPVBSrFZBvMaZp8t+/fL8mebGjw8eNhSSH+gJcnGmcTj82EGI5VeDSbLxmnrGyEh7uD3FxJmavEDvavdxZSpEpliiUDLoDLobaPFyZTeBWZd6zq4O5uDXBMBXNki5oHOoPkc6XeO/uDr50p3b16Qu5GGn3IksSZyetVreIV2Uo4mElVagJzkLZ7wOsJodiyeDuUgqfIjHc5kWWrdV8LV0k5HYgi1pHrKBrc6n+c5OxhsPWA2E3blW2Vej2dPltQa71otCZok5eM2pucLu6/AxErPP9+Ir1Ggd6/dxaTKMbJnfWlXUeN62AfIv53I0lZCFsMeSdHV4uTEUplVXbGlH54Ams6QndMHEpEkXdoFgyGG7zcHspVbNdi2aKuFWJaNb6pF+aSfCOHW2cHolwdznFSrJAwK3Ydcm1jEauaE2LjLR7ee/udhaTBTr9ToSwBp1fvx+taTuLZopEM0U7MKfKDQ2z8SzzcWra2Y4MBLk+l2ioCxvxqKSrVtVGIl/rMbFcwaonVsaGI9yYTzATe1BaWV8XrSbodtS10elVHikVrs+nbMuG1+9HOT8V5cRQ7aD146KV1HkL0XSDX335nt2ovaPDy3wiz+7uAD6nQmJdWcCpSDWrwOGBIF+9H+XMZIyQx8GRfqvpe3ItW5dFvLeSqRkhKhkm6YI1QS8QCAEhj8p0eXVwq7L9wZ5YzbCQsCbyX7m7yst3VlEkQckwG9b9opkiDkWyW+UO9ATqfu7yTKKpPmt/2F3TsLCcKrC/J8BmggT7e/zIkuD0SIR37WrnzGS0YZdRM0bbvVyYjuMudzcd7A009CkR1DZlfO//PGdLUD5uWivkW8ifXJhDkQSFkkGHz8laplgulJsc6gvUzD5GPA4O94dIFUqcGg6TLeosxK16omFaQdBotQl7HIyUP2jrRZyUsqLdWqZoZ0ZH2r3kNR1JCPp6XXb9LuB21CRibiyk2NvtZyaabTgp4VIkrs0nUSTB7i6/7Sy1FW4uJvGqcs3rFnWDk0MRdNNEKtdljPK/i7oBJjXv/8AW1QsqOGTB/VVrS7q/J8BsNEu6UGpoQeCQBRGvyvv3dbKULPANB7sJPSEHrFZAvkUkshqffGMKWRLs6/HT5XfypXLy5MZCihdH2zjQG7B6PQXcnE/a57iDvQFURUKRBefKrWvNxocqwQjUdJw4FYlMVUva1FqGeFazA0eVBW7Vkr6YWsvgckh1Z7RbiykO9we5UiXt4XJYz6kEb8jjYHrt4fRfNd3k2EDQni4BGF9OM6/K7O8J8MYW3LWuzzcXtGrEaIeP24spJAG3FpIbjmMVdZNvONjFD71/95Ze+1FoBeRbxP/3+Ttohsml8oe53eusmdPTTcO2nKumu9xONlH1vQN9wYbKcTs7vXa2s82r1hT8LVXvB/f/npC7xpH42GCYaKZg92i+cT9KUTc5NRyuWSmvzCY42BvA5ZAQCHTTrPn+arrI2EiY6TWrw2ar4szrW9vAuhHNNLDna8bZyWiN7UEj/C6FkbLywMFePyXDasbY6DkeVeY7Tg5u+ToehVZAvgVcmI4xuZpmfPlBaj1Z0ChoOscGQqykC03rdD6Xwvg6sd8zE1HGRiI1U/4Cq9hdOdusZYqMtnvtJoNOvyXsZMnsG6jlIntP0IUiCc5ORjk1HMEhZdEMk2L5zFSJ6Up/rd/l4NZiioBLYaaBDZ51fZX3UmgqVryeypRKNbGsxsPI2BgmzMVzRLwqiiSIZ4sUdZO+kIu5eJ693X4mVtM1KzxYCadKDXc9siT43neN0v0WGfOIJzXX9SicPHnSPHfu3NO+jMdCplDi7/z315mJ5ej0O5lP5PCpMv0RqyzhVRWSeQ0BthZMBbdDolAyGiZSAHpDLpyKxMRqtqGt+KnhMAJI5EuEXA576+dSJEwe6OhU65tW/DQqVIalO30ql2aTSMIK4rn4xpMhFQYj7k31UytUfCer2d8TYHw5Zd8gtkLlbyEEeMrb+0oZxumQODcZpVCqfb3jgyGEEBRLOrcWUmiGyc995xG+8XDPExFUFkKcbyQc3lohnyCmafLP/+QKumHaJYLeoItdXT5eLp8fBZDXdEuwqduNz6VQ0q2fz2k6+8JuMgWdoMdRt02dj+c5PRKh3edsuMJWHmv3qUyuPlilKudGw4SIx1kTMAvJB//e2+1HN018ToWc9uA5WwlG60wq0+V3kcqXmgoeV9PhczIfz7Ov228r5CXyJToCLtwO2d4pyMKawMg1UAkYinhslT7TxD4bnp+O2buJRvbu1V97VJl/8cE9fNvx/k2v+XHTKns8Qf7na5MsJAs183rzibzl+FQWDO4KuDg5FMEwTdYyRc5Oxrg4E2cqmmU5VeDaXILpaIaL0zFbi3W4zcOp4TC9IRez8Rx3l9OMjTyoi63XK11NFzk6UN/Z4lRk1CoVgqDbYa9QDlmQLpS4OB3nzlKaWFajq8n8YAWHLDg5ZF2XW7XKOGenYsSyGqdHNq/b5TSdNq/Ktfkkk6sZkvkS1+eTzMVyRDMF2/tSliWO9IcajqNJZav19TzMRjBb1Guck99KWivkE+IvrszzlfEVzq3LEO7o8PLq+Conh8Ic7gsyvpLm3kraWh0a6LgUddN2Sx1qc2HGszgdct2KeHYiyomhMC5F4qv319jZ6cOjyhiGiaYbSAI8DqmmWC8JwUoqT4fPyUq6QFfAya6y9Xm6UKqxSs9pumUrUD6TuhSJ4XYvQbeDQskglde4v5ppqJED2LqszYh4VQwT+8xbaZM7MRjm/HSMaEYjmtGIeFWO9Ae5MBPH53IwFLFa+SoNABVlhLUm2VYhrP9FPCrRJg5eL+1so3+DiZcnSSsgHzOmafK7b0zzpxfnuDAT59Twg1R8yOMod9ZYHouKLMgWdQ71Bbg6V59hrWZftx+PU6ZQcjbUkDGxWsPGhiMYpmX1relGzVnJ7ZDxqbJdPI9mi0ysZjnYF2CwzYOEydkmAXViMMzd8oe+4td4a3HrbWRXZuM1Dejr6Q25uNbgb5DTdA71BSkZBpIQZAol+2ZULBlcmUvUrb6V/tVGWMJZcWRJ2HOO/+qb9+NzKhimtV3d0eFDrFeRfotoBeRj5vp8kt/+6hTziRy6YbKQyHF6JIIQD4Z0hdBJ5q2CfzQT2/Q//vHBEEvJAjfLAbA+8VFNuqDR7lNZbSDTmNN0xoYtacfRTh8T5ZLEtbkkgxEPgxE3AbdCMmdJbuzo8KEZBlrJIF3QEJLgvXs6WEkV6tQMNsMwrczvySHLPGg+nrOztEG30jAYwZqE2dFudTQ1cuECq9zxrl3tzMay6AZ1Q86N0A2Tu8tp2n1O3rGjvW5C5WnRCsjHSCKn8a//7Bqr6YLdqzodzZHXDEIeR410oVeVkYVgd5cPf4MVr5psldp3heqVDrC9Km4spDg2GGoYkGCJC+/q9OFSpAfyjT4nqmy5DvcG3UQ8uv2zYKnMXZ5NoOkmXX4XPueb+9ik8iV7S7ury2c/vqvTz1w8x0DEw/hS2t5KhjwOFEkwHcvW9OmuZzBiOUmvNyLaCt9ytHfbBCO0AvKxkdd0fuSTF4hmNHu8p8JIu5dMocTebj9uVcYhCy5MxXi96pzjdlhZw73dPkwE40vWlvboQL2dN1jNAfnyiuFyyNxeSrG7y2ptWz9dX83JoTD3llPs7LLUBvxOB06HxFw8h9f5wCH5SH+QsZEIa+kCC/E8J4fCTK5lOT8d41gDU5ytIoSV0HIpEnOxHDs6fOQ1nWxR58xEFElYN4Cr5S3upSbTL9XMJ/KbZm1CHgepfMlujvjafV186FA3H9j/dJI3zWgF5GPANE1+6W/uEstqdQJJ+3v8uBwyl2fieJ0Ku7q8nJ2IUX3Dv7OU5j27OlhM5nHIllGMJCxV72atYEvJPH6XgltVuLWYJJEr2WURjyrzzp1tfGV8jbGRCCXdwDBNCppOoaQTy1nnsGMD1vxkZdWqdruq/Lsn6LSGd/EQ8aosJPJbshFYT8SrEs0U2dHh4/p8grxm0OF34qlqagdrazuxkmFfT2BLwQjWWXJvt6+p0zJYY1iTq1ZL4Ewsx7/5lgNbEvV6q9lS2UMIMSmEuCqEuCSEOFd+7GeEELeEEFeEEJ8SQoSaPPeDQojbQohxIcQ/e4zXvm34pS/c5fM3lnE55BrdmLGRCDcWUiRzGkG3A900ef1+DITg2EAIsLJ9Ozq8zMSz3F5K4Vat/ySGCePLVsawbZ1HYsClEM0WuTqX5MxEtKZw3el3MrmW5bV7a+zp8lMo6VyYjnNtLsnEapZ0QbeTIBdn4puqeAdcKgjB6/ejzMVzvLgjwv2VzKYlkGpODIWtiRBJMF4+t5UMEyFoeMMZafeymrY6jbaKaQpbXNlSaQ/Z3+v0O7k2l2ApVWAqmmMw4uHmfMLWv91OPFFLcyGEDPwKljfkfuC7hBD7H/GatxV/fWOJV++tcXspxc2FJE5F5vRIhKMDQUT5w76WKTAYcTMYtuqDumESz2kc6gvgdEjcW8nYQ7mCBwHdFXQyG8vRF3bX+DmOtvtqFNwM09LVqbCr00e7z2lN7pfjzaPK6KalIXNmMmqvDnOxHC6HhEO2fEHWc3spZSsbKJLg7ESUtUwR7ybnXqj4g4TtweCKYkBFCnI+nmcwUr9K3V1OoRsm91czWz7f3V5KcaQ/xGi7h4hH5cJ0nLGRCGMjETTdqGkeD3tVvve3zvPe//wlfvR/Xa7RgX3avOnGANM0P2eaZuWdvA40amsYA8ZN07xvmmYR+H3gW97s79xuLKfy/OrL9+wPXDJfsl17L80kcKky79ndTjqvc3YqjquqXzPscXB1LmmLIjvKo1FvTEQ5NRxmT5efdp+TuXiOK7MJfE6FU8Nh9vf4UR0SRwdCdq0s5FHxOS1vRNO0pjIiXgezsRzO8nnSNB/ozZimdaba0eFlKVXgaH+IowMh5hN5DvUFGpZVAPb2+NnRaakVGBtkWU8Nh5GEtco30lRN5jRUReLYYMjuEhoIu6vEsSwdm5ND4YeS7L84E8fndLBUrmWembBEv9Zb2l2djQPWjfF/nZ/le379DRYSW2vve9Js9QxpYtmSm8Cvmqb5iXXf//vAHzR4Xh8wU/X1LHD6oa/yKVMo6bxxP8rf3Frm9lKSYsmkpBv4XQp5TW9YAjg9EuGVu6v4VMXWi6kYfkoCFtephGuG9T0hHrS8BVwKRweCOGSJlVSBa3NJcpqOyyFxoDeALAl7BVp/BbcW05wYCpEtz1MqkmA6mrOztdfnk3T4VF7a2UYso9leHlfnkrT7VI4NWlo7lUJ9V8DJuYkYumkyNhyhUNI5Phji3koawzApGSYDEQ+dfifnp+N2/63PpXByOMxiIm83GuRLBu/d3c791QySgN1dfoolg/uraevGMhQiW9AxzMYD0ZKwssqNMq+brajtfmedMsPF6Tjf/Euv8tv/YIx9PQ83V/m42WpAvmSa5rwQohPLD/KWaZqvwKaW5o3+Og1veUKIjwMfBxgcfGtGXbbC39xa4l//6XU6A5bjcDpfIlvU6Q66uDafxDRNgm5H3cT+fDzH7k4/JcOwR5AUyZrUPz4YrvOGSOdLjI1EyBV1ewTKgIaJjbxm4FUVbiSTTDUptFdeczFZsK/tQG+gpnyyki7Smy/Zg7oVEjmNQSCZ1xgbjlDUDdwOyR6grpRDPKpMsaRTMqx5yztLaUJutcZro9IjeqQ/WNP5c30+RWfAyeE+lUuzCdp9alnVQOeVO6sE3QoHeoN4VBkTa2VzKhJyWQhsIOK2E0/VdddNbcqbfHs1XeAbfuHLXPyXHyC87sz+VrKlgKy2JRdCfAprK/pKlaX5+5tYms8CA1Vf9wPzTX7HJ4BPgDXtseV38IS5uZCizeesE0iq1n3pCToZaqsd3A24HSwl86ymi4y0e+jwuTBMk9PDEfKazvHBMELATCxHwKXQ7XcxE39QKB/t8HFxA0OXr95fY39PoCYzClYCwyFL9IXdzEZrpT3uLKUYG4nYkotH+ssf+Kq/9o4OL2GPisshE/GqNZMfh/uDGKZpF/GzRd0eWK60xglMjvaHuDwbx8TavnqdSp2FgFuVCLgczCcsXdrZeJawR8Wrygy1eZmJWomp6msXYE99SJIlPuV1KkysZHn3rnYKJYNopsBY+W8sS6K8mkoYpsliMk/J2LiFL5otbu+AfBRLc+AssEsIMQLMAR8B/s7jufS3hvl4rm4ecT2WALClfep0SOzu9HNzwZKmB8uePOxRmYvlWEoVambvAm6FxUSeWFbDo0qAIJErlbdszX+nppvMxLI4ZGvrdnQgyHKygCwJZmK5ukaCynPuLacxTJODvVYw7+32IwurPONxKtxeTDUdKq7ccMaGI0yupVlOFVFliYGwpToezRa5Mpcgp1nCW0IIzk7G6koSh/uCqIrE3eVUeWXL4XPKzMVzHBt8UOqpVixYvz1dTRftVfFAb4BXalyQM3T6rUxutfbN3i5fU8v2XZ0+fusfjDVVT3+reKKW5qZploQQPwh8FpCB3zBN8/oTeSdPiMVEnn1bEPpdSOTZ0e6l3a9yZyllB+OxwRALsRx3FlPs7vZT1I2aJEMlW6obJmupIiMdXryqXLeNXM/OTh9+p4JTkdAME0nQsDl9PaMdXs5OxuxrkIQgqxncWNhaX+pouxeENaUy3O5jJZVnMOLh3FTtjGF1z6rboTA2EmE2lqUn6Ob8VIydnT5Gy+UNsCZPDBOkqlPOmYkoxwetWqkJyFXaOpX/Hi5Faqj07nfVqxW4N+gw2tPtpyf49OuST9TSvPz1Z4DPPMI1PlXmE3k7o+hTZfb3BknmNRRJ2BKITkXi/HTcksJXJLrK83vtfieXZ6wEx/6eABem4xztDxHLxut+jyQgXbRWxQO9gTqzmGoO9QW4tVgr++hUpIZzftUMhN0USzrtPhVVsT76mm5s+rxIuSnexJKqDLiVmmb4+XieIwNhbpcbFNZTkceIeBzcmLdW2fHltO3NAbCj08eZiSjX5uIcGQhyuXx2Xn9dDlmgyhInBsOsZQp0BVx1tcz9Pf6GN5jbC8m6AWyw/vYfe2m46ft/K2nNQ27Cf/z2Q/SHXbw4EsHrUri/mubWYopr80nmE3mKusH4SprTI5Ze6krKUiAPeVRuLiQfZBudVvnB0cBwZjDioSvg5PhgiBvl113fL+ooyx0ORjxcnUvWbeEKJYOVdIGQp7kaWtDj4M5yhtWyBd5cPM/d5bSt6raeseEIfqdCb8iNLEt2LW+9unqhZHB9LsGero0zlI51Q8XRbJEXRiOWKkF5i53VDC7PJBgbjtjyjNVoumnd6GZjTK5l64JRkQSeJithVjNYTuf5t99ygBdH2wCr/PRrf+/kE9NZfVharXObcLg/hNfp4Au3LAW4k0PhmsZt3TBJl2uPe7v9TEWzXJtPcmwgxO4uP8upAh0+FbdqWaqtz8aClSDq8Ds53Bcg6HHUZCOH2zwE3A5bU3UjZqI5jg6EyAf0utGoPV3+momK6oA+NxVjbCTM+ckHLX1H+0OcnXqg2VO57h0dXiJeFdtJRAgKmjW9spZp3NztUWX6w27m12nwzMfzlHQrS139nr/tWB8vjLbx3S8M8pN/dr1ObcA0oSfobqjp43UqXFyXgPM5Fd6zp4P37u7gW472oSoS33y4l//wmZv86NfvofMpnxuraQXkFrhWLkM4lcb+hUcHQpyftuYDK1KE1SpmK6kCbHJGW0kVuL+apaDpvHd3B3PxHHnNmvJoNkPYiEszcU6PWM3bFamOsZEIS5sUvs9MWNL8F6aiHB96kEzZ2+1HCOv/85pOIqvhcsispgp2AR6sQL23kuFAbwCPKnNvJWMnVA70BlhNFxENaoSabtSt6q/eW+Vbj/fxrl0d3F/J8AtfuFvz/elolrGRSMOATOQ0ugNOFpMFBiMe3r+vkx95/y5CntrMadir8jPfUXcSe+q0AnITKpPwAIWSyf4enx1sblWmw6ciyxKysAb7zXIG80bVdrXCicEQsiyRyBa5vZSmL+ymw+dEFgKXQ+LVcpr/7nIKTTcIelSODoQ2TSitZzae41B/kPHlNAMRj2VVsAX1tpsLSXoCbjsYO3xOptaydXOIox0+rqes1VaRoD/soc3r5N5KpkbKsifoZLTdx+Rahrl4nhdGI7YC+KWZGE5FRgjBxGqGF3dEOD8Zo6ibLCUL/PLfjDM2EuGj7xhmNmYNWxumybt3dfBHF2ZrOni+a2yQmwtJrszGafM5yRR1fuhrdvK97xwluMEWfjvSCshNuL1krXqmaZUqZmMZDvcFWUkXGAh7ODMZZTqa44WRCCXTbJiMqSRNltMFe7i43afSG3DZE/o7O712CUMIwd6eAGcnotxtIOTkdyns6fLXyWXs6fITcCvohonASpTcX8lsKRgBQm4HPUE3PreC2yHjcsg1tcAK1+cT9k5AlgRT0SyBBgY5C4kCkpBsUSzdMO1rPjkUrulKcio5/uD7XuSHPnmR2ViONyai/Nxf3+HHv2EfP/udtSvZVDTDH56brfp7we9//AVWUgU+dWGWoXYvHz7S+9Sm/h+FlgxkE24uJPnDczOcnYjiUWXyJYO1dJGdHV5URbJ1XirIAtp8zoYpeEUSHB0IoSoSmm5wZSZOQTdrsokdPicjHV5ciuCVu1YQvGdXO1lNRwiBxyGTLpSsRumC1TNb+V395Trg1bk4hZLJcJuHdp+zqb7NVvC7FDwOuWZbWs2hviBr6Tx9YQ8XpuO0eVUGIx7ShRITq2l6Qx46fE7OTUXtncLBvgA35ut3Dh99xzAfe2mYoTYvxZLBdNRqXEjmSnzwYHfd7zYM0xazevGnv0B3wMWXfvR9b/q9Pg1aMpBb5K9vLPHrX5mgoJXQDJPrC0k7sbG7y4ciwdmpGD1BF8NtXu4spSmUdDTdxDQfDBpXUyqvDKdHLL0br8vBjoCLe8sZBiMe2n0qPpfCK3dWkURZT1VYfoo3F1I4FUHY67QbFHZ0WALII+1ejHLniacsuz8dtc6clWsebvMQ8ji4Pl+fma0gS9akx2w8Z5uWdvjUmg6esZEIsWyRu0tpjvQHcTlk2roDtmnqcqpg3yBURSLicdSVFyZWMoy0W2fNf/lN+zk+GMIwse3iKs/d2elnZ2dja3TA9mcMe1Ve/adf09Ag51mltUKWMU2TX//KBH96aa4cZI33eWGPg/09AYq6TiJbYmotQ8ijki8Z7O7y1Zz3VFlwoC9IsWStahslZzr9TgTYK9Lebj+LiRzxqrpepcMlli1QKFmWdN1BF18Zr91Whj0Owl4VhyS4XfZJHAi76Q25KeoGqiwRyxYJuVWS+SJep8L5qbjdBjc2HAFhnZ8LmtVEf2MhiUOWGO3wcruqBtoTdBF0O+qyulZLnklOM5AlQYfPyXC7h9fL/bA/+vV7+IH3NSxlPxe0VsgN0A2Tf//pG/zmq5PlSQbLz35fTwCHLJCEQAhhj/K8em+N7oCLzoATWRIMtXmYXM1glEWFQ25LFqNk1HsNNqOyuvQEXezusork61faK3MJjvaHaPe5KBkmJcOoC0awJPgdssRg2wN91plYrqn0f0WS48psgr6Qm+Vkjpl4vq5RW9P1OjGqhUSeNp9qj1tVyBZ1Tg2HmVjN4FZlZqI5hqqu52c+e5udnT6+/kD9lvR55rkPyFyxxI/98VX+/LLV8z4fz9EfdhPPFHEpMmuZgt2CdagvaE9iLCbzLCbzHOkPksiVSBZKmCaMDYVYzhSbqqhtxkIiz0DE01CV++hAqKG+TiMqW8i93X6r0T2Rtw1V13Nv5UGb3lw8x+G+IPoW5f/BUq1TFYnDfUHOTcVwKhK7u3xki1aZpFK3za6zOv/c9SU+sK/riVqEP2s81wEZyxT5h791jnsrlvL31dkEnQEnF6bjDIRdOB0S7T5rnMjqyqmXIaxMW+zo8DIfzyGHPSS2IJu/EY2OETs6vFyaidvqclulspV0OSRODFr10q6Ak+6A5QtiANfWTYxU6wIJsTXVb9M0SeY1DvcFmI3l6nRmB8JuJlYz7Oz02Wfhl+8sU9QNXNLj9854VnluA3ImmuXv/eYZ7pdXvzMTUd6zux3DgL6wG1WR+HJ5giDidfDuXe0YJtymcdP3vZUM3UEXC8k8A2E3Q21eCiWDu8sp4g8ZoI0CLuRROTWsohsmiiRRMgxmqwaINyOvGbZha2/I3XQrfbAvgKabOGVLiW5Hh68uOVNhMOKmO+gmkdNwyhIBt8JXxtc40Bsg7FVxKjJ+l4JhWtccyxQRWEmkoNvBf/jWQ7g2UMh7HnkuA/LqbIJ/9LvnocpjA6yezFi2yHDEw1w8x2DYTbtf5cJ0gpymo0hSUxFisCZD3A6ZNq+KS7WMQPf2+HE7ZK7PJ+vkIZtRPTuoSHCkrA633mznYVTTHLLl7DQ2EsHjkHjHjjZyms6dxRQjHV57qHj9VtutPti69oUsbZ+bC0lODEe4PBOvMeo50h8EsJsD1huoVrwmXxiJMDYaIexViWWe7vzhduO5C8i1dIF/+sdXyGs6q+kisw3mBm+Tpt2n0uG3WrBODYdJ5TXS+RJ7uv2sNkikVMhpOsupAmGPg+NDIdIFnVxRJ1vQ6hyJmxFyO1AkGG7z4nTIZIs6NxfiNT8jgPmqdjiHbK06jW4WJ4dC3F1Oc7FKfaDT78TvVBBCbHjenY3lGBsOkynqlvFNPEdv0IVDFnWZ6DtLafZ1+7m/mkZVZNbWCRdXZoMNE37xC+P84hfGafOq/JOv2813nx7a9O/yPPDcBeQv/8040Uyh6SpXoXoAdjGRL0+15+kLeRhu8zCfyGOaZsPa3kIiTyxrlRNkTIq6QU/QhWGYHO4PIgtL1CqnGVyfT9jZyf09foJuFacC79zZzit3V5sOKb9jRxupfInZssCxhGVQE/Go7Oz0UdB1DMNEla3E1PrXWU4VGG7zcG91c4fjM5OxGnet+USe+USe/pC75oa2o9PL9fkkLodMKl/iYG+A8aqZxPPTMQYjHrxOmd1dPu4spVnLFPnVl+/zrp0dNVnh55XnKiCn1jL8xZWFOsl5v0thIOyxhZ7WY5hwZzlNxKNiCpOZaBaz/PixwRDLyULdhH5eMzg7GaM/7KbT72SozYtpCuK5IppuosiQ10q0+5yMtHssbVVhopfg/FSisRpRFUupPOPlMahoxjLDmYrmiGaLDc98nX6nbW9Q4d5Kpi6o4EFjAoBWMrg2l2g4pTLS4aHNr9rdRrcXU/QG3fbf4uxklNMjEc5NxexzcYffyRdvr9TopvaF3K1gLPNczUP+p8/eZiVdoKNK5NfnVBhp83B7McmhvmDT5xZLBqOdXkq6iW5Cu1fl5FAIhyTY1+PnUF+ARq2Ts7EcF6bjpAol0oUid5fTXJtPki3qBD0qfSEXpmmtqq+NR3n1/hqpQolUvsSB3kDNB7eaiNdZY5kmbfJfspEg8sG+IN1BF0cHHvwOv1OmWDJsCcWZWJZdXb66KZcdHV7OTca4vZBid9mnQyuPUlUoGZas5cnye3CWZTvAUl6vkMw/Wlb67cRzs0Jenonz6SsLgDW57nJI9ATd3FtOc2WuIoGYoMvvRHVIDR2mzpW7cHqCLgbCbkqGyXIqj0uR8Dpkun0OFEWpK8Dv6vQhIdB44OhbPRXRjKtzSY4PhlAkYUtNDrd56PA7uTGXQMdSDyiWTFwOyT6jjg2H0XSTK3MJjg+GKJQMrpZLG11+J/1hj2UhMBm1r2dsJILAav+rbpB3q3Ld9L3PaekAVWql8/Ece8peIR5VqbEx7/Q7WUoVeO+eDs5PRm3JktWqXYpDlvgfr07wrcf7awL6eeS5CEjTNPnZz93GWdZHnVzLcrDXz8XpWN0ZcCllCfRuZPm2kMgTz2nsaPcyEPFgYt3xd3cHWM1onA65KekmQpgYhpUpDXoU/vrmykNfuyREje5rm1etac+r1PucjqBt6HN7KUUiVyLkcXB+KmZr0gB0BV2cb6BmN7GaIZXT7BlKsM60jeT2ZQGZqpGsdEG3DVPB2j5PR3Ps6/EzE7VKM+uV5xRJooClWhfLFPnJP7/BT33mJi+MtvH3XxrhfXs7H/pv9XbgudiyfvH2Mq/cXaVQMiiUDDyqjNfpaLpFvbucwu2QUZXGfx4h4NRQmGRe49XxNVbTBXZ0+FhNZhhfSJIrFPE4rfEl3TRZThf565srnBqutxXfDLfDUiQ/ORze0NVKYJ0Jby2m6PRbE/DxrIZRViwfirg52Bcg7Hawr6e+cXslVbAt4nZ1+djbbenSCGFJh1SaaTwOicE2L4f7Q02vRZKss/V8PG/L9N9YSHJkIGSXRjJFnbHhMPdX0nYHkaabfPnuKr3b0ATnreJtv0Lqhsl//Mvb9tdORXCgN8hKKke60LiBPJEr8cJohJymIxB2u5rfqbC/N0BB00nkNNp8TqajOW4uprm9lObEUJg9fU4Mw+Qr46t1HS5nJ2Mc6A1wezFVp3Z+sDeA16mg6QYlwySVL+FTFb48/kDecKTdy/3VNHu7/UQzRbspYHeXr0afdX1dr82rMhXNAdaq71NlQh4H8axGyOMgW9Q52BtAIHDIgpVUAa28UlasEQ70BiiUDJI5zW4f3Ntt1VglSaBIAt00SeVKmFDXeGCaDwSrjg2GuDgd58xkjKGIG1kq2UmjwYjHPpM+j7xtAvK1e6u4HDLHB2tXoT++MFuzndINk/lEloBL5eZi3H68WivV7ZCYj2fJFQ1G2r28c2cbAri1lMI0TUJelURO4+5iirFyRnI2luXOUrphNrKa6/NJ3rmzjWLJZK1cftnd5eNaWc90V6ePu8vpsipcbdBWWtpi2RQHegN2QMYyWjkzajWWG+UB5e6gE6ci0+F31jQlpIs6Lw2GWEsXmIvlONhrKeJ5HBLtPicLiXydEl2jM++txRTDbR6m1rI1V9q5iTNWPKvhcUhkNYOpaK6mPvu3jj6bg8WPi2c+IBcSOf79p2/y6SsLvDAa4fc//iJgDbH+wdlpfvmL43jKkxcj7R6CLhWXKiGQeGEkjKrI5DXd9mbs9DtRhCCvG0iS4I3yuJDPKTPa4WMtU7STHtYYlkGyvCpsFowVLs8makoQ1WfCSitZsWRwqC9Q1xNaofoz63XKXJqJo+kme7sfKAksp4rohlk39jU2HObVcnPDYMTDctIK7JxmsCvgpDvgrBGd2ojJtWzddS6nCuzu8pHKl2wzoWrafGpNv2x17+5nry/x4aN9NW5ezxPPfED+8Ccv2h/o1+9HOT8VxSFL/Mxf3SaR11hI5DFMOD4YxKnItj9FdeaymnsrGcZGwrah6QMEV+cSNdvQ9XXL/T2BprXMaroCLlL5xj2xclWkXZ1L0htyMR+v/1AvxPO0+1R2dPg4X6WZUy0f2agndr0uqaoIxpetgDXBrinu6vRtuU826HZwbCCEQ5YolHTurWS4s5TmcF+wJiAr9dZz62ROrszGbUPX20spPvKJr/LKj70Pj/rMfzwfmmc6qbOWLtR5bvzC5+/wU5++yYXpGFdmH3TBLCWLFDSDLr8TIWgYjBVuzKesM1buwTYv4FY2rFMCzMWzdAdcHOgN4G2gKVqhzasil+Ou0jhQIVWoXWV7mkgUrmWKCARnJ2sFrFbTzYNof0+grmkg4mm8vdwogbQew7TEkM9MRrk8m7ATOVfmEpwaDjPU5sHtkFlJFeoGmQ/0Ws3sLseDj+Jqusj3/fb5R56aeRZ5pgPyC7eWa1rCenwyc9EMb0xEaww6wZrzK+oGXpfCgbLlmKV1E6TNq9IbdNlZ0L09flRZYiGR52BfAFlYGqK3F5Ps2mArlciV6Ao4mVrNYJomYyMR/M7aD3aX30mxZNDud7K/J0BJNxhu83KwL8DJoTBtXrXGMbkyobGeiFdlX7e/5v2fGg5vqErga+D7eHc5xUC5wcBdFRSNtppgJXKOD1relEcHQoyNRJiLNf+dZydjtHlVSrpBT9DNgd4A+3r8nB6J0Bdyc33eyr6OtHnt6wD48t1VfvWVe01f9+3KlvYEQohJIAXoQMk0zZNCiO8AfhLYB4yZptlQc6PRcx/9si0+f2PJ/vfJwRDX5pMspJv7W1ybT3KgN0Cn3zon7e8NEM0U2d/lJVEwWE4V+Nq9HRR1K5njkCWKJR2PU2Ffd4CJtQwTq2k78dKIQkknXb4ZXJy2PCyimSK9QTdrmSLT0awt07FUbly/NhcnWzWQ3B924yvJqIpMrqjXNaWPjUSIZgrMJ2vPeWcnY7xrZzvziRzZos5CwtrWrmWKHO0PNTRZ7Q66SOZK9IXdrKQKHBsM4ZQlkjmNnpCL6/NJ9nb70XSDO0tpVtMFYpkiuknNObO6GWA9qbylT9Tsb1bJyHpUmYGwm3afk4szcT55Zprvf++Ohop2b1ceZpP+PtM0qy2GrgHfBvzqm3juI5PXdHteEQBTrylqV3NkIIgqS5ybiuFRZQolnZ1tTs5NRknma1fSar/FiNfB/m4/+zs93F1O0xlQiXhU2n0qfpdCMv9ABa7SiB5wP1jdNN0kmi4iy6JGOLmaa/NJ28i1QjxbpM2rIkmCK3MJnIrE2HCEaLaAblizm4f6rMbt6hEnRYJ7q2nm43lCHgcHewNcm08SdCtcn09wvCy9WDkH7+nyk8qVavpw5+M5JCFYSOTxqVaS6/p8kp0dXnqCLnZ0eFlJFWsy1wDt5RJQI7Z6Fg24FHKaTjRTsM+UH/6lr/BH/+gdtPs2zty+XXgUS/Obpmne3vwnnwyvjq/WCPjeWEyzo63+vLWn28/lmQRnJ2M4ZYmzkzFW0kXWcib7ejY+E0YzGl+5F2UqXqRQ0ukJubm9lEIzTO4spRlfTjO1liVf1O2Wr9l1nS1Lqdre2fXs6PDaZ8CIR6Uv5Gak3UsiX2Ji1XqtQslAlmAunrezk1fnkuSKOm9MRBkbiTA2HGGk3UdBMwiXa4zXyqWKXZ1+irrJ6/ejHO0P0RtycbgvSLtPJbtOBLkv5La3q+miYRfpx1cyLCTy3FvJEHRb9/HqxomNLPsSOc32NtmITr+L1XSRrqCbnR1Wc8LkWpb//sr9TZ/7duFxWZo/8nMf1kH58zeXar7OaiYzsTxHulxcWynYGUZn1RmssoIuJPLs7PTahqITq5mm41iVaYWg28EXb62ws9PHuUlLa7SS7k8XdcaGg0yuZfC7HLDu/BVvMpjsckhcryoXWFZ26Ybejook+O9/9yTX5hL8xZX5mhnG9TOWPUEXYCVEDvcHa/RZKyv1fDzP3m4/yjo9m/U+Gg5ZsL8ngCyB3+Xg3nKau8tpXtrZxr3lNJ0BFyXdQDdMOgMmU2tZux3RIQt2d/mtXYlmcGWu3g26moq5TuX9HOwNMBB213g8vt15ZEvzx/Xch3FQNgyTz99crnu8aMDlpTynBgOcnbY+sJlCCQEo8gNP+oGwm4vTDz4cEY/KyaEwkhAYWA5WyZxGb8htbwcrtbLx5TSdfksQ+epckkN9AXQDTEyG2jy4HHLdds4qfoc5M1GbEd7V6bcGfkMudMNsqpXjcyp877tGeefOdt65s51vPNTDD3/yIjcXk5R0sy5j3B920+ZTCbgcNVMVjVi/nZxYzTDc5qErYDk+n5960O87Nhyxz78l3WQxWWAxWfv8d+1so6CbZArWVrjSULBR22DI42Aw7KkZuAag7DDtmU1gmuZz0TDwSJbmT/q5zbgyl7AMbJowHc3R7nUw0OZlIZ4n4HagGybHBq3s6lq6wMmhIOemrKCMZotEp2rvwpUMYIVi1fl0uN1rf5DXF+6HIm47YP0uxW4ASFbpqx4ZCPHBA9187B1DuFQFraTz3v/8csOVUVUkfuIb9/GePQ+arQciHj760jA/8vuXkAScGApxbS5pT/DfX8nwpz/4EhOrGc5NxvhvL9+rm+7vC7lq1ObAWtECLgfJnEbY66i5aQE1M5o3F5KMtntt35MKy+kiU6uZuvP8+llMlyJxqD/IcqrATDTLlWz96nltLkmn38ntsgHu85DcedOW5lt58Ud57kZUZ1cbsZTW2NPpZWotQzSj2U0AV2cT7O8NMBhxky/WK8hVMxfPcXokTKFkEvIoZAs6V+etc9vF6VhTU1DNMBkpB+y+ngDLyTweVaHNqxIYcfAP3zXK1+7rrLnbf+baYsNgBPjYO4b5rrH6LXxFnMsw4fxUnNF2L51+lXRRx6MqdPqsMat37epgJprlTy7O1Ty/J+i2PTfafSqjHT7ur6SJZ4t0+J31wQhcnIrZYsqH+oOspAr0h9wMtXnIFHUuzcQJuR3cbpBcW07mEcD+3gAuh8ytheSmJkK7On3cW0njVCR8z0mTwKNYmn8r8EtAB/BpIcQl0zS/vtrSvNlzH/Wi158fG3F7OYPHIVlbUUlgmibz8TyXpmOcHm1jLbN50dk0TVbTBS7NxOkLudjX7bdb1JZTBU4MhrkwHcPvtsoiqXyJbLHEjXlrDvH+SrrmbPqjX7+HD+zvqvs9N5tY1f3kN+/noy+NNPzeb3xloubrLr+D20tpolmNv/viEGpVYf8jY4M1ASkJuFveVp8aDnNuMsZq2tqaqzIIIfCqcl0tVzOsrejODi9nJqL2VrY75OLqXIITgyFcDpmugJOldVvZaFbjZPl3bZWSYZa7rMLPjXbro1iafwr4VIPHbUvzZs99FEyz+VlrPVnNaGg489q9NU4Pbez2C5AtGrgcMm6HzFw8z1w8z8mhMOemYrbmznCbh2im2NBMdX2iaP22rcLh/iA/8L4dvHNnB+PLKS5Ox5lYy7Cnu/Yaz0/F+PWv3OfrD3TT4XeSKpTsMsZKRiOa1fjHX7ubH35/rUR/b8jFC6OWg1fJMPE5ZcZXMhzsC3J1Lm43hg9GrBrghek4bodsl02qiXhVLkzH7f8GDllwdyllyVPKEi/fsWY+TwyG6+YulxL5h9KVrSScuoPbx1D1SfPM7QOEEPzw+3fxQ5+82PRnvA6BQ5aI55tvS+eSGieHQpim4MpcvG5QuTfo4tp8kp2dXru8srfbz4VpS/CpMtzcrDPmzlJ9GeBwf+Myy4cO9fChQz0AvLijje95sfE1t/tUUvkSL99Z4SOnBrizlGJfT4C/uLrA9fkkH3/3KD/ytbvqnvezn7tje2qApTowF8sxF7Pk/b1Og+Vk3sqilrfCOU2vS06BlWQxTZNTw2EW4nlW0wUS5fNxdXP9ldm4tfpOxey650wsZ0tBNmJHh5eVdIGwW8XjlO3h6F3P0TjWM2m2oxsmH/z5V+o6P4YjbrqDTq4vpCmWDA70+iloBiUD3KqEKksgLDnCdKFEm1flzGTUckCeimGYVrfIcJsXn0vhzESUfT1+FEkildfo8DvRdINLMwlcisS+ngCSJCiWDDTdQJEE+ZLB+HKa0Q6vfc6rMBBx8xc/9K7HLlMxF8/xX744zr/58IG6Vrt7K2k+8HMv17TYucvTL5WbkFeV8ToVVlIFTB5YFoy0e9ANyzDHqUj0h90sJvKk8iV7nGu9p8d6LdaBiBuvqtg9rH6Xgmli97tW847RCK+VbxyVnQjA1+zt5Be/61hN4/yzTjOznWeyl1WWrFUS4GCvn7HhMMNtHiajOV6fiJPKlyiUDC5MJ1hIFgh5HMxGc5yZjHFmwpK0uLWY4tV7a2i6SaFkcKQ/xOF+y13qxkLS7oa5vZiynavOTsZYTRXZ2+1ntNOLIgvOT8W4OpfAIUu4VZn5WBa/U8HToLl8Jprjn/3xlYZWAY9CX8jNT33roYZ9r51+J7u7ahUCcppRc1PwOhWcDsneuqbyGmGPg8Gwl+lojpVUgdlYDsO0xq2qZysN02q8r/DGRJSdHV7765lojmimiKPcTZ/Klzg5HLYFuoJuhRODIXZ3+XhjMsZwWX2u+qixlim+rYJxI57Zd/lNh3u4vZjkl7+4cQNy5XwnCRjt8BJ0OVDW5QdimSJLiRxFo/wBGQpT0g2yBY2Rdm9NO11X0MXESpqSrrO3J8ip4TAuRaKoG0hC8FPfeojhdi8Bl4LP5cDlkPnQL3zZzqJ+4eYyK+mCLbPxpPG7HPz6R0/xt37lVbtUdKA3UFPSGWn31qxqPqdCNFMkXdQ42BfA7ZDRDZN0XsPtkOssznd0+GoUAtp8zho91uVUwe7/PT0SsT0lwWrIP19+riwJ/A0a4G+Ws9vuDSZo3i48kyskWGfJr2uQsWyGYVqlgrVMEQPY1/3gXDIby3F4MMTebj+pfInzUzEcikQsV0I3agvv56diRLMaLtVRTlAY6KZJsWRyczHFjYUkRwdC7Oj00xWwvBP/zYcP8IPv28nHXhrmiz/6Xjre4r7MvpCb//jth+yvY9naZFP1en16JMLl2QSxrIZpWrXAs5MxxlfS5EtGXTACuJTaQLk+n8S1To+ow+fk5FC4YfKrgm6YxLJa3d9nqM1DUa8vpbwdeWZXSIDd3QEGIx6mm9israeSUKj8vM+pcKA3wM2FJBVjq0q7VyU93+isA9ZdP5HTOD0SIZotMhPNkcprdPpddR0lX7u/i699iJvHk+Br9nbZ57LlZB5HVedSukoXtfrmk6+aQNnbHWhogyAJWE7VdgOlCyVODIZYShXoDblxKRJfbqAx1IjZcuKnImY91ObhD77vxedGHvKZDsilZJ7UQ4jsXp9P1pjlpAsl+459dzltB191941Dlmo+mNUUSgavl7fDec3g6/Z38b3valw33A5UPtQlg3Jjg/U+PaqCAE6sqxMup/J4VctbZH3z+IFeP05FRgjBldk4Ozu8jK9k2NPlJ+hxWFnceI7ZWI49D5kllco3tG881MN/+LZDz00wwjMekL/4hfG6ZuiNyBZ1NN0g5HEgCVHTtNxsJdzIYgAetNQNRjz8zHcc2db9lt9xsp+wV+V73zWCIgl+7I+uIEuCxYTVXlgdjHu7/ciS4MZ8EhPr/B3NFPGXtYUur/OU7A66WMvUj2UB3F5Kc3wwiEOWyBR0ptaypJr8vR2yYLLcjvf33zn8XAUjPMNnSID37e3Y8PteVWYg4uYXv+uYbd2m6SbxrLbllXW8bOa6Eaoi8V+++/i2//B88GAP//k7jrC3O8DOTj8/951HOTsZYyaWqxPoCrgdXC8HI8ALI228c2c7AbdaF4zHB0N8ZXxtw5tjXjN5YyLGtfkkJcNgbCRiC1dXCHkcnCo3sI8NR+oUBJ8HnukV8p0722sauCuoisRPfGgfX3+gm0JJZ6jNywcPdHNnKcWXbi/zV9cXubkFKX+wVsDlDSYmBiMefum7jnFwE72d7cjr95vb6lUicbTdy3eeGuD73j1KulDim37pKzU/1uZVcSpS2ePE8jdZH7A7O73cXHzw985plndIf9iNyyEzXs6+3ltJc2EqxoujEX7+I8e29W7jSfFMB6TXqfDNR3r5vTemax4vlgy+7kBXTcuVqkgc7AtysC/Itx3v5yt3V5mL5/ij87NNG7srNDtDftPhHv7fbztkzUA+g1yasdTeiiXD3rL/X1+7C4cscXYyypH+IL/x0VO0lbOefpeD//mxMf7+/zhrT3ns6PDx1ftRHLKw5x2PDYRqFBLavE7bqaua2ViONq/KsYFQTfZ1R4ePribiXm93nslOnWoMw+STZ6f5iU9dq3n81//eSd6/b/PM5mIiz+duLPKv/vR6058Jexw12zGXQ+Inv/kA/8epgWf6Lp4plOxto2Uya612lUbugqbjbKA+9x//6hb/9UtW/Xe9oDJYyaOdnV7OT1mPV1T1Gkl57Or0sZq2lNLTRZ337ung1/7uyabiXm8XmnXqPNMrJIAkCb779BBORebucooOn5OugIv9vZs3j4OVjNhszi6W1fjGQ928uKOdRE7jfXs6t/z62xlvVfdLIz+NRsEIlp5RhUKpvi6ZyGmcn4pzeiRCyTCRJWFPlzRClgSmIvHNezv5T3/7yNs+GDfimQ/ICn/7RP+bfu76D9V6EeX37ungZ7/zqK0q/rwz3OZhpN1Dm9fJ7cXmZ/F8SbeFlxvRE3RhYtplqFfvraFvwx3bW8nbJiAfhSMDIb7hYDemCWGvg/fv7eL7f+c8//ZbDgLwkVMDz8083lb4nheG2NHh539+dbJuZhKsRM9AxMOV2XjN4yeGQpZv5WwCSViqftfnH6yc3/+e0eemZ7UZz/wZ8kkwvZYlmi3WOAu3aMxsLMtP/tmNmqHxnZ3euiRO9YTJ7i4fbodcl439+LtH+ecf2md/ndf0t+2u5G17hnwSDLZ5Wp73W6Q/7OFHv34Pu7t8LCULeJ0yp4Yj/O+Lc3zh1gMhssP9DzKpPqdSlwjyOWV7CmYhkePnPneHmViW3/joqefK4+P5eactnhh7uv382Af31jzWE3TxhVvLeFWZkQ5fjadI5Xg+NhJhPp5jNVXAoyp86uIcblXhj8/P4nMq/MH3vfBcBSM84506LbYve7r9fPQdw/z1P3kP797VXusaNp/gxVHLHmExYdkAOhSJ1XSRX/zCXebiOW4vpfgnf3j5sc+Obneer9tPi7cMv8vBT374AAAffWmY3/7qlN2/emQgZNsClgyTVKFkf88hC77pcC8ffccwe7r9z3Sd983QCsgWT5Tx5RQ//idX6Qm50KJZeoPuppo6qizxe//wNCeHN+4dfjvTCsgWT5Rfffk+F6Zi7O0JkNcM7q9mODlsqcQnyw3t1oRHlv/1j15kb/ez33DxKLQCssUTo1DS+QfvGiFb1Pn01QX78fXarAd6A/zidx197oMRWgHZ4gmylCjw4V9+tcaGYT0/+L6d/OMP7EZuNV4ArSxriyeIENgqchWq1fjetau9FYzraAVkiyfCK3dW+L//8DLpfAm3Q8KpSBzuD/IXP/ROdpRlIv/vr9vTCsZ1bCkghRCTQoirQohLQohz5ce+QwhxXQhhCCGa2pQLIT4ohLgthBgXQvyzx3XhLbY3f31jiTOTUeYTecJelU6/k//xsTFGO3x877tGOdIfZGfn86NIvlWeqKW5EEIGfgX4ADALnBVC/JlpmjfezMW2eHaoCCGDZQ57YijMQiJHxKvyXWODfOQZnyV9UjxpS/MxYNw0zfumaRaB3we+5c3+zhbPDh5VLjs5W5yfivHfXr6PUe6bawVjY7YakBVb8vNl6/Gt0gfMVH09W36sDiHEx4UQ54QQ51ZWVhr9SItniLvLacKe2sHvP788z+c28fZ83nnSluaNboMNmxMfxtK8xfbm7GSU3/rqVF2GVRLQE3Tyvy/OcWMhyfv3dtq2Cpsp+z0vPGlL81lgoOrrfmD+YS+yxbPDxGqGj/3mWQB8ZZ8OgWVnEPGp/MjvX7It/D7xyn0A/tPfPtwKyDKbblmFEF4hhL/ybyxb8msbP8vmLLBLCDEihFCBjwB/9mYvtsX2Z3Itw3/+jsP4nQqqLDHS7uXoQIjZeI4rswk7GI8OBNnT5eedO9v4mj0b6+s+T2zlDNkFfEUIcRk4A3y6YmkuhJgFXsSyNP8sgBCiVwjxGQDTNEvADwKfBW4Cf2iaZnN5txbPPO/b08lKqkCqUGI+nmViNcNCIseeKku844NhLs0kuL2U4ivjaywk6tXonldaEh4tHiuLiTwf/PmXOdQX4svjVpXMp8qWm1hW4+RwmLV0AVmSCLktB7G1dIH37e3k+96zg4hHfS70i1oSHi2eODcXklydSxDPlSjqhiUDqRs1Jq+SsCY7KsvA2HCE8ZUM4ysT/NpXJvjTH3iJw/2hp/YenjatgGzx2Pid16e4XbYun4/nKJSMOnFkwzQ5PRLh9bK+TqpgjWCdHArjdEjPdTBCKyBbPAZM0+QzVxf53TemGQi7cTtkYtkih/uCDEY8SJJALwsmn5mIoioSgxE309EcerlRYC6eQ2CpqXufYynI5/edt3hs/Ks/vc5vvz4FwEwsx4mhEE5F5rV7D8x8Ov1Oe7Uslgxb3vHOUpp37mzjK+PWz87Fc+yuSgA9b7QCssUj88rd2s6qa3MJDvSGkMQDhbl4TmNHh5d7K5Zea7aoc6Q/iKYbvHpvjXftaqegGc91MEIrIFs8IqZpIq/rSx2MeLk6F0cIwYmBIOen4zgViaDbwY4OL2GPikeVuTgdZ7TDyye+5yQf2N9V4xnyvNKah2zxSAgh+D9fGKp5LORxoOkmumFyazHFrk4fh/uDXJiOc28lw7mpGDOxLPmSzuRallg5A/t2VSl/GForZItH5iNjA7T7nfzGlydwKIKLVarkmaKOEHB+nY7OxGqW9+zu4LV7q407np9TWitki0fGoyp8+EgvQ20ers8na5zD+sJu7iylya/T1Tk2GGJfT4DP/PC7+I5HcC57u9EKyBaPjV1dPrJlN6wTQ2EA5mI5Tpb/Xc34Uor/9vI9/udXJynqzUWwnjdaAdnisWCaJpfKXpAf2N/FH3z8BT50qBuAVL6EQxYcKJvcnhoO2zbxv/P6NL/68v2nc9HbkNYZssVjIVPUOToQ5Ie+Zidep4IiS/zydx3nd0aneGE0gqabeFWFf/cXNzjQG+BffON+vnh7mevzSd63p/NpX/62odVc3qLFU6BZc3lry9qixTaiFZAtWmwjWgHZosU2ohWQLVpsI1oB2aLFNqIVkC1abCNaAdmixTaiFZAtWmwjWgHZosU2Ylt26gghVoCpp30dDWgHVjf9qe3Bs3Ktz8p1wuO91iHTNOsUordlQG5XhBDnGrU7bUeelWt9Vq4T3pprbW1ZW7TYRrQCskWLbUQrIB+OTzztC3gInpVrfVauE96Ca22dIVu02Ea0VsgWLbYRrYBs0WIb0QrILSKEkIUQF4UQf/G0r2UjhBCTQoirQohLQohtLbsghAgJIf5ICHFLCHFTCPHi076mRggh9pT/npX/JYUQ/9eT+F0tTZ2t8yNYprOBp30hW+B9pmk+C8X2XwD+yjTNv1122PY87QtqhGmat4GjYN2YgTngU0/id7VWyC0ghOgHvhH4tad9LW8XhBAB4N3ArwOYplk0TTP+VC9qa7wfuGea5hPpJGsF5Nb4eeDHgGdBQNQEPieEOC+E+PjTvpgNGAVWgN8sHwV+TQjhfdoXtQU+AnzySb14KyA3QQjxTcCyaZrnn/a1bJGXTNM8DnwD8ANCiHc/7QtqggIcB/6raZrHgAzwz57uJW1MeVv9YeB/Panf0QrIzXkJ+LAQYhL4feBrhBC/83QvqTmmac6X/38Z65wz9nSvqCmzwKxpmm+Uv/4jrADdznwDcME0zaUn9QtaAbkJpmn+uGma/aZpDmNtV/7GNM3/8ylfVkOEEF4hhL/yb+DrgGtP96oaY5rmIjAjhNhTfuj9wI2neElb4bt4gttVaGVZ3250AZ8Sll+jAvyeaZp/9XQvaUN+CPjd8lbwPvCxp3w9TRFCeIAPAN/3RH9Pq3WuRYvtQ2vL2qLFNqIVkC1abCNaAdmixTaiFZAtWmwjWgHZosU2ohWQLVpsI1oB2aLFNuL/B1f9a6auBXnsAAAAAElFTkSuQmCC",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"nl_map = gpd.read_file(r'../data/shape/Netherlands_shapefile/gemeente_2021_v1.shp')\n",
"nl_map.to_crs(epsg=4326).plot()\n"
]
},
{
"cell_type": "code",
"execution_count": 29,
"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>GM_CODE</th>\n",
" <th>GM_NAAM</th>\n",
" <th>H2O</th>\n",
" <th>OAD</th>\n",
" <th>STED</th>\n",
" <th>BEV_DICHTH</th>\n",
" <th>AANT_INW</th>\n",
" <th>AANT_MAN</th>\n",
" <th>AANT_VROUW</th>\n",
" <th>P_00_14_JR</th>\n",
" <th>...</th>\n",
" <th>P_TURKIJE</th>\n",
" <th>P_OVER_NW</th>\n",
" <th>OPP_TOT</th>\n",
" <th>OPP_LAND</th>\n",
" <th>OPP_WATER</th>\n",
" <th>JRSTATCODE</th>\n",
" <th>JAAR</th>\n",
" <th>Shape_Leng</th>\n",
" <th>Shape_Area</th>\n",
" <th>geometry</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>GM0034</td>\n",
" <td>Almere</td>\n",
" <td>JA</td>\n",
" <td>-99999999</td>\n",
" <td>-99999999</td>\n",
" <td>-99999999</td>\n",
" <td>-99999999</td>\n",
" <td>-99999999</td>\n",
" <td>-99999999</td>\n",
" <td>-99999999</td>\n",
" <td>...</td>\n",
" <td>-99999999</td>\n",
" <td>-99999999</td>\n",
" <td>-99999999</td>\n",
" <td>-99999999</td>\n",
" <td>-99999999</td>\n",
" <td>2021GM0034</td>\n",
" <td>2021</td>\n",
" <td>122665.358635</td>\n",
" <td>1.095623e+08</td>\n",
" <td>MULTIPOLYGON (((150213.998 479503.726, 150087....</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>GM0050</td>\n",
" <td>Zeewolde</td>\n",
" <td>JA</td>\n",
" <td>-99999999</td>\n",
" <td>-99999999</td>\n",
" <td>-99999999</td>\n",
" <td>-99999999</td>\n",
" <td>-99999999</td>\n",
" <td>-99999999</td>\n",
" <td>-99999999</td>\n",
" <td>...</td>\n",
" <td>-99999999</td>\n",
" <td>-99999999</td>\n",
" <td>-99999999</td>\n",
" <td>-99999999</td>\n",
" <td>-99999999</td>\n",
" <td>2021GM0050</td>\n",
" <td>2021</td>\n",
" <td>83290.773617</td>\n",
" <td>1.633050e+07</td>\n",
" <td>MULTIPOLYGON (((170588.413 486792.192, 170570....</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>GM0060</td>\n",
" <td>Ameland</td>\n",
" <td>JA</td>\n",
" <td>-99999999</td>\n",
" <td>-99999999</td>\n",
" <td>-99999999</td>\n",
" <td>-99999999</td>\n",
" <td>-99999999</td>\n",
" <td>-99999999</td>\n",
" <td>-99999999</td>\n",
" <td>...</td>\n",
" <td>-99999999</td>\n",
" <td>-99999999</td>\n",
" <td>-99999999</td>\n",
" <td>-99999999</td>\n",
" <td>-99999999</td>\n",
" <td>2021GM0060</td>\n",
" <td>2021</td>\n",
" <td>156406.894023</td>\n",
" <td>2.085914e+08</td>\n",
" <td>POLYGON ((196000.000 610000.000, 196000.000 60...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>GM0072</td>\n",
" <td>Harlingen</td>\n",
" <td>JA</td>\n",
" <td>-99999999</td>\n",
" <td>-99999999</td>\n",
" <td>-99999999</td>\n",
" <td>-99999999</td>\n",
" <td>-99999999</td>\n",
" <td>-99999999</td>\n",
" <td>-99999999</td>\n",
" <td>...</td>\n",
" <td>-99999999</td>\n",
" <td>-99999999</td>\n",
" <td>-99999999</td>\n",
" <td>-99999999</td>\n",
" <td>-99999999</td>\n",
" <td>2021GM0072</td>\n",
" <td>2021</td>\n",
" <td>104274.683035</td>\n",
" <td>3.618323e+08</td>\n",
" <td>MULTIPOLYGON (((158392.775 580357.500, 158387....</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>GM0088</td>\n",
" <td>Schiermonnikoog</td>\n",
" <td>JA</td>\n",
" <td>-99999999</td>\n",
" <td>-99999999</td>\n",
" <td>-99999999</td>\n",
" <td>-99999999</td>\n",
" <td>-99999999</td>\n",
" <td>-99999999</td>\n",
" <td>-99999999</td>\n",
" <td>...</td>\n",
" <td>-99999999</td>\n",
" <td>-99999999</td>\n",
" <td>-99999999</td>\n",
" <td>-99999999</td>\n",
" <td>-99999999</td>\n",
" <td>2021GM0088</td>\n",
" <td>2021</td>\n",
" <td>152568.858991</td>\n",
" <td>1.624101e+08</td>\n",
" <td>POLYGON ((219000.000 616567.418, 219000.000 61...</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>430</th>\n",
" <td>GM1966</td>\n",
" <td>Het Hogeland</td>\n",
" <td>NEE</td>\n",
" <td>414</td>\n",
" <td>5</td>\n",
" <td>99</td>\n",
" <td>47834</td>\n",
" <td>24052</td>\n",
" <td>23782</td>\n",
" <td>15</td>\n",
" <td>...</td>\n",
" <td>0</td>\n",
" <td>3</td>\n",
" <td>90308</td>\n",
" <td>48249</td>\n",
" <td>42059</td>\n",
" <td>2021GM1966</td>\n",
" <td>2021</td>\n",
" <td>321301.166576</td>\n",
" <td>4.875998e+08</td>\n",
" <td>MULTIPOLYGON (((217037.735 601967.991, 217043....</td>\n",
" </tr>\n",
" <tr>\n",
" <th>431</th>\n",
" <td>GM1969</td>\n",
" <td>Westerkwartier</td>\n",
" <td>NEE</td>\n",
" <td>476</td>\n",
" <td>5</td>\n",
" <td>176</td>\n",
" <td>63678</td>\n",
" <td>32034</td>\n",
" <td>31644</td>\n",
" <td>17</td>\n",
" <td>...</td>\n",
" <td>0</td>\n",
" <td>3</td>\n",
" <td>36887</td>\n",
" <td>36269</td>\n",
" <td>618</td>\n",
" <td>2021GM1969</td>\n",
" <td>2021</td>\n",
" <td>99030.762281</td>\n",
" <td>3.688457e+08</td>\n",
" <td>POLYGON ((215186.661 595044.495, 215190.788 59...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>432</th>\n",
" <td>GM1970</td>\n",
" <td>Noardeast-Fryslân</td>\n",
" <td>NEE</td>\n",
" <td>463</td>\n",
" <td>5</td>\n",
" <td>120</td>\n",
" <td>45481</td>\n",
" <td>22879</td>\n",
" <td>22602</td>\n",
" <td>17</td>\n",
" <td>...</td>\n",
" <td>0</td>\n",
" <td>2</td>\n",
" <td>51645</td>\n",
" <td>37783</td>\n",
" <td>13862</td>\n",
" <td>2021GM1970</td>\n",
" <td>2021</td>\n",
" <td>238426.959926</td>\n",
" <td>3.837930e+08</td>\n",
" <td>MULTIPOLYGON (((207769.575 603284.528, 207773....</td>\n",
" </tr>\n",
" <tr>\n",
" <th>433</th>\n",
" <td>GM1978</td>\n",
" <td>Molenlanden</td>\n",
" <td>NEE</td>\n",
" <td>393</td>\n",
" <td>5</td>\n",
" <td>243</td>\n",
" <td>44130</td>\n",
" <td>22317</td>\n",
" <td>21813</td>\n",
" <td>18</td>\n",
" <td>...</td>\n",
" <td>0</td>\n",
" <td>2</td>\n",
" <td>19158</td>\n",
" <td>18173</td>\n",
" <td>986</td>\n",
" <td>2021GM1978</td>\n",
" <td>2021</td>\n",
" <td>88570.376691</td>\n",
" <td>1.915841e+08</td>\n",
" <td>POLYGON ((123569.533 440132.167, 123576.153 44...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>434</th>\n",
" <td>GM1979</td>\n",
" <td>Eemsdelta</td>\n",
" <td>NEE</td>\n",
" <td>692</td>\n",
" <td>4</td>\n",
" <td>170</td>\n",
" <td>45587</td>\n",
" <td>22841</td>\n",
" <td>22746</td>\n",
" <td>14</td>\n",
" <td>...</td>\n",
" <td>2</td>\n",
" <td>5</td>\n",
" <td>36407</td>\n",
" <td>26789</td>\n",
" <td>9618</td>\n",
" <td>2021GM1979</td>\n",
" <td>2021</td>\n",
" <td>173966.493452</td>\n",
" <td>2.727771e+08</td>\n",
" <td>MULTIPOLYGON (((269190.000 594253.046, 269190....</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>435 rows × 38 columns</p>\n",
"</div>"
],
"text/plain": [
" GM_CODE GM_NAAM H2O OAD STED BEV_DICHTH AANT_INW \\\n",
"0 GM0034 Almere JA -99999999 -99999999 -99999999 -99999999 \n",
"1 GM0050 Zeewolde JA -99999999 -99999999 -99999999 -99999999 \n",
"2 GM0060 Ameland JA -99999999 -99999999 -99999999 -99999999 \n",
"3 GM0072 Harlingen JA -99999999 -99999999 -99999999 -99999999 \n",
"4 GM0088 Schiermonnikoog JA -99999999 -99999999 -99999999 -99999999 \n",
".. ... ... ... ... ... ... ... \n",
"430 GM1966 Het Hogeland NEE 414 5 99 47834 \n",
"431 GM1969 Westerkwartier NEE 476 5 176 63678 \n",
"432 GM1970 Noardeast-Fryslân NEE 463 5 120 45481 \n",
"433 GM1978 Molenlanden NEE 393 5 243 44130 \n",
"434 GM1979 Eemsdelta NEE 692 4 170 45587 \n",
"\n",
" AANT_MAN AANT_VROUW P_00_14_JR ... P_TURKIJE P_OVER_NW OPP_TOT \\\n",
"0 -99999999 -99999999 -99999999 ... -99999999 -99999999 -99999999 \n",
"1 -99999999 -99999999 -99999999 ... -99999999 -99999999 -99999999 \n",
"2 -99999999 -99999999 -99999999 ... -99999999 -99999999 -99999999 \n",
"3 -99999999 -99999999 -99999999 ... -99999999 -99999999 -99999999 \n",
"4 -99999999 -99999999 -99999999 ... -99999999 -99999999 -99999999 \n",
".. ... ... ... ... ... ... ... \n",
"430 24052 23782 15 ... 0 3 90308 \n",
"431 32034 31644 17 ... 0 3 36887 \n",
"432 22879 22602 17 ... 0 2 51645 \n",
"433 22317 21813 18 ... 0 2 19158 \n",
"434 22841 22746 14 ... 2 5 36407 \n",
"\n",
" OPP_LAND OPP_WATER JRSTATCODE JAAR Shape_Leng Shape_Area \\\n",
"0 -99999999 -99999999 2021GM0034 2021 122665.358635 1.095623e+08 \n",
"1 -99999999 -99999999 2021GM0050 2021 83290.773617 1.633050e+07 \n",
"2 -99999999 -99999999 2021GM0060 2021 156406.894023 2.085914e+08 \n",
"3 -99999999 -99999999 2021GM0072 2021 104274.683035 3.618323e+08 \n",
"4 -99999999 -99999999 2021GM0088 2021 152568.858991 1.624101e+08 \n",
".. ... ... ... ... ... ... \n",
"430 48249 42059 2021GM1966 2021 321301.166576 4.875998e+08 \n",
"431 36269 618 2021GM1969 2021 99030.762281 3.688457e+08 \n",
"432 37783 13862 2021GM1970 2021 238426.959926 3.837930e+08 \n",
"433 18173 986 2021GM1978 2021 88570.376691 1.915841e+08 \n",
"434 26789 9618 2021GM1979 2021 173966.493452 2.727771e+08 \n",
"\n",
" geometry \n",
"0 MULTIPOLYGON (((150213.998 479503.726, 150087.... \n",
"1 MULTIPOLYGON (((170588.413 486792.192, 170570.... \n",
"2 POLYGON ((196000.000 610000.000, 196000.000 60... \n",
"3 MULTIPOLYGON (((158392.775 580357.500, 158387.... \n",
"4 POLYGON ((219000.000 616567.418, 219000.000 61... \n",
".. ... \n",
"430 MULTIPOLYGON (((217037.735 601967.991, 217043.... \n",
"431 POLYGON ((215186.661 595044.495, 215190.788 59... \n",
"432 MULTIPOLYGON (((207769.575 603284.528, 207773.... \n",
"433 POLYGON ((123569.533 440132.167, 123576.153 44... \n",
"434 MULTIPOLYGON (((269190.000 594253.046, 269190.... \n",
"\n",
"[435 rows x 38 columns]"
]
},
"execution_count": 29,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"nl_map"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<AxesSubplot:>"
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": "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",
"text/plain": [
"<Figure size 720x720 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"import matplotlib.pyplot as plt\n",
"\n",
"fig, ax = plt.subplots(figsize = (10,10))\n",
"nl_map.to_crs(epsg=4326).plot(ax=ax, color='lightgrey')\n",
"df_geojson.plot(ax=ax)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We hebben hier een probleem dat sommige punten de coördinaten 0,0 hebben, dit is niet iets wat we willen weergeven. Laten we eerst kijken waarom dit het geval is in de data voordat we het er helemaal uithalen."
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Stembureau 32\n",
"Adres \n",
"Locatie SB32\n",
"description Stembureau Mobiel Stembureau 1\n",
"Geldige stemmen 99\n",
" ... \n",
"\"Leefbaar 's-Hertogenbosch\" Paul Kagie NaN\n",
"RAADSGROEPERING ''BOSCH-BELANG'' NaN\n",
"gewoon ge-DREVEN NaN\n",
"VOOR Den Bosch Joep Gersjes NaN\n",
"geometry POINT (0 0)\n",
"Name: 2520, Length: 973, dtype: object\n",
"Stembureau 33\n",
"Adres \n",
"Locatie SB33\n",
"description Stembureau Mobiel Stembureau 2\n",
"Geldige stemmen 115\n",
" ... \n",
"\"Leefbaar 's-Hertogenbosch\" Paul Kagie NaN\n",
"RAADSGROEPERING ''BOSCH-BELANG'' NaN\n",
"gewoon ge-DREVEN NaN\n",
"VOOR Den Bosch Joep Gersjes NaN\n",
"geometry POINT (0 0)\n",
"Name: 2521, Length: 973, dtype: object\n",
"Stembureau 157\n",
"Adres \n",
"Locatie SB157\n",
"description Stembureau Stembureau Stembus\n",
"Geldige stemmen 72\n",
" ... \n",
"\"Leefbaar 's-Hertogenbosch\" Paul Kagie NaN\n",
"RAADSGROEPERING ''BOSCH-BELANG'' NaN\n",
"gewoon ge-DREVEN NaN\n",
"VOOR Den Bosch Joep Gersjes NaN\n",
"geometry POINT (0 0)\n",
"Name: 2918, Length: 973, dtype: object\n",
"Stembureau 171\n",
"Adres \n",
"Locatie SB171\n",
"description Stembureau Stembureau Stembureau op locatie al...\n",
"Geldige stemmen 174\n",
" ... \n",
"\"Leefbaar 's-Hertogenbosch\" Paul Kagie NaN\n",
"RAADSGROEPERING ''BOSCH-BELANG'' NaN\n",
"gewoon ge-DREVEN NaN\n",
"VOOR Den Bosch Joep Gersjes NaN\n",
"geometry POINT (0 0)\n",
"Name: 3579, Length: 973, dtype: object\n",
"Stembureau 172\n",
"Adres \n",
"Locatie SB172\n",
"description Stembureau Stembureau Stembureau op locatie al...\n",
"Geldige stemmen 66\n",
" ... \n",
"\"Leefbaar 's-Hertogenbosch\" Paul Kagie NaN\n",
"RAADSGROEPERING ''BOSCH-BELANG'' NaN\n",
"gewoon ge-DREVEN NaN\n",
"VOOR Den Bosch Joep Gersjes NaN\n",
"geometry POINT (0 0)\n",
"Name: 3580, Length: 973, dtype: object\n",
"Stembureau 173\n",
"Adres \n",
"Locatie SB173\n",
"description Stembureau Stembureau Stembureau op locatie al...\n",
"Geldige stemmen 162\n",
" ... \n",
"\"Leefbaar 's-Hertogenbosch\" Paul Kagie NaN\n",
"RAADSGROEPERING ''BOSCH-BELANG'' NaN\n",
"gewoon ge-DREVEN NaN\n",
"VOOR Den Bosch Joep Gersjes NaN\n",
"geometry POINT (0 0)\n",
"Name: 3581, Length: 973, dtype: object\n",
"Stembureau 174\n",
"Adres \n",
"Locatie SB174\n",
"description Stembureau Stembureau Stembureau op locatie al...\n",
"Geldige stemmen 65\n",
" ... \n",
"\"Leefbaar 's-Hertogenbosch\" Paul Kagie NaN\n",
"RAADSGROEPERING ''BOSCH-BELANG'' NaN\n",
"gewoon ge-DREVEN NaN\n",
"VOOR Den Bosch Joep Gersjes NaN\n",
"geometry POINT (0 0)\n",
"Name: 3582, Length: 973, dtype: object\n",
"Stembureau 175\n",
"Adres \n",
"Locatie SB175\n",
"description Stembureau Stembureau Stembureau op locatie al...\n",
"Geldige stemmen 121\n",
" ... \n",
"\"Leefbaar 's-Hertogenbosch\" Paul Kagie NaN\n",
"RAADSGROEPERING ''BOSCH-BELANG'' NaN\n",
"gewoon ge-DREVEN NaN\n",
"VOOR Den Bosch Joep Gersjes NaN\n",
"geometry POINT (0 0)\n",
"Name: 3583, Length: 973, dtype: object\n",
"Stembureau 39\n",
"Adres \n",
"Locatie SB39\n",
"description Stembureau Mobiel stembureau met beperkte toeg...\n",
"Geldige stemmen 56\n",
" ... \n",
"\"Leefbaar 's-Hertogenbosch\" Paul Kagie NaN\n",
"RAADSGROEPERING ''BOSCH-BELANG'' NaN\n",
"gewoon ge-DREVEN NaN\n",
"VOOR Den Bosch Joep Gersjes NaN\n",
"geometry POINT (0 0)\n",
"Name: 5494, Length: 973, dtype: object\n",
"Stembureau 34\n",
"Adres \n",
"Locatie SB34\n",
"description Stembureau Stembureau Mobiel stembureau verzor...\n",
"Geldige stemmen 119\n",
" ... \n",
"\"Leefbaar 's-Hertogenbosch\" Paul Kagie NaN\n",
"RAADSGROEPERING ''BOSCH-BELANG'' NaN\n",
"gewoon ge-DREVEN NaN\n",
"VOOR Den Bosch Joep Gersjes NaN\n",
"geometry POINT (0 0)\n",
"Name: 5784, Length: 973, dtype: object\n",
"Stembureau 35\n",
"Adres \n",
"Locatie SB35\n",
"description Stembureau Stembureau Mobiel stembureau verzor...\n",
"Geldige stemmen 151\n",
" ... \n",
"\"Leefbaar 's-Hertogenbosch\" Paul Kagie NaN\n",
"RAADSGROEPERING ''BOSCH-BELANG'' NaN\n",
"gewoon ge-DREVEN NaN\n",
"VOOR Den Bosch Joep Gersjes NaN\n",
"geometry POINT (0 0)\n",
"Name: 5785, Length: 973, dtype: object\n",
"Stembureau 11\n",
"Adres \n",
"Locatie SB11\n",
"description Stembureau Mobiel stembureau Ommedijk\n",
"Geldige stemmen 14\n",
" ... \n",
"\"Leefbaar 's-Hertogenbosch\" Paul Kagie NaN\n",
"RAADSGROEPERING ''BOSCH-BELANG'' NaN\n",
"gewoon ge-DREVEN NaN\n",
"VOOR Den Bosch Joep Gersjes NaN\n",
"geometry POINT (0 0)\n",
"Name: 6260, Length: 973, dtype: object\n",
"Stembureau 12\n",
"Adres \n",
"Locatie SB12\n",
"description Stembureau Mobiel stembureau Van Alphenstaete ...\n",
"Geldige stemmen 68\n",
" ... \n",
"\"Leefbaar 's-Hertogenbosch\" Paul Kagie NaN\n",
"RAADSGROEPERING ''BOSCH-BELANG'' NaN\n",
"gewoon ge-DREVEN NaN\n",
"VOOR Den Bosch Joep Gersjes NaN\n",
"geometry POINT (0 0)\n",
"Name: 6261, Length: 973, dtype: object\n",
"Stembureau 70\n",
"Adres \n",
"Locatie SB70\n",
"description Stembureau Mobiel stembureau\n",
"Geldige stemmen 34\n",
" ... \n",
"\"Leefbaar 's-Hertogenbosch\" Paul Kagie NaN\n",
"RAADSGROEPERING ''BOSCH-BELANG'' NaN\n",
"gewoon ge-DREVEN NaN\n",
"VOOR Den Bosch Joep Gersjes NaN\n",
"geometry POINT (0 0)\n",
"Name: 6738, Length: 973, dtype: object\n",
"Stembureau 71\n",
"Adres \n",
"Locatie SB71\n",
"description Stembureau Mobiel stembureau\n",
"Geldige stemmen 43\n",
" ... \n",
"\"Leefbaar 's-Hertogenbosch\" Paul Kagie NaN\n",
"RAADSGROEPERING ''BOSCH-BELANG'' NaN\n",
"gewoon ge-DREVEN NaN\n",
"VOOR Den Bosch Joep Gersjes NaN\n",
"geometry POINT (0 0)\n",
"Name: 6739, Length: 973, dtype: object\n",
"Stembureau 699\n",
"Adres \n",
"Locatie SB699\n",
"description Stembureau Stembureau Mobiel stembureau\n",
"Geldige stemmen 59\n",
" ... \n",
"\"Leefbaar 's-Hertogenbosch\" Paul Kagie NaN\n",
"RAADSGROEPERING ''BOSCH-BELANG'' NaN\n",
"gewoon ge-DREVEN NaN\n",
"VOOR Den Bosch Joep Gersjes NaN\n",
"geometry POINT (0 0)\n",
"Name: 6863, Length: 973, dtype: object\n",
"Stembureau 32\n",
"Adres \n",
"Locatie SB32\n",
"description Stembureau Mobielstembureau\n",
"Geldige stemmen 63\n",
" ... \n",
"\"Leefbaar 's-Hertogenbosch\" Paul Kagie NaN\n",
"RAADSGROEPERING ''BOSCH-BELANG'' NaN\n",
"gewoon ge-DREVEN NaN\n",
"VOOR Den Bosch Joep Gersjes NaN\n",
"geometry POINT (0 0)\n",
"Name: 7348, Length: 973, dtype: object\n",
"Stembureau 90\n",
"Adres \n",
"Locatie SB90\n",
"description Stembureau Roll and Vote\n",
"Geldige stemmen 339\n",
" ... \n",
"\"Leefbaar 's-Hertogenbosch\" Paul Kagie NaN\n",
"RAADSGROEPERING ''BOSCH-BELANG'' NaN\n",
"gewoon ge-DREVEN NaN\n",
"VOOR Den Bosch Joep Gersjes NaN\n",
"geometry POINT (0 0)\n",
"Name: 7364, Length: 973, dtype: object\n",
"Stembureau 19\n",
"Adres \n",
"Locatie SB19\n",
"description Stembureau Mobiel stembureau\n",
"Geldige stemmen 77\n",
" ... \n",
"\"Leefbaar 's-Hertogenbosch\" Paul Kagie NaN\n",
"RAADSGROEPERING ''BOSCH-BELANG'' NaN\n",
"gewoon ge-DREVEN NaN\n",
"VOOR Den Bosch Joep Gersjes NaN\n",
"geometry POINT (0 0)\n",
"Name: 7857, Length: 973, dtype: object\n",
"Stembureau 1428\n",
"Adres \n",
"Locatie SB1428\n",
"description Stembureau Drive-thru parkeerplaats Rusheuvel 1\n",
"Geldige stemmen 163\n",
" ... \n",
"\"Leefbaar 's-Hertogenbosch\" Paul Kagie NaN\n",
"RAADSGROEPERING ''BOSCH-BELANG'' NaN\n",
"gewoon ge-DREVEN NaN\n",
"VOOR Den Bosch Joep Gersjes NaN\n",
"geometry POINT (0 0)\n",
"Name: 7912, Length: 973, dtype: object\n",
"Stembureau 1437\n",
"Adres \n",
"Locatie SB1437\n",
"description Stembureau Drive-thru parkeerplaats Rusheuvel 2\n",
"Geldige stemmen 239\n",
" ... \n",
"\"Leefbaar 's-Hertogenbosch\" Paul Kagie NaN\n",
"RAADSGROEPERING ''BOSCH-BELANG'' NaN\n",
"gewoon ge-DREVEN NaN\n",
"VOOR Den Bosch Joep Gersjes NaN\n",
"geometry POINT (0 0)\n",
"Name: 7913, Length: 973, dtype: object\n",
"Stembureau 1528\n",
"Adres \n",
"Locatie SB1528\n",
"description Stembureau Drive-thru parkeerplaats Rusheuvel 1\n",
"Geldige stemmen 323\n",
" ... \n",
"\"Leefbaar 's-Hertogenbosch\" Paul Kagie NaN\n",
"RAADSGROEPERING ''BOSCH-BELANG'' NaN\n",
"gewoon ge-DREVEN NaN\n",
"VOOR Den Bosch Joep Gersjes NaN\n",
"geometry POINT (0 0)\n",
"Name: 7923, Length: 973, dtype: object\n",
"Stembureau 1537\n",
"Adres \n",
"Locatie SB1537\n",
"description Stembureau Drive-thru parkeerplaats Rusheuvel 2\n",
"Geldige stemmen 208\n",
" ... \n",
"\"Leefbaar 's-Hertogenbosch\" Paul Kagie NaN\n",
"RAADSGROEPERING ''BOSCH-BELANG'' NaN\n",
"gewoon ge-DREVEN NaN\n",
"VOOR Den Bosch Joep Gersjes NaN\n",
"geometry POINT (0 0)\n",
"Name: 7924, Length: 973, dtype: object\n",
"Stembureau 1541\n",
"Adres \n",
"Locatie SB1541\n",
"description Stembureau Mobiel stembureau\n",
"Geldige stemmen 125\n",
" ... \n",
"\"Leefbaar 's-Hertogenbosch\" Paul Kagie NaN\n",
"RAADSGROEPERING ''BOSCH-BELANG'' NaN\n",
"gewoon ge-DREVEN NaN\n",
"VOOR Den Bosch Joep Gersjes NaN\n",
"geometry POINT (0 0)\n",
"Name: 7926, Length: 973, dtype: object\n",
"Stembureau 200\n",
"Adres \n",
"Locatie SB200\n",
"description Stembureau Mobiel stembureau Ma\n",
"Geldige stemmen 30\n",
" ... \n",
"\"Leefbaar 's-Hertogenbosch\" Paul Kagie NaN\n",
"RAADSGROEPERING ''BOSCH-BELANG'' NaN\n",
"gewoon ge-DREVEN NaN\n",
"VOOR Den Bosch Joep Gersjes NaN\n",
"geometry POINT (0 0)\n",
"Name: 7958, Length: 973, dtype: object\n",
"Stembureau 201\n",
"Adres \n",
"Locatie SB201\n",
"description Stembureau Mobiel stembureau Di\n",
"Geldige stemmen 30\n",
" ... \n",
"\"Leefbaar 's-Hertogenbosch\" Paul Kagie NaN\n",
"RAADSGROEPERING ''BOSCH-BELANG'' NaN\n",
"gewoon ge-DREVEN NaN\n",
"VOOR Den Bosch Joep Gersjes NaN\n",
"geometry POINT (0 0)\n",
"Name: 7959, Length: 973, dtype: object\n",
"Stembureau 202\n",
"Adres \n",
"Locatie SB202\n",
"description Stembureau Mobiel stembureau Woe\n",
"Geldige stemmen 44\n",
" ... \n",
"\"Leefbaar 's-Hertogenbosch\" Paul Kagie NaN\n",
"RAADSGROEPERING ''BOSCH-BELANG'' NaN\n",
"gewoon ge-DREVEN NaN\n",
"VOOR Den Bosch Joep Gersjes NaN\n",
"geometry POINT (0 0)\n",
"Name: 7960, Length: 973, dtype: object\n",
"Stembureau 30\n",
"Adres \n",
"Locatie SB30\n",
"description Stembureau Stembureau voor de telling stembure...\n",
"Geldige stemmen 2004\n",
" ... \n",
"\"Leefbaar 's-Hertogenbosch\" Paul Kagie NaN\n",
"RAADSGROEPERING ''BOSCH-BELANG'' NaN\n",
"gewoon ge-DREVEN NaN\n",
"VOOR Den Bosch Joep Gersjes NaN\n",
"geometry POINT (0 0)\n",
"Name: 8108, Length: 973, dtype: object\n",
"Stembureau 40\n",
"Adres \n",
"Locatie SB40\n",
"description Stembureau Stembureau voor de telling stembure...\n",
"Geldige stemmen 2953\n",
" ... \n",
"\"Leefbaar 's-Hertogenbosch\" Paul Kagie NaN\n",
"RAADSGROEPERING ''BOSCH-BELANG'' NaN\n",
"gewoon ge-DREVEN NaN\n",
"VOOR Den Bosch Joep Gersjes NaN\n",
"geometry POINT (0 0)\n",
"Name: 8109, Length: 973, dtype: object\n",
"Stembureau 990\n",
"Adres \n",
"Locatie SB990\n",
"description Stembureau Mobiel stembureau (meerdere plaatsen)\n",
"Geldige stemmen 47\n",
" ... \n",
"\"Leefbaar 's-Hertogenbosch\" Paul Kagie NaN\n",
"RAADSGROEPERING ''BOSCH-BELANG'' NaN\n",
"gewoon ge-DREVEN NaN\n",
"VOOR Den Bosch Joep Gersjes NaN\n",
"geometry POINT (0 0)\n",
"Name: 8161, Length: 973, dtype: object\n",
"Stembureau 991\n",
"Adres \n",
"Locatie SB991\n",
"description Stembureau Mobiel stembureau (meerdere plaatsen)\n",
"Geldige stemmen 70\n",
" ... \n",
"\"Leefbaar 's-Hertogenbosch\" Paul Kagie NaN\n",
"RAADSGROEPERING ''BOSCH-BELANG'' NaN\n",
"gewoon ge-DREVEN NaN\n",
"VOOR Den Bosch Joep Gersjes NaN\n",
"geometry POINT (0 0)\n",
"Name: 8162, Length: 973, dtype: object\n",
"Stembureau 992\n",
"Adres \n",
"Locatie SB992\n",
"description Stembureau Mobiel stembureau (meerdere plaatsen)\n",
"Geldige stemmen 39\n",
" ... \n",
"\"Leefbaar 's-Hertogenbosch\" Paul Kagie NaN\n",
"RAADSGROEPERING ''BOSCH-BELANG'' NaN\n",
"gewoon ge-DREVEN NaN\n",
"VOOR Den Bosch Joep Gersjes NaN\n",
"geometry POINT (0 0)\n",
"Name: 8163, Length: 973, dtype: object\n",
"Stembureau 17\n",
"Adres \n",
"Locatie SB17\n",
"description Stembureau Mobiel Stembureau dinsdag\n",
"Geldige stemmen 115\n",
" ... \n",
"\"Leefbaar 's-Hertogenbosch\" Paul Kagie NaN\n",
"RAADSGROEPERING ''BOSCH-BELANG'' NaN\n",
"gewoon ge-DREVEN NaN\n",
"VOOR Den Bosch Joep Gersjes NaN\n",
"geometry POINT (0 0)\n",
"Name: 8318, Length: 973, dtype: object\n",
"Stembureau 228\n",
"Adres \n",
"Locatie SB228\n",
"description Stembureau Stembureau Drive-in\n",
"Geldige stemmen 80\n",
" ... \n",
"\"Leefbaar 's-Hertogenbosch\" Paul Kagie NaN\n",
"RAADSGROEPERING ''BOSCH-BELANG'' NaN\n",
"gewoon ge-DREVEN NaN\n",
"VOOR Den Bosch Joep Gersjes NaN\n",
"geometry POINT (0 0)\n",
"Name: 9093, Length: 973, dtype: object\n",
"Stembureau 30\n",
"Adres \n",
"Locatie SB30\n",
"description Stembureau Mobiel stembureau\n",
"Geldige stemmen 25\n",
" ... \n",
"\"Leefbaar 's-Hertogenbosch\" Paul Kagie NaN\n",
"RAADSGROEPERING ''BOSCH-BELANG'' NaN\n",
"gewoon ge-DREVEN NaN\n",
"VOOR Den Bosch Joep Gersjes NaN\n",
"geometry POINT (0 0)\n",
"Name: 9151, Length: 973, dtype: object\n",
"Stembureau 31\n",
"Adres \n",
"Locatie SB31\n",
"description Stembureau Mobiel stembureau\n",
"Geldige stemmen 8\n",
" ... \n",
"\"Leefbaar 's-Hertogenbosch\" Paul Kagie NaN\n",
"RAADSGROEPERING ''BOSCH-BELANG'' NaN\n",
"gewoon ge-DREVEN NaN\n",
"VOOR Den Bosch Joep Gersjes NaN\n",
"geometry POINT (0 0)\n",
"Name: 9152, Length: 973, dtype: object\n",
"Stembureau 32\n",
"Adres \n",
"Locatie SB32\n",
"description Stembureau Mobiel stembureau\n",
"Geldige stemmen 24\n",
" ... \n",
"\"Leefbaar 's-Hertogenbosch\" Paul Kagie NaN\n",
"RAADSGROEPERING ''BOSCH-BELANG'' NaN\n",
"gewoon ge-DREVEN NaN\n",
"VOOR Den Bosch Joep Gersjes NaN\n",
"geometry POINT (0 0)\n",
"Name: 9153, Length: 973, dtype: object\n",
"Stembureau 76\n",
"Adres \n",
"Locatie SB76\n",
"description Stembureau Rondvaartboot Toerist VI\n",
"Geldige stemmen 148\n",
" ... \n",
"\"Leefbaar 's-Hertogenbosch\" Paul Kagie NaN\n",
"RAADSGROEPERING ''BOSCH-BELANG'' NaN\n",
"gewoon ge-DREVEN NaN\n",
"VOOR Den Bosch Joep Gersjes NaN\n",
"geometry POINT (0 0)\n",
"Name: 9661, Length: 973, dtype: object\n",
"Stembureau 68\n",
"Adres \n",
"Locatie SB68\n",
"description Stembureau Drive Inn (evenemententerrein Het L...\n",
"Geldige stemmen 285\n",
" ... \n",
"\"Leefbaar 's-Hertogenbosch\" Paul Kagie NaN\n",
"RAADSGROEPERING ''BOSCH-BELANG'' NaN\n",
"gewoon ge-DREVEN NaN\n",
"VOOR Den Bosch Joep Gersjes NaN\n",
"geometry POINT (0 0)\n",
"Name: 9853, Length: 973, dtype: object\n",
"Stembureau 14\n",
"Adres \n",
"Locatie SB14\n",
"description Stembureau Mobiel Stembureau\n",
"Geldige stemmen 24\n",
" ... \n",
"\"Leefbaar 's-Hertogenbosch\" Paul Kagie NaN\n",
"RAADSGROEPERING ''BOSCH-BELANG'' NaN\n",
"gewoon ge-DREVEN NaN\n",
"VOOR Den Bosch Joep Gersjes NaN\n",
"geometry POINT (0 0)\n",
"Name: 10427, Length: 973, dtype: object\n",
"Stembureau 18\n",
"Adres \n",
"Locatie SB18\n",
"description Stembureau Mobiel stembureau\n",
"Geldige stemmen 50\n",
" ... \n",
"\"Leefbaar 's-Hertogenbosch\" Paul Kagie NaN\n",
"RAADSGROEPERING ''BOSCH-BELANG'' NaN\n",
"gewoon ge-DREVEN NaN\n",
"VOOR Den Bosch Joep Gersjes NaN\n",
"geometry POINT (0 0)\n",
"Name: 10431, Length: 973, dtype: object\n",
"Stembureau 23\n",
"Adres \n",
"Locatie SB23\n",
"description Stembureau Stembureau Mobiel: Wkp Zout Veere\n",
"Geldige stemmen 55\n",
" ... \n",
"\"Leefbaar 's-Hertogenbosch\" Paul Kagie NaN\n",
"RAADSGROEPERING ''BOSCH-BELANG'' NaN\n",
"gewoon ge-DREVEN NaN\n",
"VOOR Den Bosch Joep Gersjes NaN\n",
"geometry POINT (0 0)\n",
"Name: 10497, Length: 973, dtype: object\n",
"Stembureau 24\n",
"Adres \n",
"Locatie SB24\n",
"description Stembureau Stembureau Mobiel: Okp Dom\n",
"Geldige stemmen 35\n",
" ... \n",
"\"Leefbaar 's-Hertogenbosch\" Paul Kagie NaN\n",
"RAADSGROEPERING ''BOSCH-BELANG'' NaN\n",
"gewoon ge-DREVEN NaN\n",
"VOOR Den Bosch Joep Gersjes NaN\n",
"geometry POINT (0 0)\n",
"Name: 10498, Length: 973, dtype: object\n",
"Stembureau 115\n",
"Adres \n",
"Locatie SB115\n",
"description Stembureau Tent Nijverheidslaan\n",
"Geldige stemmen 258\n",
" ... \n",
"\"Leefbaar 's-Hertogenbosch\" Paul Kagie NaN\n",
"RAADSGROEPERING ''BOSCH-BELANG'' NaN\n",
"gewoon ge-DREVEN NaN\n",
"VOOR Den Bosch Joep Gersjes NaN\n",
"geometry POINT (0 0)\n",
"Name: 10525, Length: 973, dtype: object\n",
"Stembureau 116\n",
"Adres \n",
"Locatie SB116\n",
"description Stembureau Tent Nijverheidslaan\n",
"Geldige stemmen 377\n",
" ... \n",
"\"Leefbaar 's-Hertogenbosch\" Paul Kagie NaN\n",
"RAADSGROEPERING ''BOSCH-BELANG'' NaN\n",
"gewoon ge-DREVEN NaN\n",
"VOOR Den Bosch Joep Gersjes NaN\n",
"geometry POINT (0 0)\n",
"Name: 10526, Length: 973, dtype: object\n",
"Stembureau 117\n",
"Adres \n",
"Locatie SB117\n",
"description Stembureau Tent Peter Benenson park\n",
"Geldige stemmen 285\n",
" ... \n",
"\"Leefbaar 's-Hertogenbosch\" Paul Kagie NaN\n",
"RAADSGROEPERING ''BOSCH-BELANG'' NaN\n",
"gewoon ge-DREVEN NaN\n",
"VOOR Den Bosch Joep Gersjes NaN\n",
"geometry POINT (0 0)\n",
"Name: 10527, Length: 973, dtype: object\n",
"Stembureau 118\n",
"Adres \n",
"Locatie SB118\n",
"description Stembureau Tent Peter Benenson park\n",
"Geldige stemmen 329\n",
" ... \n",
"\"Leefbaar 's-Hertogenbosch\" Paul Kagie NaN\n",
"RAADSGROEPERING ''BOSCH-BELANG'' NaN\n",
"gewoon ge-DREVEN NaN\n",
"VOOR Den Bosch Joep Gersjes NaN\n",
"geometry POINT (0 0)\n",
"Name: 10528, Length: 973, dtype: object\n",
"Stembureau 310\n",
"Adres \n",
"Locatie SB310\n",
"description Stembureau Mobiel Bijzonder stembureau 1\n",
"Geldige stemmen 26\n",
" ... \n",
"\"Leefbaar 's-Hertogenbosch\" Paul Kagie NaN\n",
"RAADSGROEPERING ''BOSCH-BELANG'' NaN\n",
"gewoon ge-DREVEN NaN\n",
"VOOR Den Bosch Joep Gersjes NaN\n",
"geometry POINT (0 0)\n",
"Name: 10623, Length: 973, dtype: object\n",
"Stembureau 311\n",
"Adres \n",
"Locatie SB311\n",
"description Stembureau Mobiel Bijzonder stembureau 2\n",
"Geldige stemmen 55\n",
" ... \n",
"\"Leefbaar 's-Hertogenbosch\" Paul Kagie NaN\n",
"RAADSGROEPERING ''BOSCH-BELANG'' NaN\n",
"gewoon ge-DREVEN NaN\n",
"VOOR Den Bosch Joep Gersjes NaN\n",
"geometry POINT (0 0)\n",
"Name: 10624, Length: 973, dtype: object\n",
"Stembureau 88\n",
"Adres \n",
"Locatie SB88\n",
"description Stembureau Mobiel stembureau 1\n",
"Geldige stemmen 78\n",
" ... \n",
"\"Leefbaar 's-Hertogenbosch\" Paul Kagie NaN\n",
"RAADSGROEPERING ''BOSCH-BELANG'' NaN\n",
"gewoon ge-DREVEN NaN\n",
"VOOR Den Bosch Joep Gersjes NaN\n",
"geometry POINT (0 0)\n",
"Name: 10894, Length: 973, dtype: object\n",
"Stembureau 89\n",
"Adres \n",
"Locatie SB89\n",
"description Stembureau Mobiel stembureau 2\n",
"Geldige stemmen 35\n",
" ... \n",
"\"Leefbaar 's-Hertogenbosch\" Paul Kagie NaN\n",
"RAADSGROEPERING ''BOSCH-BELANG'' NaN\n",
"gewoon ge-DREVEN NaN\n",
"VOOR Den Bosch Joep Gersjes NaN\n",
"geometry POINT (0 0)\n",
"Name: 10895, Length: 973, dtype: object\n",
"Stembureau 31\n",
"Adres \n",
"Locatie SB31\n",
"description Stembureau Stembureau Mobiel Stembureau\n",
"Geldige stemmen 32\n",
" ... \n",
"\"Leefbaar 's-Hertogenbosch\" Paul Kagie NaN\n",
"RAADSGROEPERING ''BOSCH-BELANG'' NaN\n",
"gewoon ge-DREVEN NaN\n",
"VOOR Den Bosch Joep Gersjes NaN\n",
"geometry POINT (0 0)\n",
"Name: 11032, Length: 973, dtype: object\n",
"Stembureau 0\n",
"Adres \n",
"Locatie SB0\n",
"description Stembureau -\n",
"Geldige stemmen 0\n",
" ... \n",
"\"Leefbaar 's-Hertogenbosch\" Paul Kagie NaN\n",
"RAADSGROEPERING ''BOSCH-BELANG'' NaN\n",
"gewoon ge-DREVEN NaN\n",
"VOOR Den Bosch Joep Gersjes NaN\n",
"geometry POINT (0 0)\n",
"Name: 11101, Length: 973, dtype: object\n",
"Stembureau 132\n",
"Adres \n",
"Locatie SB132\n",
"description Stembureau Stembureau IJsselhallen drive thoug...\n",
"Geldige stemmen 52\n",
" ... \n",
"\"Leefbaar 's-Hertogenbosch\" Paul Kagie NaN\n",
"RAADSGROEPERING ''BOSCH-BELANG'' NaN\n",
"gewoon ge-DREVEN NaN\n",
"VOOR Den Bosch Joep Gersjes NaN\n",
"geometry POINT (0 0)\n",
"Name: 12038, Length: 973, dtype: object\n",
"Stembureau 133\n",
"Adres \n",
"Locatie SB133\n",
"description Stembureau Stembureau IJsselhallen drive throu...\n",
"Geldige stemmen 48\n",
" ... \n",
"\"Leefbaar 's-Hertogenbosch\" Paul Kagie NaN\n",
"RAADSGROEPERING ''BOSCH-BELANG'' NaN\n",
"gewoon ge-DREVEN NaN\n",
"VOOR Den Bosch Joep Gersjes NaN\n",
"geometry POINT (0 0)\n",
"Name: 12039, Length: 973, dtype: object\n",
"Stembureau 232\n",
"Adres \n",
"Locatie SB232\n",
"description Stembureau Stembureau IJsselhallen drive thoug...\n",
"Geldige stemmen 113\n",
" ... \n",
"\"Leefbaar 's-Hertogenbosch\" Paul Kagie NaN\n",
"RAADSGROEPERING ''BOSCH-BELANG'' NaN\n",
"gewoon ge-DREVEN NaN\n",
"VOOR Den Bosch Joep Gersjes NaN\n",
"geometry POINT (0 0)\n",
"Name: 12053, Length: 973, dtype: object\n",
"Stembureau 233\n",
"Adres \n",
"Locatie SB233\n",
"description Stembureau Stembureau IJsselhallen drive throu...\n",
"Geldige stemmen 73\n",
" ... \n",
"\"Leefbaar 's-Hertogenbosch\" Paul Kagie NaN\n",
"RAADSGROEPERING ''BOSCH-BELANG'' NaN\n",
"gewoon ge-DREVEN NaN\n",
"VOOR Den Bosch Joep Gersjes NaN\n",
"geometry POINT (0 0)\n",
"Name: 12054, Length: 973, dtype: object\n",
"Stembureau 358\n",
"Adres \n",
"Locatie SB358\n",
"description Stembureau Stembureau Mobiel stembureau 1\n",
"Geldige stemmen 70\n",
" ... \n",
"\"Leefbaar 's-Hertogenbosch\" Paul Kagie NaN\n",
"RAADSGROEPERING ''BOSCH-BELANG'' NaN\n",
"gewoon ge-DREVEN NaN\n",
"VOOR Den Bosch Joep Gersjes NaN\n",
"geometry POINT (0 0)\n",
"Name: 12118, Length: 973, dtype: object\n",
"Stembureau 359\n",
"Adres \n",
"Locatie SB359\n",
"description Stembureau Stembureau Mobiel stembureau 2\n",
"Geldige stemmen 169\n",
" ... \n",
"\"Leefbaar 's-Hertogenbosch\" Paul Kagie NaN\n",
"RAADSGROEPERING ''BOSCH-BELANG'' NaN\n",
"gewoon ge-DREVEN NaN\n",
"VOOR Den Bosch Joep Gersjes NaN\n",
"geometry POINT (0 0)\n",
"Name: 12119, Length: 973, dtype: object\n",
"Stembureau 360\n",
"Adres \n",
"Locatie SB360\n",
"description Stembureau Stembureau Mobiel stembureau 3\n",
"Geldige stemmen 89\n",
" ... \n",
"\"Leefbaar 's-Hertogenbosch\" Paul Kagie NaN\n",
"RAADSGROEPERING ''BOSCH-BELANG'' NaN\n",
"gewoon ge-DREVEN NaN\n",
"VOOR Den Bosch Joep Gersjes NaN\n",
"geometry POINT (0 0)\n",
"Name: 12120, Length: 973, dtype: object\n",
"Stembureau 361\n",
"Adres \n",
"Locatie SB361\n",
"description Stembureau Stembureau Mobiel stembureau 4\n",
"Geldige stemmen 36\n",
" ... \n",
"\"Leefbaar 's-Hertogenbosch\" Paul Kagie NaN\n",
"RAADSGROEPERING ''BOSCH-BELANG'' NaN\n",
"gewoon ge-DREVEN NaN\n",
"VOOR Den Bosch Joep Gersjes NaN\n",
"geometry POINT (0 0)\n",
"Name: 12121, Length: 973, dtype: object\n",
"Stembureau 114\n",
"Adres \n",
"Locatie SB114\n",
"description Stembureau Stembureau Mobiel stembureau (beper...\n",
"Geldige stemmen 109\n",
" ... \n",
"\"Leefbaar 's-Hertogenbosch\" Paul Kagie 11.0\n",
"RAADSGROEPERING ''BOSCH-BELANG'' 8.0\n",
"gewoon ge-DREVEN 0.0\n",
"VOOR Den Bosch Joep Gersjes 1.0\n",
"geometry POINT (0 0)\n",
"Name: 12504, Length: 973, dtype: object\n",
"Stembureau 115\n",
"Adres \n",
"Locatie SB115\n",
"description Stembureau Stembureau Mobiel Stembureau (beper...\n",
"Geldige stemmen 80\n",
" ... \n",
"\"Leefbaar 's-Hertogenbosch\" Paul Kagie 9.0\n",
"RAADSGROEPERING ''BOSCH-BELANG'' 5.0\n",
"gewoon ge-DREVEN 0.0\n",
"VOOR Den Bosch Joep Gersjes 3.0\n",
"geometry POINT (0 0)\n",
"Name: 12505, Length: 973, dtype: object\n",
"Stembureau 116\n",
"Adres \n",
"Locatie SB116\n",
"description Stembureau Stembureau Mobiel Stembureau (beper...\n",
"Geldige stemmen 119\n",
" ... \n",
"\"Leefbaar 's-Hertogenbosch\" Paul Kagie 3.0\n",
"RAADSGROEPERING ''BOSCH-BELANG'' 3.0\n",
"gewoon ge-DREVEN 20.0\n",
"VOOR Den Bosch Joep Gersjes 3.0\n",
"geometry POINT (0 0)\n",
"Name: 12506, Length: 973, dtype: object\n"
]
}
],
"source": [
"for index, row in df_geojson.iterrows():\n",
" if (row.geometry.centroid.x == 0.00000):\n",
" print(row)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Het zijn dus duidelijk allemaal mobiele stembureaus, die kunnen we in een aparte dataset houden voor later, voor nu zijn ze onbelangrijk voor de kaartweergave, laten we de dataset dus opsplitsen in drie dataframes, de originele, één frame zonder de mobiele stembureaus, en de mobiele stembureaus alleen."
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/tmp/ipykernel_58008/291552514.py:3: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n",
"\n",
" mobiel_mask = df_geojson['geometry'].centroid.x == 0\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"2520\n",
"2521\n",
"2918\n",
"3579\n",
"3580\n",
"3581\n",
"3582\n",
"3583\n",
"5494\n",
"5784\n",
"5785\n",
"6260\n",
"6261\n",
"6738\n",
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"6863\n",
"7348\n",
"7364\n",
"7857\n",
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"10525\n",
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"10527\n",
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"10623\n",
"10624\n",
"10894\n",
"10895\n",
"11032\n",
"11101\n",
"12038\n",
"12039\n",
"12053\n",
"12054\n",
"12118\n",
"12119\n",
"12120\n",
"12121\n",
"12504\n",
"12505\n",
"12506\n"
]
}
],
"source": [
"#de waarschuwing over de projectie die niet klopt kan genegeerd worden, we zoeken naar data die x = 0 is, de projectie gaat geen effect hebben op die data in Nederland\n",
"#filter de data en print welke waardes 0 hebben op x\n",
"mobiel_mask = df_geojson['geometry'].centroid.x == 0\n",
"i = 0\n",
"for item in mobiel_mask:\n",
" if item:\n",
" print(i)\n",
" i = i + 1"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" Stembureau Adres Locatie \\\n",
"0 1 9461BH SB1 \n",
"1 2 9461DA SB2 \n",
"2 3 9461JA SB3 \n",
"3 4 9451KD SB4 \n",
"4 6 9454PL SB6 \n",
"... ... ... ... \n",
"12591 703 5391AR SB703 \n",
"12592 705 5391AR SB705 \n",
"12593 750 5382KE SB750 \n",
"12594 751 5382KE SB751 \n",
"12595 752 5283KE SB752 \n",
"\n",
" description Geldige stemmen \\\n",
"0 Stembureau Gemeentehuis Gieten (postcode: 9461... 784 \n",
"1 Stembureau OBS Gieten (postcode: 9461 DA) 562 \n",
"2 Stembureau Zorgcentrum Dekelhem (postcode: 946... 566 \n",
"3 Stembureau Ontmoetingscentrum Boerhorn Rolde (... 1495 \n",
"4 Stembureau Dropshuis de Eekhof (postcode: 9454... 347 \n",
"... ... ... \n",
"12591 Stembureau Stembureau Gemeenschapshuis de Meen... 268 \n",
"12592 Stembureau Stembureau Gemeenschapshuis De Meen... 398 \n",
"12593 Stembureau Stembureau Gemeenschapshuis 't Zijl... 663 \n",
"12594 Stembureau Stembureau Gemeenschapshuis 't Zijl... 170 \n",
"12595 Stembureau Stembureau Gemeenschapshuis 't Zijl... 222 \n",
"\n",
" Opgeroepen Ongeldig Blanco Geldige stempassen \\\n",
"0 2780 3 3 700 \n",
"1 1396 0 0 518 \n",
"2 1409 2 2 516 \n",
"3 2209 2 4 1335 \n",
"4 477 0 2 298 \n",
"... ... ... ... ... \n",
"12591 0 0 1 237 \n",
"12592 0 1 0 359 \n",
"12593 2321 2 0 552 \n",
"12594 0 0 0 151 \n",
"12595 0 0 0 193 \n",
"\n",
" Geldige volmachtbewijzen ... \\\n",
"0 90 ... \n",
"1 44 ... \n",
"2 54 ... \n",
"3 166 ... \n",
"4 51 ... \n",
"... ... ... \n",
"12591 32 ... \n",
"12592 40 ... \n",
"12593 113 ... \n",
"12594 19 ... \n",
"12595 29 ... \n",
"\n",
" Nationale Bond tegen Overheidszaken - DH Haags Belang INL Den Haag \\\n",
"0 NaN NaN NaN \n",
"1 NaN NaN NaN \n",
"2 NaN NaN NaN \n",
"3 NaN NaN NaN \n",
"4 NaN NaN NaN \n",
"... ... ... ... \n",
"12591 NaN NaN NaN \n",
"12592 NaN NaN NaN \n",
"12593 NaN NaN NaN \n",
"12594 NaN NaN NaN \n",
"12595 NaN NaN NaN \n",
"\n",
" Rosmalens Belang De Bossche Groenen \\\n",
"0 NaN NaN \n",
"1 NaN NaN \n",
"2 NaN NaN \n",
"3 NaN NaN \n",
"4 NaN NaN \n",
"... ... ... \n",
"12591 105.0 2.0 \n",
"12592 174.0 6.0 \n",
"12593 47.0 19.0 \n",
"12594 8.0 11.0 \n",
"12595 10.0 2.0 \n",
"\n",
" \"Leefbaar 's-Hertogenbosch\" Paul Kagie \\\n",
"0 NaN \n",
"1 NaN \n",
"2 NaN \n",
"3 NaN \n",
"4 NaN \n",
"... ... \n",
"12591 6.0 \n",
"12592 2.0 \n",
"12593 53.0 \n",
"12594 13.0 \n",
"12595 22.0 \n",
"\n",
" RAADSGROEPERING ''BOSCH-BELANG'' gewoon ge-DREVEN \\\n",
"0 NaN NaN \n",
"1 NaN NaN \n",
"2 NaN NaN \n",
"3 NaN NaN \n",
"4 NaN NaN \n",
"... ... ... \n",
"12591 0.0 33.0 \n",
"12592 3.0 31.0 \n",
"12593 2.0 62.0 \n",
"12594 1.0 22.0 \n",
"12595 2.0 28.0 \n",
"\n",
" VOOR Den Bosch Joep Gersjes geometry \n",
"0 NaN POINT (6.75899 53.00524) \n",
"1 NaN POINT (6.75990 52.99975) \n",
"2 NaN POINT (6.76600 53.00494) \n",
"3 NaN POINT (6.64736 52.98281) \n",
"4 NaN POINT (6.60459 52.95269) \n",
"... ... ... \n",
"12591 0.0 POINT (5.43290 51.72810) \n",
"12592 2.0 POINT (5.43290 51.72810) \n",
"12593 5.0 POINT (5.45919 51.70595) \n",
"12594 1.0 POINT (5.45919 51.70595) \n",
"12595 0.0 POINT (5.45919 51.70595) \n",
"\n",
"[12532 rows x 973 columns]\n"
]
}
],
"source": [
"df_geojson_clean = df_geojson[~mobiel_mask]\n",
"df_geojson_mobiel = df_geojson[mobiel_mask]\n",
"print(df_geojson_clean)"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<AxesSubplot:>"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 720x720 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"fig, ax = plt.subplots(figsize = (10,10))\n",
"nl_map.to_crs(epsg=4326).plot(ax=ax, color='lightgrey')\n",
"df_geojson_clean.plot(ax=ax)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Nu we een mooie kaart hebben van nederland met de stemlokalen erop, kunnen we gaan kijken naar hoe dit verhoud met de bevolkingsdichtheid als eerste voorbeeld. De kaart is opgehaald van het CBS, eerst gaan we kijken hoe de kaart er op zichzelf met dezelfde projectie uitziet."
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<AxesSubplot:>"
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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NeP1VF7Ju5YQ//qarTv97bNvHV5/ZEywX8iY0UPdkyzgmUEqHCxTtMDeEElVGcsAvca6rlmBNjerlGJgFcCISN/t0w5mSvXBDREUaCT6uZsqJNcyDJqfieOlitWoYoCbtQBtjFcQDmFEY9yG15GxU4pzrJGqMY4kMawkurpaS51QZW1o1wcQ4dMw42hsrTkHGZ5aQ52D8yLddxcGjPTdeesFp+5r7jixwtK9ctjbarT96fFdWIW91D1VhIFgsUTMTzKk5TgBQKCoMg0KXSKwE3Q31bP+IZCslkjKH/D5CRI5MYhOjEb9pJJysw54zCkejutJWsRyvPs4o43uwqNTx/yldF9XdPSq1tISNJFPLkU4bvYhQhwFVpbrRiTJlvPsUSFJh2SnOes8NOedZjHFkYeBffOph7tmy97R+XXfny0/u5uqf/u3QOt2yD6JRxZBIS89RBDk6SEqalzbEa2c3R4sFRc19rHSY0Fmc4WJIH1+vSMGlIFIoqiGnUSs2DPjQU/tK3y9kRdSg20kmq0XLaZ6JDgmPkkQDUNFcLytR3euAY9R+iIVkt3HWGShvfqXs0t2C86paQJzBa6oQRNcgDd2qzqce2HFKv4dZQp5j8eHPPMaz+w/z6Yee48nnD5+2r3vhqmV86I4reOpnP8ATOw/i1RKAiftb3WObQnN/sMb5z7OljBC0wZOuUe1yCVjckSJY8aho7qgYqrFdoWJxN2ZFQgqlaJAOuphHVnPMBnyIZI28zMNnQLaJhnb5NSTbY5AaZ8/YsuyiqhUFi3M4rW0mzpWtLcUdKXl2VZLEkESG2lOtju/9x95wBe+97bJT+j3MEvIcis88vJMHtx8AlGrOv/+jJ87I+xya7+lrxQZjoa8s1IGhH+gXFoLwTaxAiUZlCNw0NzcaOKPZ+1lOJqVVs+CXRy9ZQDJxJcYj4sTYIdGedoItUuhUs9rFf+4DVgfqMCR9L0Abc6PkNcU1yrTaScwi8Rjwe1ZOswG8Yn3NkY7glvualPh7Q6AARBFVShfkAxsG3v+6TaesMjBLyHMk9h/t+cR92+Mpr9E2bt93jE/c9+xpfy8HuqKoFrpSkCLoXEE6TTqb4bXiVql1wGuFOkCN9nLh6AI2GNYb1QJECYA1+1qVIHH7kAwCxjbUJVpgEYmhvzpObTxwKETFRVDtgtFTQDphYb6HGkRyTzQ2vojlgBNIzmsgx5LzUZBSqBLnXrMhdif7hRhvYIHIpuqAypR3617wCldcfHp2J2cJeQ6Eu/Ph33+EHfuOUPsBr878wjzVK32rQKcxfuYjDwQy2ZZ8KeCKmiIuKBqMlqSneSlQYqbnRek6oWgkcCmKD1l9hgGvBkOlrz1DP0QFy0RpRzHN7Y2GvgbfVAMBbd+uk+wfQaWgpnn+LIgKgw94jcTKA2VuothYzZP0E+2oxfupKNJ0eQoBOllQ9jBHNaAnPEYy7gNaop2eH+op/+xnCXkOxKce3MFjuw4x6RTpUhlNC8tLxwdu33RG3rOBM+QgIMShLGlrNjJfxIXOZVxrilZRoeQehUT1QRW6Eq1jkQBYOmUYapwLa6UO0X7WGhS80FWO5WVXDxaNQAhTZbVNbNZsiG2SpMMpimeCmnuAQ8OA1UqnZTwnakOKNbiyjbggLhTpYh2saLTGlpS71kh720MRduw7wq9/+elT/rnPxh5LPJ4/eJTf+vqzIVHRiNQsZr2c3rj6p38bGE9KSbqOtrJIIKPkUSqOgrJoa8JDJwrPJeC4scfchgR4BHOno6PtTsa2RXBUhZhbDsS4QUoXlSvfTxJ4oe00Oi17YxaZ1LeQ+0gUtXRYDQ+QWodsoUvyEBqhXDK5awBKOfhvAJAgDO6IDdOjpGjS3mG+P/Xfx6xCLvH46Nef5eh8P11DGpHIRQDDaYjfumcbv/DpR3nqZz8A5PTPQyDZkn4Wc37PAfr03aeVRiN5PW7k0LXJMUkuLkueC6FmlfVxTEG+pp0PIUATKYJbxb1GGzpUzAXL+aF5soJ0SgTPpxaIJTsn9i+LdohqSEBaTWAoGlnzUMmjtbTxxYNE4DoSClQ0COptrEO8ZZMmOZWYVcglHIfne762dR9tm2Jxi6ZS+I4bTn0f79MPPsvdW/axbddh3nLdxWOF7Ieaq1WRLK5KsOBk5Im6+3gTWru24midntXaPVqAmmoB4pk4lPaXcTXKfJpAJo56oSnBTb/3/FMdqEKsbi1fljPSPPPl50iCMNUq3oUUCCHjg3YlFUXiawWvtsYOZ0N5M8lj1mggilmo1o2UCRswE0qZJeSrOu7dGvqpOtYiC7U0dZbNFX7wzpcvd1/N+bd/8CRrlhf+xntvZteheTZesJy/+5H7AJh0OcZIvmnNVs7aTN6hqRQLwWip1TEzrG3mi1JKVMhBPM6ZqjlKILRxCOkPzUF+EcErcVZ1S9TTxoSNFllDhU7AvdJ1JRLJYykajfMplme8rGKl3e7uKFNxLST0WwfrkaIxQnGondJ5/txF0fw5iARFMJI1kVd3Dh1deNm/jxavhKX5+4CfJx6Sv+TuP3vKV32exJef2AO0M1pozqgHqflH3rA51dlOPvpq/MKnH+HqDWv44OsCFNp4wQu1YuJGk3H43gEVzZYya/WEJHITZ7qiqET1ds0VqKHGWpURrWyFakNsb2ioy4lEJTPzOPNlOy4I7jpW6nF9yjxlJONhodqNrXBxHVk4raMQbRXWEl3VlH1USIcugIJSWgeAU63Se+i5jqXeDNESgI6njiwxEtl5aP5l/T4Wx8mcId/t7ncsUsv6OXe/3d3vAH6LsDR/QUgMcf458H7gFuDHReSWU7zm8yb2HpkPVopVxIxSlMsuWsUP3HkV77jp0pf1NbftPcI/+91HeMcNG8dkXBztDNkeBME/BTCSBxDtYs79i0sQzkWI7URFu6kSeekKpgUaY6cEalm6WHuqPuDDwGBDVNc6kCsaKYgVUliNnuZueX6OJGq4aMgTBHNINYb9FEE6ZRh6qOCB6aBJbtdc34pGtyJdknUU0Cndru1Nzs/PT2elGjquku1sXKrnGfTlx8sGdU7Q0vzNwGPu/oS7LwC/RlTVWZxALJsE97JILPpesHyOv/eB23j/bZe/rK+3de8R/t0fPMG333gJd7yEts7/8gO3JpoJEK2aSdvWT7DGo9X0RnWDVBAPfwwk3KTizCh0HqMFcp6ooogUOlGsKyAl9hxVGMzo+wXMoitwT8KPxTRSPNpRq+HPoRKoc6tilvuUxTVkI8sk5qUTARsYrFIHH3Xtqjnqod2qSSAwB6n59TSraglqnvcx/tDq4wPDHXYcPEbfn9os8kQT0glb8rvTejx+ASL/WES2AD/BcSoksAnYsujvW/Nj3xQi8pdE5C4Ruev5558/wct6dcdtl6/LuZ+zbuUyvue2y15yofil4ncfeJb/+OUt/MRbr+FN1760zujf+y/3J7vFRjZL25Rwtdy0yP+8IhrJiUeL6SLJZY3XqU6NblCLqmuegljJlc0RQyfKJNtZEaXL/Un3gVp7+pxbivg48fBsHRsC3M6loWhuTPKYiDMuH6sK1WIuaTXOjjHnDM6qSkOV83t3o9O5mHF2BbeB6jXOp0kZXL9iwmRyaoOLEwV13r7YllxEHnL3z7r73wf+flqa/xTf7KB8PNjpuDXd3T8MfBhCKPkEr+tVGb/0ucdZv3LCpChXb1jDu2+6hNdtXn9SFm+L43fv38G9Ww/w1997A5MTXQ9q44o2KG+zRmvzOc/1JI0JRpHchySqI21dGcQsktZDVa5mO9qG6lF1E+30cOEq2lpmpVjMN81hglOFmE8y5dCWLlg9InFOLO4MFiQBc21bjlm945xYdBLnWVF8iKpXiybQE99De6h4Jqfn7peWkl2yYf0A4ly1Yd1UavJlxgm9erEtOfARohVdHL8KHM8vciuwGAq8Avgm4GcWL4z7t+3j9x7eycFjPT9052ZUlY/d9yyff/TkOgcz55c//xh7Dh7jb3zXjSeejMSN5maYxf9WM+rQJ1tlgGFA8vzXaHHWV6pVam8x2/OUvpCQ51Cg5swwBiPJLogpYAzg24y1LRUnEQKTdLVSxEsATtqhJQAbG4bgoA42Vl7BKIngjmfirGbSfDwQOi0hsNUpQsVqZRg8xLnSWyAqddL8HJoyO6pjEr7jNFgznFFLc+DLwA0icg2wDfgx4E+c8lW/yuM9r7mUay9ahbnxTz7xYGzgq9CpsPfQMd5zy6WsWjZ50dcfmR9QFX7hM49y88YL+J7XnvyZUyXazEKowRUPeQttZm9djhMWMYbEDdXJqH3qdUi3KsCdgfCd1ElHkRJyGZURyRUkQM829yPv+xTUqik7KUk2LzkfVfcAjeLgiFUPfRy3GH9I01XPB43HFohaDZIFghbPN4txhphR60Aderq5uegGFlXN5geCgVdj5YrlvPaKdSf9c/7GOKOW5u4+iMhPAR8nxh7/2t3vP+WrfpXH9yX6+Yn7n2WYX0BUcRNee+3F3LLpwvFmXRzVnB0HwgX5d+7ZxuoVy/ihN17J7Veue1nXYJlEroSEhWbSieXIIRJNShv2pwHOolZX2ljGp7PAyaTDcxbpNeZ3brENYm6UbvoaGRO9tc0NtBGKalIJY5dRGlkhVe+qG13pogp68GNVY2VKkntrLvGzfYGhT6iXo6FmMOkmDNWYiFAJqRKkjompEg+nW06TgvkZtTTPv38U+OgpXON5Gw9s3x9q3dqhOPsOz3PdJd/szbHQV/7X33mArXsP58lNWLncX3Yy/t7//Z383O88FLRVbwP42PK3xqrJqjSKPamH8pt8I4dVkRysxzpkDOWlgFfHY7uJkvPLOoyDzXSkAklWTEwkPMAUKTmfjIeV5gqXeL5/EShKIa5Vc3wTQ//gznaljNcmrQXN7xeCjytdoXMPdT0cq0MW0oK6U92Z6zq+97Uvbwz1jTHjsi7hcJyiSkfM3p5+/jAf+eqWb1rz+cT9O9i69xiC5nzMOXRsngNH+5f1vu/5f382qWkBdEgCLSmwFnUrWOeZJpGA6rHUG5S4GG9QoEomiyY4AyMvV5It41LASwxFSodooZOoYLXWREMHFoY+Xa1kSq9TT95tcGM99X+SThRzQxFUBc05KDheDRummjih1TGt/pTstiVnoqpIF6DPUPuUFVFed8W6FwhTn0rMqHNLOFSifarEjWoOH//6dr70xG5+9E2bQYT/+tWtPLf/yAhdB/VUONpX/stXtvCn337tCb/ffdv288F/9vnx774ICW1uVDl/z3Nf/jnFiU1Aiqe5KkC0gm0zxaqN7JyYKSYXPbBSEI8ES6mQNkqRrMSC4jWSzW2gAtSo1Kba6K4jqSBEspL5I7FYrSiDG52Eg3LRsMyLR5xE5c5vVJr41TjCSfkSKVBDge7CVRP+/Duvfzm/3uPGLCGXcMz3FZUuzluafaMIew4f48OffhwL2JJG3RJC1jC5X9z1xE4+9PpNrFu57ITe7xP3TQFw92EqfuxRLWvJ8aNH1Qg6qebsz6lDpdSQxRBrSuQaq05MuTXTNS2huFHbmdgVFcMpoUIO45aL5raIoiGKRY5JSlbvXKkazJh0ZeSd8oKEb/KRKcvRqnVTMrewGRhq8GOBcd4qyU4ibdhVQ73uvbdcltX49MSsZV3C8ey+o4nS+2j15n3FB6MfeupCQP0LfYwjqsWQvpTQi1kw+LUvPTMCKt8q3nLtou2RVIFDFNVJELYlGTXSxKdKdqdCEaXr4mOiRAWrA1b7kPaolWHo01cj0mm6QhUrV+ZDvk+mkEjIeSQbSDQOsFGVLTWpYoLvqe9aRDBzhmpNvCf+nytiSV1tnFwPEKeYxFmzC0ZUKRoPArOcT8bDMLZupgDTLZddwHtvOT1nxxazhFyi8dWndnP42Dx1iE36EOwdgguqkXCx71cCYMjK0YxILf+75+k93Ldt3wm959tvuHjKZU2UNepEDNUVS3W4IINvvnA1y0pJxFER6TK1CKdibf9FAkxSSrGtTuGZoLVnGIZQC2eqmSzuiNWxGlo1inSZYqkKkFQaHa9BYjSjQcMz6/FaGWofuji6aNaZGh7etH6cUbWuJFMoRjMDQ43tE3NAYdWKCT/4xs2n9XcOs5Z1ycbdT+8L/qTAYFGdoiDE0NwQilneUyGckSZw4NOFLRF4etcRXnvFi3NXvzEe+Z/fz5O7DgHBC31y5yE+9eCzHDkWCfO6zRfyHTddwjUXr+ZXvvAU2/YdYevuQzlsb6uLbVPDYuWK2BYp0ta6EkyNN4m20AK8KR4zR5dAdlt7OxVHztc2cWZiJOEeYsYplpoPpy5s53LzRHBMSigAeOPcTlXIJdULWoMtGkSCYh4EiTpQJnNsvGAFm07Bw+PFYpaQSzS27Ds8yvhHCxVD7LiBm3p3Gp+2cxTdeM5c7GGx+iQpd3OdctMiVfTXXLaW77h5I5999HkOzw984PbLR07tUI3nDxzLWWTjl8XrpIBZnNucdI9KSzf3JvHY0KE4c4YvQdvICLaN1wBd6jAg3WRk+sS3GnNMFag52JfGag875UBHXaK6yyTodbVnTGdt6gCGajfq5kB8mZh1FnofKN0Ed+PKdStP+nd6IjFLyCUYew8vcODIwujSlGuJhPpbtFiOx1A9b2ZB8i5OAMMDAhEX7rjqxKvji8XKZR3v+wYR4M89spOvPLOPZlTu+b5t4x9rpHGwSiRGqswJxJyzWb95ckpb3UxaWhS7EJnqJmGIU30YdyGREMyyRhyQkTeEF9BhWkNNlKI5OS052pBg9dSk0UkSEiRHNSDp0Jy7ISIs6zreceOp0+SOF7OEXILx1af3cmzBR1nEtgjlEje8+ogbJksl0USLquk1aGOJBI3UttMZ+44s8J/vehofevo830kJHVdPKlxrJVvhI92mmuhwkwgKN4CQcwwSu0WraGFXrqnZoyWAGEsGUUlyd4BHFSmF4onGuo9Df5fw++gkNfEayJW0OVcghavccsbbdVAtWmaS8J4Jv3yibL5oViHPm/jq1j2ZRAHPq3h4J+aNHjuCoTeqYhhOrRXpuvTNCNTTUxp/fjj9CfnrX3qao30kTiEFnlRj4yNnkoHOOBWh1iF62FKS7J0NqyZ9TgipRw+znkoASprsHisWLfHoiEWOgjQ1dqBIobql7QGIZUWGGH2mhE/b24qKTn6+UgjfEBeipfUQ1wrZkJh3Cky/5hmIGcq6xGL3oXkee+5w3EDV6YeeoQ5YblrUWkOSUYWuKKaLkdZCJ6UB/WGIo4Vf++JTp/UaH3/uIF9/Zh9AenfEJkRIYDSEs0RFS4S1yzFJ0ZxxWggZ2zCMy8gxc5S0vbMYsQI+LhADlNzASGDIwxey00CYS2rWlpR4tDrQz8/HCMVat2HkejWiUKmxPiaWa1aCaJdrWFD7haT9RTtb5MylzaxCLrH43MPPMQx9ij4pXYkWTQhPxlJKtGCJVpbcNaQXtLN045amP4WIs23/UZ7edZgr1q/kv351GweOHAMVVs51/MDrr2SuO7kb7I+e2MUAo4ZqDvTyvZNOl9VRxqrTxiNJOncJb0cCDJLcxheCNxrmrk1jh2TuhOKceGjaFcCL0LrMKkaJhcXg9Wi0wqUr4wiluk/V1iFJ7MH/FW9g2RQMohp0XYI+8fqX2rQ51Zgl5BKLJ/ccplBGv8VRghBA6gicBGCzCGntwruwSLcIuIysPHi052c/dj9Xr1/NE7sOx1eVqCy7Dx7jr77nppO6xviqNm2vPLw6RIQw0In/8QRNmm5q47yOFBwJ1fMhieXt46ZJtxMPWchhCGNYJ4CeHAcx8sAFiqC12QUkuGNEi0sJP44kFbg4JLMHD5dkw1PZgCSoNx1zT8erkAxBnavXn/5xR4tZQi6xmF8wXNMevN1w4uMNPrajrWI0+QoCbXVNVW+XUEhLcubQDzyx6+Aopxh0UWXHgZejlNbOpO0sliAMaetG0NBoY4WmCtVQKm8vDZIB2a6aBtd0ej4MG4NaumAMpdcG1TBJ8WSNdpjkz3qeRwGkCLVG526enUQgYdH2OwxuQU4AvIFGgWdnNU0+r3nqQCuTk+woTiZmZ8glFrF50DbiZfwNJUiZI4LQipEGTEiD60nyd6sgcQattY/N/xqb/2aVaqEAvv/wUf7g4Z0nd43VqUnfG4YFFhYWMA9pjXhbSaZQIK0u0TpjcXZj/C9HIBafp6apRdzOh6HzWkQTmQVXhS6NcroCXmMrpRo+WJ4tNfYaUxQrPCw1JT7ia4eUCHQ6QbTkallTSMgEjZ2z3BbRYALVFNQ6QzGrkEsstu0/Qha7SDgP/C+kbKZwvVWjeizKikw9K1Q7UAhVUqXLzf5Jsl9EFDOPFSSBI4Pzhad38bYbLz7u4vPxQkoASk2CsVhs9LsZQ47bxQTcqfJChLVkdfek9NRqOZhPAn0be0C4StHGJqlCHvDtyPYR0UBINZK++XcMZslLDbOd6TpWPMAsHxDxdZLZEyUWgPl+gaIBzUaXYvFvKvHxMxSzCrnEwqxVwLihzYyh9vjQxw3f98FrVaHTUGULr48EKlQDwE+7tehQNRLCs+im5L0mW+axHYf4X3/7fu55eu8JXaNbSCOaaGKrYePWSRl5pJbb+UjybruQxhgsHK48TU7rENW7CU81FlKMOFobHlVXJFBlE82nVU0DV6bUtxJoq3Qlfk5DkPFj2J/8VwuiQopKxiMk7dpJjmzRsNwzr9gQPh5ICCRPToNlwIvFLCGXUDywfV+YjiZn0ghx5JItlaSVtqZMhatgRTMhUrQYDwkKJOdoCfSLjaY2WVvGncMKPLbrIL/8+SdHb4+XimaaEyuPngCKp6lpFJPO40FQstVr7FrRGNG4xhm2KyUlGYM8b7WnH4x+WGCw8I+UfJDgodye3Xguc5SxXW9SHJKmP13pAgDSUMSrQyw4gyHqaJG85kVHA3Hc62hdXlxTsYAYPdXhtHh4vFjMEnIJxZ7DC6gWBidMSHO+5yXPL+3GztInLmjzy6AVFCGkqWKA3YygNGF9z4ogGrO+IlDwdLcKZs+3Ssr1q+bQ5Is68cbeZDBcIc+PIiG3ERXMRjqdmI+jBpc2vwy902D7CDopwThK5bvaDzEOWeSoJe1g3USSCwH2KIR6Viwck7NQKfE+Zga1YkMcykNwoMaR1pPf1Bg+IbgeM8lScIFlJ6Hed7IxO0MuoSgaN42a5WZ6PvUhqlCiowGBHAdplZCXqIT+S+pvAGlQCo1wBzVl82n6p01+I+LerfteVEXt++7YxKq5wm/cvZXqltXO0jTHp3KONd/edWS7aO4rQjBzcB/VCBq448SeomjCsQIpjhM6qg4LQ3Bb24gHomRKm4GS7WfOOuMagiQeJj8dF61exluuWc+mC1fy3IFjXLBiwq5Dx3jD1ev57Xu2c+/2A3QqrFnecWh+YBgM0Y7bTmJz5mRjlpBLKB5+dn/chEnlUo+lW8NHeYqmJB7slUawiwohGrNFaahke+LXPgAWMyYlpCvalkTToKm1ToflwG9+5Rlu27T2RYGe99xyKfdv28fXtuwG0azG8YaqGqp1I14SLa3mWEKykocoVpeD+HYO9MSuKiYeMpQSS8qSgI6JMOmCl4rVSHAhdi1VwgtFo8LZ2FG0UU2cV9evmvAzH7yVtSuOP+T/q++5kZ0HjgLCZetW8Nz+ozx/6BiPPXeIS77BmOh0xiwhl1Ac632ck8W5J25ISWKaNxGadn6sliTyPEOJhJRF6dL02BEpsb4l5OC8Y6xDEiJRoKg1xkrEU7uP8PlHnufbbzr+VsNQjcvXr+LeZ/dhQyK+sZRIaZ4YEhxbTWpfQ1hjNJMq5ZLqbiNymddlARRFdTfcmv7rolmhFNo2jKRcpdWUEsk1rWDc5NPB40HWSWGh8qLJCEFNvGzRitXGtSvYuHYFt206c9URZgm5pGLnwaO5U5iSSyLjGcqIZWRc6PuB0nUgoU+Kt5tVqKUwIXYCG43Ogc6VoTENEt2P1jASobbBfoakgNYbr1nPyrm4Tao5X3ziee56ei/P7T3CniN9GNTg6Lgalqe3HLF0EKRsgd6GOPtZJutQUzG8W8T6SfhHBkRKVNQSI4tcdsGpIXSFjRXcEugCo+u6tDoY4gU1V7FEcRmwkiDREoxZQi6h2H9kgaH2gFBtIQbfIpQ0H7U8MAXgU0ZAw0mhXyeqkBgDpMZ4Kr41NFQ8dVVzHKIkBcgQmVYMFeXgwsBnH36O9712Ew9s38/v3LuNR3YcRFyTahaVNsAkSzXw2DZpNgHGdBE5CN8Sn5szUjRGC25OcUnlkGhLpQAEx5WRD+vTBeIcLU49SJLdk6BLjCriIeS1slArWhQ1pwjcv30/t16+9hX7/Z5IzFDWJRJb9xzh2GC5ISEha+hl5GZ6msCEUhtAnMswprL2kbdJ/QrGigvjINuTcxo7gFFhyJY3JA59vB4TQ3Hu2bIfd+cT923n0Z2HAvwpQUeDVN/QAhRwxTV8PIIQnnS2RFjdQGq6F6fEhzDd0LD83iXPh9UqjA5V02ttgleS33OoyIFqjHyCwhp+lo2EL9pRmpGOGfsOHuMXf/9RHn724Bn/3Z5MzBJyicSxvsaeYyKlmpVuHG8kB9WFkZKmOQLwXCVSb+MLSaDRKRhNgC1sJkOsKXedYkzhjao27eNiD1E5ND/wj3/rXh549kBsnXgM5BtT1VJceJxHNiEswmMjTo4pnKxxvTFWqGgHzWWq5FxTco9zoun/IaECFxZwlaGGml2tmZx5thQEs5zJ5kOi/SyBNOCJYX9BWbZsjis3rOKR5/a/Ir/fE41TsTT/OeD7gAXgceAn3X3fibz2tFz5qyzu27Z3TIjMt4at5nhj7L5o032vjkqsIjllJFe3yYY5MdPzSJyhH7ASbBOwtFazXHoeMJ/eDmYBGO3cN4RBTqrLWaoTVM9q3hDSfE9pkJEADIzbKQl0SskzZM5PAZrkI8T3IxLryS5JVs/5qZQOhoFJmYA4tcYIJE7cluSJEh4hufYVRTSFnlUxjDdet4GbN67hXTdtPGO/z5cbJ1Mhv9HS/HeB29z9duAR4GdO4rWz+IZ4as/RFwzyp/oyUdHEbZw9joiECnUIUrUNPTb0YQ9nFdI2bqEOmIdblJaCdiGnLyWIB6WU0FXVREEzYhczxg1dV2JGqhoUuFLoujh/tsVpPJg2bmHBbk3acajBqAkJuWiZpZEYporlTbMmSN2RoOqKmowiVG7p8JE6rZqUvCAVaH7/FaupwCfhigyNehfEhaeeP8S3XbeBpRgvG9Rx908s+usXgB8+9cs5f2PfoXmaPwWUaC2T/CzmDFZpW+4wRVolK2AcpmI80qTy20Z828QXHLWspNmuhsdMIpWLH8+ayKXH52ppcvo51Pdg/oTpTLSKXhrg4sFw7YgqKHkerAH6vGAc0nVjkjUjn0a88TbfT65rKdBH7Wx6XqN0iJuhXUeosgYw5IMFZTBHJE6QzOf7gaMLlWVdYanFiVZI5ziW5ovizwG/8zJfe97H3sML7DiwEDe1eZ6RBoYhRH5dg8UTRPL4T0sirQiuJeh1SQgIbqYFnzyOc7hE++razFGhydlFlTIWYTrBlCGG+pLzBvE2ekjiQaPcSewyBr81V548aH+aBG6RJJ2X8OoopSCdYkQ1rUPjsfZUyz2SpNq1C6uDpxCWhJJAClDhsTKl2cqjklQ5CS8Rz4fbEIfpFZM51q2ce6V/zScUp2RpDiAif5/Y9vmVk33t4shk/UsAmzeffkXopRz/7atbYutBc3anUNtpUVv1Cd1RTeJAJFN4TIRTcZrhFNAaGq0B++ck0gl1gTS8keb3mEk4qthlmNjYwLoLliT1BhiZQafCkFsYo06qtsNkJPGIsLqMs8k2tggTmzCCDYAI8BhNuKVYVn5ckwQuIqlB20h2QmOfGwVNTxAa0ttYSWhY5YlxdH6Bx57bz3WXXHDCK2evVJxQhXwxS3MR+TPAB4Gf8BcxkDgBO/T2eR929zvd/c6LL774ZL+PczKGavzWPVv40lO7Y7ZISSRV6Rp1zkPGoll6I6nSLZFgobomI5rozZ1KLEd1bfUo3nO0a2uIKYx82Rfemo0Vkwu9iyulVXKdMIgHjS1TxrXjqJwm4OEREnuLbT25Junb4trDAiu3R5qhjoZ/iMQZERX6oceGOjKUvJHYkSSAN60haZBtyIeIBME9K+fhfuB/+9iD/JvPPc7CYHyr+NyjO7nnmb2n+Ns+sTgVS/P3AX8XeJe7HzmZ156+yz+34+tb9/E79z3HwhBGp9ODE3mDaxqFFlw9SON545rnTVYjUcxivtccmkbeK5KZ1hRictCeZ0MIES0zwxZJU3g1ao5Hqlm0xSJMNEEWmVa1JnbcZCqj2qash6SLFTF2EW97j3kmFaFK+/esqsSDQwkbgaazWrTtewJYoL8Cx4aByWSCaSRl23721mJrkAFcJMGduOA/fHwn9209wIY1sb1SRNl00Qp+5E1X0+WgdfeheX7jS8+w4YJl3LH5zNLm4NQszR8DlhFtKMAX3P2vLLY0f7HXnoHv45yMN1y1nkd2HORTD27DSPlGmerijJsR4+pSQ1mZjhokPCsQp/eg19VaQzkAo+aGxRjuo0RGyfrZ4ViVPJNGqASwhIIMUVlcI3ljizqAlloHinaZnHFYNXGGoaIlq1vuJIaQc5rbqI92ASFcnLubiYa6p5GOx2Ol1kpJnw8ISY6uxAS2lKDYaarCiQvetS2ZJPTkE0SkvVcsNx8aeg7tDWNbcefRXQf53AM7uHHThdxx9Xqe3nWIY0Nlx/5j7Du8wLpVZ/bseSqW5sd1qVxsaf5ir53FopAASUqR9JwJ4CFG+k3SXmJ/zz3U3fLsNNQeLZoLs9LyNDbiRSPFu0gSyZvevC76TEmR4Rg42OK8LXFdYQfgqOgord/oevHHYOkInqY4cbbrCkgXjByzIcjiPkVYixaslBzzRLW0FCUO01aiyrbrU8HRcY2sGflIXo9qSTfmmJNa7RlSebx0JDMi2vA2qxUpuZ4VP5/Y6XR6hAd37OfB7dmmitI73PXkbt77DXYKpztmTJ2zHA89u38kSkNUPash24EN9Im0WolZYUNao22UkIxsi8eSi7gaGjNWLLY4LFLYcrvCGwDkEgP63JtcfDOI6Zhc4xmxwQROIJke5HRRw3IbCvLR0OaIkvPPUtLrsSGs4YrsNSU96hDyJFkRk74a5HWJVjh49Hle1NDrcanp0Gx4CXAnVtEmwfBRDSkPr3jNn7K0HVDHcqbpCf6YG5MkPIjm+RfHhp7fuPvpM34/zBLyLMaW3Ud4bt+R0MpZ6FPtLGQ7ujwvNX/FkuepqjF7kwRyXCxGE57GNB4tLkSyuEvOF+PMGe1ewfLrhezNVEmgxajaKFMpEFKrR1uBVWLLnxj4N5kRH4nskIfVqUqAh5iUeirBaUFLjDG6LvRTa5IaPB9MQz+MZ97mbNV8QeJbDX9MMU1CResiNK7XNaphp1Ar/cJ8Q8WgOuKVZlA9HrtzJkqCZ+7hyPw/fuRrPPn8meO/zhLyLMbH7t2WBJZ4GitNGEpDIxRNg5iUvve49cYnvBC9Ze5KaqhixNpSorUolDxbeooZi4YigVjOJPN6XmDK47UdEwOMEcsRhqVUZQBKCIteZVOYN0i3uBeC5J5gVSKsNR8kmKAulGTHh+pBPIjIChfVPfVYF4Lz254dYe5q8fMoIUsSu8/BTootlGxjXcIioOQepQ9ROS0QWPdszROBcsmnEjEHVgo79x/jI3dvO1O3xGz96mzFgaMLPLDjYMpeTGF7S3RUclUqPBYBK1CmSGuAHcGOiVFEACaRstF6hSYPjORYfIrQNmCF5Kd6+DC2GIZ4CLQBf4wXSO3VVPVuVQVGdDSnpnmetGgxk//qDWF1TQJ4qBxUixY0/cZRT3pRDD4Dcc3dyBhfgNUBN6hY2Kp7Cn8lNUk80OARAW4JPISpq6bie9uhrEMfDs3d3Cio1Ujr7pagUHQeuw8fO2P3xSwhz1J89pGdHJ3vSc3xpLjlqU0ktUklq5G8AGmNG1nwWjMRFfEQhPJU6B7qwJx2NLAmjbDCoVg7qocjunlQ29q5rkWnrYoQ2yGtTXRnINTt+qGyLB23LKudScwI+2p0c5OR1hfgpue1N2MdH/POaz5K8gEQpXk6+wx0SRqMAxrbH13aAESlE2J5WadyINkDSv7fmH9KkCokHzQehriB1lZq9eTulrGPjS2UfEbMzHZeXVHNueupPQl+RIlRj00ERChYile1uaK/AGm11MIZhopOuumsjTKWrE7a+lFUlOKMbaNKWBS3sck05Bv+mIQD90RT4waPrxU3j7fZ5/itxOd2DbmMJch82MQ1U1I0Oc+nZMULVynPKmnJ7onrCPWASKLWMjdnrSJN/S4fGFbj/Nxa9K4xFhJZbj9XyGuMc62U4A1TiEa+9mHqo/G9lxQV2zjT1Hl1xVef2cOO/fMjayY28GldJbVxL3P7eKhG0Q7vhGKaZySnTGIsUUrbDInEjM41B3AKJTtRk0imUQsj+siYC7bZYouUTm/IrOTuv1uKUGnMDFXz9dmCOmEYW7TLqu/jQwUPlQDR6QKyIjDAMAyjnIe4YDkTtZwXGlldsTwLkq0kyWgiz9WhLifN/JUw6zGPZaxOA90dW/U8ww81ztKqOnYlXgpSc7Y5OCmPzofuuPyM3RuzhDwL8dGvb0fcovVzYUj3Xhsq2nVQdARvjHYeKnHTxeErmCcG7jVlFBuCmfCgxTaF11QHSP6nNYSWRBkbZzWrTQtPVk0pUKsQWq/JRRUfP8fQsfo6nuansWMZIl3gNgVHam6GmBOVx31UkXPVoLolwQCBoVYmkznIitusy30ImRHxRYCRBP9VaCOSONN6sp2s1nzQASW/X0/SgUS7jEt4RSbLx0Sy24hqv3H1CjZftOqM3RuzhHyFY+eBYzy9c3+ONWLOF/MuD4dfTXl7JZ725nQiuA+BwCbv1IVYdxLQHMy3+37kkRbJ+zqTdDyjZgcn3jpEABbTkcVDfDKQVmG0x/NGOs85ZHHM29Z+nFedYNo0kCrOjHG+1ERYYzdak3IqKXuZlb4wTaxWSbMr8HYWlaTweav2MTIYPK3saI1Ak9KcksxjxGGRnBYUP5VF4xoP4MpsQLUE0V4UscJ33nrZGSWkzxLyFY7f+tp2tIQvhjJtsyC2J9ws2s1MPINco5IRaTW3XGpqch6LxKtg3KKIyiDjk76NSjSRXBUPnwwPlmsTMI4vkupvjYBOJF5jknpWqkhob1BLvLcGhbwN8UfNn+oxd7Rsb2MMOB36iYUKXpO6DEw4KlRrL0u00UPf02nIXUppJPhEi7vwMXEPAMkc3PuR/hfX2RQJNPV6YlpTui4VFpxGdPdkSM1NhNefYT7rLCFfwdh1cJ6vPLM39gIt2k+hYQ0hqRF23gG62AhiyIi0qifgsAjwIUcRhuNDBZy+GnOly+2LTJ4EVcokZBdrniNrW9NaLHJV68jOMWvc2GC6qCievopol2c1z/WpkPyfTEKJIBT6ZRy4Oz5a5bU6U6uFIp0F6SGSJoxei4JhwWbyaJGjeYjWvSgjumz5UJFakkI37QACPCpIzFgSZdWwOtAuRyOG1SG1boMjS+K6rsaxQdh3pGftGdylnBEDXsH47a9vpR9Sm1Rq3lqarWuo5be6KG34nmcpiGrSD5U6pBlPDfeoWmsCJJZeh4VJSnOIpllMwvha0qHKCyGrH59fVCksIperUiToem01TAnB40iukv+1AbrSFUUnBS1xo4fLVVAAbRhC02cIkCTOnJoPgngYhMNxkg+Icy+xiJaIaTwgqlU6UWS00QyhVUlihadjVYiG5QJaPvkk5680Er+0/+K8iYY0iKef5jgXzvnvf71nyxm9R2YJ+QrFlj2H+crT+5LyBrRxgYCYEVsSrR0UarXQo6nB8+yHcMWS1JApJfms6YxVVPMGT7YPkYw067kEcULaw/ASMo94zjQ9QJExsiqPXaxY6PIks6ad4Uh2ULPEkwRtwpouHgbkg2HSTRPabcB8SC5rH6LJAXNijQsrxLUKzU0v3pcc4SQjyNvqmUNZ9L5aNJQX+oVEh/PJlutnNsSZUqQpx4YVHd60hqJl9toz9IaLc+/Wffz6l58+Y/fJrGV9heI37t7CsaFGTzoK3QAItdZo4TQqYGlIa9v2hVHaMHM5vBktgJTcu8+vFmdHkrDelMnJdjjLbrTFOShvEpHjcA7CqsChK0EEiCE5IyBEVrTQOSUqZQI74akRSKtaDNIt282SSa4a58LYdInvzd0Yam2aV9Fed5MQ5RqtDqK6lgYeJencALTJaOaVeJPwCLDMfBi3XmKsOt0hbYyiqIhDClHHD84LrCjK0b7nghXL2bhmNoc8p+PJXQd5+NmDCW4U6jCEa1T1VIGbikl1k0BSiwuW1Db3GPQb4ZiMJ9mEmI2ZW4IajQUT6gJmwdoJYoC3Zpgm1xFc0vYeAt00IUuuJbnpOG5olLI2YnEDunbmy7NWnnk1219rKG/x4KIqaTeei9YqibZKACztfOlCl45XVoeo4Nk6Sro/x0eaFVF+3yJYqijE4jYpgzIlHaDxNYcaY6YuN0Ozj6CZw7bvdeWc8A9/8HVs23eUmy694IzeK7OEfAXilz/9GHUYEJyqQimCemGwqBnuMfII2cNs54qOy7pGcFqDJ1CSQxqsnnDAkgR2PGX3A9QYAmVBLGU/aNUjxyZ5s0arF5/bwnLDQUZUJIu6lizuUamiNOVrU1tnPAeLpECxpDVdoqFxYCPAzWiFawJWxaJ1DwHmZPPkOKWYU93D0TjfK6hDkkrlOr5vKBXkWlv+PR56OVZyo+smiS7HNklrv0O/dQqEXbdxLauXT7jp0hc35zldMUvIMxyfevA5dhw8OrZOzZBJciTQDGOkKi4BQngROit48RAkbkirx7pVnmworgxkpUxydxENdW8zBjPmvBshfEkFAa+VUroYjQwyGuToog3loLLB4FCHgUkJAxsdIkFqG7HI9L09KX9xozN2BE48ZKTtbeXQPd7HQ4S55ihknN2EGJeb5d5nEByojcoW7x37o6G1U7RgTVayqft4rIWFqofEtaaPpC5atNZEiYeFHi0dWjrcjWVF+cE3XnnG75MWs4Q8g7F97xF+5+vbR/YHFme6JKGNVnDhiZEvciLx1EZOdVP1Rki/x9S6kVyrqhUvHYIzSFRgK4VJjTawQA7sHbFsCylISf2aNoRfdIaUotnukXqnBSuRiOIOg6FdtII+bRrBYhwiGmOVhGCCd5sgVOjVxMfDhi6V5zwXiNuuYkoQhNykj0SKRgxoWiYqk4CoSxmr3Uh8aAwizesT8uEEiOf3HCRzxZFSEIW1K5S3XLuRjWuWc9m6FWf6VhljlpBnKPpq/ItPP8ahY31q4wQnU9DwvpAYgHuJ9mkk0iSY4u7k3Z9VIsWFuy6g+RieULMYtFMSGiDi6KScLBuMOF9JVAxKEgd8Wk9GZgFRLSOBGRehy6JtFC1MvzbTh4yYR2UjEij+1YPD2lBkG6IyuTOknIeK5ll6yjFt7WcT55Kcl2oSzSVnlpImtSGaHBW5uDNY7Hym+hVkl2I2RHs7fj+GGKOh7fK5jj/1tmu5/Qw6Jb9YzBLyDMRQjX/1e4+w68B83JBFQt4+ZNdG5kdI3cdWQ601b8JKNaN0BekENR1v7LjHy0iDc0msRPM8pcS8LqGOJtfBaH7qSAkTHEneZjO/UZ2ybQC8afy03ULacH26DjbOIjK5GvUsqlaOVJLGVmnc0aQKumOJsGoSwcOrI5K8HyqTrgutHNFp9SQfFNogKqG6pU9mtKma7a3alJYIjuU5PrpXiUrbSPZjqwyvuXztWUlGmCXkaQ935xc/8xj3bT84/sLbdkLBGDzWf3obEElov3QhheGxV9iVAjVuMssEGNUCaDQvSbU2MvHyid+G7N5WmwK+t9xwIHf6oqUDqNNqscjFVFO+3ww0Z5nBJMo20KfwTRusg4ytZLSHcdNPRxJJfFgkuiymOQeNygqx4TE36XBRqg3R5otj1ZhM5sY2uM1h4gER/FlJJJi4nBjn5IJ2PCQUavifeHVqF+yCqfCHcPsV687kLfKSMUvI0xz/8ctP89Vn9ua9HTenYCwsDOHeBKCRdO5BCNe2DAzZiEaFq2SbOCKtks5OZXo2gkBkxi8dCVslHgKx9T+FENu0sjSUlEbNOx7K6mNLOgKp2RqGgkDOHa1xRttWR7KMEukUJ1Tn2sOh5VOul1kjxI2E8hzWi+P5GnGnOAxWCRG5VChonSfJuGnjkVENgPFjEEeHTifx+QrrV81x4aplDLViLtxwyWruvHr9mbg1TihmCXka4z/fvYVPPbgTiJGDmOeOICHka0aRLm7CJk1hUUUjFTSBmxg0dlawpJPFonAirXnzRcKELYAkothGGpix0A+hBSOKyJBE7lg3ktKN79vQVx2RJcJFi0Xn1jbqYKq72uUDxjGopGAWSQyIWeq0igI+XTB2kfDqSIRVS1M1j0SONnWaTOrCIM6kSXko8XMMlAuzHJGURHVrDVbQ4nBiMbuNRhDecNVF/PE3bT5Tt8RJxywhT1Pc88wePnnfdqqFmWg3mQt0s5B6ocogAponoTYX0LgxxjlYE6lwCQMbcv6XZycEqjj0lhUgUrnvF+hKmQojO3Sl5PJynPFKA2FyHtfmboFiTvcKgVjOxUbjVsn2L67HmXTQdExLcNwwg4Whp0vE1z0rfc5DvbQ5arpuaRv0xzcZHa5QR04hSTRwXOPhZWmdPp5PfUB0kj8Lo6aaeV8rE821tGzhG3rbpDmWzSnvfs0lr8DdceIxS8jTEPdu2csvfe7RWLqVgqvQuWDFY9CfrBu06YR7Q+xj8G9tiO7jTWjZpjVT1uqBtPY1qHVx5swzZK4ZiRRKaYCPIzUZPJrZnliMS2leqdkiSoqiT1vW4gFCqcaifGtoFXJLIlFbnT4wVKDTDpVW2YlFaoxSClUC4XQLEtxQB1y74PTkWa5VYVLuX/I8WKuh2rVnVl5P24ts52GlkzizF3XcKlicYUMvyFJvx9mwZo6r169i7Yql5YI1S8hTjINHe37hM4/RD+Q9r3QuDI3mhsaqUB6eLAmqGhbCkGjogKFDA0JsVEQrqQejeeMHn1tHECU4mPG+6NRpKnlucY5rSGjOFcUqKuGOJZpjBm2jhoimQt4SRGgVKSqOBbk0K4/mRn1cs6st8qxsp2LJJC+jBmopgaBG61nja1tIPooEObw9OUSC9NcqZswVcwMkLjNAnTwzNyIGXcqWWKUfKpSO269az1/9jhtG/46lFEvvis6hONZX/snvPsBCzfbRspQ0jZm8q9vIQMebJ7c5ao9ZzzD0UXlKbG6gwqSU0IpBRqRQJM5lArkp35acPccWsfERNy1oV0KWwpLbmSTscaWrKaY32HUxMcDzjNowHWmD9QCSxCVWuFTwEmBKu86QcdQckTiilWYvPjL0tD2s8qGSa2DiMNd1MFGghh5OHej7gWppKtQeBPm9tPOgisXCduq0ao4ywktkEkP/IqzolId37H+BQsJSiROqkCLyFHCQwPMGd79TRH4O+D5gAXgc+El333ec174P+HmCS/FL7v6zp+fSz3782z94nC17jiY/NNeKJFXMEnSIm18DZndjWKh0XRdDcALAEZUXzBc1z3x8A9Lq4iPhPLU7yNNgnLsyzxKTDSDEgyFDI4i3hE2NnXirJJu/4LuLdaoXnnnzIQPRUorlGCXH/9Y0d4BW0YVsUXXR/LRlZfNynCKsklVRPVpwKU710NyJMmiYNbIAlJKAk/v4I6kuuUQdjsmG43VIaUv48lN7+NJTe7hx4xr+2Buv5LqL15zBu+Tk4mQq5Lvd/Q53vzP//rvAbe5+O/AI8DPf+AIJ7cB/DrwfuAX4cRG55RSveUnE7z/0HF/fsj+8I9oNvciF2JyQwK/hEOzusXVQcjkYUgOncWzaeKIlX7SdYUEuWB6cOg2OJThTFfFpJY5/iVbRErGtQ419wyGqct/31GphQTdUzHo8wagWtRo+9NR+CGtwi93Mvvb0tWehHxiGWDhuLW2rN+KxLqXZzkYBi6+tKaoVNnodUpNhI5Jsuan6nSWqHD/T6B7CIyQ9Ozyuy+sQCgf5/p4AzxQky5xXRrUQgMeeO8TPf+JBvvDErtN+f7zceNlnSHf/xKK/fgH44eN82puBx9IFCxH5NeD7gQde7vu+knF4fmDL7sPc9fRuHt15mIUFo/fwNp5fsARjmvZMUK9i/hU3mBQBDx2cAE8YExdAavg+ShfAzrRK5kTSBdERwcibPudrInETepzn+jbKkPCgWER/RSdJbCcQ0g6hSFP6Jkco8gKUlaKU2HmC1Hc1nE7jYTMRxv1McRhswCwkPdpqWE5KWKiVyaSjUMYlbIQAopwRnGrfc6gQxBNmcIBhtCYXywVv0aDc5c+saKj29VYRUWrRNLj18WcX62GRoiqByM6j/Ns/eJIDR3q+85ZLAzE+i3GiCenAJyQ4SL/g7h/+hn//c8D/dZzXbQIWax5sBd5yvDdYapbmX3x8F//xrqc5eGygLd+qB4SvsR0b8P0wxLC6BLoqqXWjCFSQkvSs1qqJp8KaTO3bXKLK5mBbSLhfIsnJEcmQpjALtTIpHVKSv+rOxNsYYiTnBI5TLVaadCpoJUasLEGOQBJtXdQvaQOMUu7fsl211habj6tRkLIXed3B6SOYRCLMtQeIDfGw8qTG5RxTi7Z3bJSCkI/0mGeaC16VKf20PbR8PL+aa7wnQcUzr/GAGEGg/N49H0AQ519XqMZv3LWFY7XyodddcaZvrZeME03It7v7dhG5hDBofcjdPwsgIn8fGIBfOc7rjve4Oe5JOpP8wwB33nnnWT9tH+0r+48shLx8nl1iJaGmQaoAFSnKRDoGN+Yo4W0Y+UeVUEyzJv9PoKFucd6RPPe0dg1LIrkG3D+kLYB2JUneccOXHK/YWPYKZlG9IFsyT0YMTlXL1i8qs+uUQdP4pf4NKKskF9WkgqQmrEtuUETfF220jnzQ0lbKgnjE6KrV7NiTGucCkw5oVdotdHBqJPAgQleatEbOJyWl/1NxrzdDZTIlX7QzsWYLTBgOqVmIeVlyeyXO6+qePiWe6DHM91Nvk7MVJ3SGTBNW3H0n8BGiFUVE/gzwQeAn/PiQ1VZg8TLZFcD2U7ngVyoe3HFwumkQ+APDMAQJvJ39NChsqilNkecjU81tvGSqZII1VbUYxhOaOYOFANTQx43XBHyLMEkV7/BgzDOlJxkv30tqQP2ltIQPMMY0m7Q8h7ZhfNutbJsObRE3cJYX3g4ucY4jGTfRek9HOOLZFqqM7S+UMdHj9TUMZVt1MsZxUMnXBU2uICJ0pYQRkFeq9bHZP4Q1XfS5hdHJsrla5Xkx/EUslRWgGOPXDWmPeJ3VnmML84liB/hz5foVvHbThWf+xvoW8S0TUkRWicia9mfgu4H7Ej39u8CH3P3Ii7z8y8ANInKNiMwBPwb85um59DMbZuGj0c+HYaqK0amG3o3F+VDI9g/PNaBGUY4l4qKKVxs7LKsDtfbUvo+Vqy52A6VoEMyJkYdLgynjCW5pAxd/buBErHJ5ej5C2J/Hkc+nQ35pS82WVDnJX3o8ZcTaNkeetxZFW+JtO4h4VFptb+lNJW56TmtwbPsZtPlgjGM0RhDioDYCVeMZr3HvNMcg2aNOSocXZag9PgzUOkx1iFi0sVFj1ENa4DGCRA7pmiUSAlhdV4IPW3u8Gn/mbddy82VnVp7jROJEWtaNwEdSrbkDftXdPyYijwHLiBYW4Avu/ldE5HJivPG97j6IyE8BHyfGHv/a3e8/I9/JaY6DR/vYAOg06V4ehjY1LOHiSRwwffjbx7a7Jp/FCePRvg7MeRf/NgnbbSu5DiWx8lhSWqP6kGOPwsiMHpHWgElUgswdiRgJ5R6SjUPOCOM+b8N64mtZ7gemkFQpzYvR6EM8lW5RhayDgcQwvStlzNUqRlMIkEk3traB+sYDxFu77M1no7WFzWKAPJS2BPSRShh2AFnFyZFlSStzKeElkkwcs+m1IJ6dSMwfLR8+PuQKlsVDC3x84HWiWHE2XrCCK9avPMN31InFt0zIREhfd5yPX/8in78d+N5Ff/8o8NFTuMazEquWz9FN5uj7IXofwtMwKGaKuSbrxZIZE74UVh3V1rDCRNOFiigMptpUXUJ9TfJJ3YbblDa8YzHSmgUpRxrJWkGDiuYDFahWEe3GKuXkAnDXoSJhsSZEkhdJV2Snk/y+Fh0iSz5oulSEG6uqEPuHItEaDkZNoMZqZaIpGWKCMzDU0K4JvkOoz7Vzcjy2UmA5es9Qn8uxRTBx6vizbLsqTbUu35Yi8ZBsauYVkK5LkKkBOoAYK+cmHJlfgKQjXrBswp9+6zWcSXuAk4kZU+dF4q9/543cevnaaQvmU1kIaWJKi1pRLHRdpJRwbiqxAe+EXVpUjnjSi+Zoov34xac3XFMI4IVI6zCEoarnLl+/0OfmO2EFXpRJifOVlwJaEC0UzVbY01qunX1NcztDMQ2Uk0VUMk978rB7kwZf0oSt1Evq3BSKaCwZa4ntk7yeotEahoBbzDGpwUzyGq5eOZ2M9xTBqVwwV+gSBEsu3ngujtyNii75gDAJpQEtHagiRaipZzsMMRrqVHjdFev4Bx+8lXffvBGRwtUbLuCn3nMTN2xcOsSAGZf1JWLPofmsYHHjtLOKu9MPPXMlW9EuIH8dK0eQyk1Ac8YYSnDR3YV3RGOb+AiIuIMPSRDIs99QY3PeVBJRjDoak4s06aHtUArp4jZFPj2eGgGmtr1LS5Al1j3iIdEAm/Z6S3DGkgiTm4riY+Vp45xWW4oLdG20kICWhxiX61TmoyP+PTppB4ZskaMy//CdV3D5hSv53z72EMf6WMrS/Lkb8cOSNooiWmGrRpe/B3KE4y7cfuVa3nDVet563cXMTeKH86NvvpqNa1fytus3sGyRSe1SiFlCvkQcOFpphjKh0JZb9OSCsUzNZ1q7Vy00YjxXi9QJoeGki3lKWLgHlU5qtKtCbHLMTSbpAhXgzEQnMUsskkTrlmjB3lFvWC64VIo0QeOQMqQIo81czj2bpwU5C23ttC9umDwqllmzE/DR8wJp75gPAvHR1KZzohGNJxRYiHEVmjdlq9JBm8nnBaoy2tP9569s5X/+Y6/j+g2r+NqW3bgWui5nleK5RdUmlnlNJeaVQqjSvebyNbz1+g3cefVF3/R7FRHeffPG03/DnIaYJeSLxNO7DnNwfoE6DPR1iB2/Eq1fFyUglmObfAbEnM2bNk7caaPkPQQK6katlmSC+JoxqnAmKVcoHSlzkeMC8ZxvBhjhEruFYcpDzkjbmTBnmh7eIWaCd4322ijejFxbtZgpuretlIhxx0MY55eSK1m0jxMJIQ3hbCiqB6xlmYAloa52VHQ1qrR5aQBcyybKQnYVB472/NNPPsTfft8tfObRnbjBsiJcc9Fq/tFv38uxfmBuLq7jsrUruOqi1Tyx6wA7D8yzclnHn3rr1bzhqm9OxHMhZgl5nHB3nt1/CKs9osqcTBLIKDGqq0zLCh1tOVaS3WwExctFqP0Q5jAlHIVV4uYsueEgGhblmjP+KiEloalnOm4yNHkMz7s2K1OhkdR0pMbFZSjNZKY0Bkzw33APNYGugTUG7vWFuqyDY/RUM6o2ZXEoaSOX3SoldyPNQhYyWDPxkGr+kC6NTug55sj5H0Fhu/7SNfzJt1zNf71nC088f4ShOkcXApH9jhtfWMneet0lzJvx5M4DPL//KNv2HuLH3ryZn3zHNfzBo7u4Y/M6Vi8/84LGZypmCbkodh04ypee3M3dT+1hy96j4RpFtqO9YWIUaxqq2SJlUrTtpWGw8LeR4EyWTpGqyQNtauChaWMph6gSiGArIc1XIlagFs0IPds0lbSty2migw89g1XmSlirmTfRJuj7GHOoe2rhCN2kjC2iECObsghllS72OiVngrSKhoc6nEbd64lLq7VSCL9Gd2egRpKWQJnNc9MEZ+VcYXnXsWrZhB9/y1Vcd8kaigp/+TtuBODoQuX5Q8eO+zv6U2+7BoDdh+b51S8+xaM7DnDZuhWICO+48eIzcFe8sjFLyIyvPrOHX/zcY2H1NngABM0zQ2N2WFLQuC0BpzhGbEZ4SGdonvNkBHECaNFaU7FNXzhjlGw7LZajmnBwU8DPER+1emiMJhJpKY6smgP8TvEaX9OTcCqZZEMNCRHPvBaBUmOPUPPBwTiny2gE+Rpk9CptvmqoBLKKM9LkCiGsVZCx9Y1XgNsQY5H82C0b1/Pn3nkDpehxydwr5gqb17+0bfhFq5fx17/zJp7cdZg1y5fW1v+pxGzskfHA9gPYEAmjAjXUO6MakXbbbnljhTyhm7OwsIAXAQ0PxpIjhGbGSjujKak/mjQ6Xjjm0BwtuDm1T3/DwWAIKzoVgkye4wgtJTc2dKSGhcGooF3L+TifdolQtjXEEXARC7Q32UZSputXWBPRalxYaNoZTaFuXJd0kkoowYgRSeoe0Za7piJ43G5f23KAP3pi12nZrLhmw6qzvqFxOmOWkBkbVs8FA9Jz+6DR0Cy10EQYasVr+AU2pW1VpTNthJM8W01V4qLViwF/IIM2Dhec5LPWgO0j+QZKF7NCSUEb1RIK4yk5EEP+cDQOj0fazB73Gt9DI3oHwpI8zkZybyOJSNiQBRHcFt0O0kClMAYi18w0ObVQcJdFVulTazqVIFEEvhPux2oxrhEPHZ4/eGwn/aL9y1lEzBIy49CxIbVU25Z/cl083JawIVeSYgiuSlQqEWryOS2NUnEZhYglGQWeiTPUNuCvDMMQS7eSZqtFmUwm0Xo2g1IP89PKQNNXFSRmCOLJGGpLwG0peBG4lMRwhxx7eH5vqebmNp2zvoDLagEFaZC3W1WPiHUuURI/FdrqZKgRZGudwJWTw3shEV1j695j7Nw//wr8Zs+tmJ0hgU89+CxfemIPrcw4Qh2skUQC8Qz4MCUILaqJxJzPago2pT5NKIQHgEIlOapBY5O5DizYO1om1DZjzM14gVh5cqFIl9sYCWmaZqK2JJdcRE4FAZRBmcr4N+0cpuc5pPFCGUcg5PwuCAwRdfC4LiQVNjKxE1jCmyJ7W5FapBkgCRRJbGAEIB324DHUL6xc1rF8blYPvjHOy4Tcc3iBLz+5m6d2HeLStcv5xP07GIY4NYpZDNgnBRuMLhHQNqJzH+JclDeq1OCaOjXOmSKY9dRa6bRDCnReMII00I3A0HTG6O0GHlkvgcPGYD3OspJgSUum5l0YFxfJPAw9vRnLSjc6T4n6eC1DE8YhP1bagDKAK120oVxKfKwORiF4usk8pVYLNBfHBgGMoRpSuqi68Q5x3i1N2TzP5m5cvn45f/O9N3PBinN3PHGm4rxKyEd2HODX73qGHfuOMF/Jk5TGSlQN8SnXAF4K0Ivk4BtMZVSVcw26VrKco5pCVM6SJG4jxxexqa/Z05mkJZ0SyKZLaOy086U3i23Peb+OI5G+1mC7ELS6Wo2udAweFLKQjBReaEHXHiYl1QvinNuVRHiTvCAuSF0EjmjsYQY7VhmXqCmIV9zj60W05eRI6NaaDguVgJkcH+L0PFhl265D/Mx/+gorl0340TdffVal+5danDcJeayv/Os/eJy9B3vMK0igpg10cE+NUCXFfYPHiZfw38DH/yce3odq8Xqz2GjA27kxgI9IMBk5rNaMWFul81bpkv6Vw3evMesbZTRwFqwy6eZiOM90cTj4pQQIk+de1bYLEpWziiJNK9XjvGfueG6RhHgy+JhgxJpYnqktxbvUcm4C0AUztSRVrkLQ9Cy38k2CVD9WXQdXOgEvykI15o/M8wu//zCP33IZP/qWq1+R+2Cpx3mTkLsPzbP/cJ9AhmO1p5t0OXrIpLEBTan7qFgafhypKmcigYgONXYbYwhIl1o25LGyOqBG9WC45AAl2DvFxmlfDPU9F6DT3z7Pct2kC75qdqYdua1Ba1l13CFsa0jm+XpPunlKVoQ+atQqmjdlq8wElS2Sd/Eckphhpk7QVBGA7HB13Hv0lAIIGY2CV9IJOcpx2MM12cus3snkWX/Bct79mkvP9K//nInz5lQ9EQkpCPE0oCkjcyRuGlqvFTeypyOTQD8EKorVaAuLjg5UhTYHrPnDlEQfC02ISS0JBkWptTL04TJMEsy1SPraB2LalUJxjbY2N/Q1FglplSbKaxNHTvQ3fUJEgvju2etabfKQPiKlMX5oWx7xeYvvhmndblUxsVoPIkFDbZswV0vwIEJI/kwimZuaXfWQP/EErxRhz4EFLrlg+Zn7xZ9jcd4k5LrVy7h64wWhKaNN1tASDWxJ2NpMckQRGqbaaZwtRycpxVPK0RrR3OPrNLJ3A33MYcgRBxajC+2UoO8oXUqCoKQuTpCtBx9y+z1nfZPUxWFUkBpzMyZ8lkwgkJYyEv+impuXHsQHH7vjVBTw5L0uGmyM+yv5fyS3NBosFN884woXmbjqIa1huYTsBdq+Z+R87l6KMBBLzp9/9HmOLAxn9Pd/rsR507LOdcpfeMf1/PLnHuPp3YfDtszCQy0oabHtMN8vBOlag3sqokjOBWPwn+2ZdzniWFRh3cZ53JBIa+k6pCvZpoHmytSoTpeoS47qY1TibU4o2ZLmPNHyvGsee5pMF6dLkwSZ7/NsmElEjXFLc6SyoPkNHkaxbWsDc+oiCY/BpnZ0k65jsEZhDzIDpcuHWM4fLWei7k1cLncVyVloS9t8UOS+ZnX4D3/0JL9x9xauv3g1r7tyHe+4cWk5Ur2Scd4kJASDZqFJL4ZuBOPwvw642kh9i8G6pBZrpVBiblegWEmvxzgfooovDPSD5bggBa6cRWfD1vk5VizOk22+ZwJeRsu16RA/DXm87RdCX4OEUCXmpP1CT9d1DDkL1KJ0RbNdzf1Ag+algcYxUi2duvJ1Lk63qGEq2gS7muBUm/tkcReNpZdUetOU3lCJ5FtY6NHSMXEf0d6+1mmnUabvDc7R+Z6vb93L/FBnCXk+xP4jPR/+9ONs23c0bnopuBlDX9FOUm4jn+i5RhEsHGBEO4FUK0ecvloO4WusHqW3hUoAQAUFH6IlJoWypK1SZbXwqe5oq5MuSSZPhkycS42FwZibm4uK7HFtsYiRchyZLAEe5YhDNDVXc26aKFFCLM0XKFfHpsSAJlhlTpDspyfNoOHFmDJ/RhJiX7T3JMyC8qEU/PzQ7tFSQiCsDkiSJbrSxffUFf7EeY62njcJ+atfeootew7Hk70aIbwbo0VN3Yu4mdpoI4b5GqSboMYhUB0ndxy7SYAqSqqphQtVyH1kBTQJeciSc08t0do2+poUfAh1OkkxrNra4OZQLADKHJbqdpnwTp4JPYkG8b0ODHQezlciNgI3bRvEIFXTUwQ6D4WjskC+p+TnFXSKsIpjNeQ/dHTP8qTpOak5ngns2errqLygFmT91GcOFk+yfS5YXrhw1atnc+PlxKsa1Lnn6b3jn60afd9jtQbNrYQoU071xrONJh/VJawDAuoU5hcWoFZUCX3W0oUZq5KzOEIhzTWQxUYoaCI6PmKW9FbxGhxZ9z5Q2RKrW+PGiOQZMHEiCdXh8GV0zweEB8MmV6W8CQ83GcVxBBjZFUlRp3ZuYxu6GMyJiFGK4M0+IMcr4lP1Ok+JKifmjlERp+Y2QqEkxdDEETEsVdPb005ERxs7R5eEevjZjFddhbxny17+2z3b2Xt4nsPzCyzrOlbOKbsPzTOZTKgWlVEg3QFyXiiBsLaRgiMhxpuSi5NSYlFX49+KOZVK5924swh5DsyS08BQM8+BeXxQXKDoWIUiTyzNRcdSFMN9B1RD/qOETGRURItqb+m2LNEWerKAtIlQjfPLeG9vBzqZzkFVk/awaAzpufipje1AsJSqVTT1glqrG9+DpzJ7e6tmyT79WZgFkUGyTzYLK4ZgDykH5nv+4W99nX/0A69nxdzSEp96peJVlZC/ec9Wfufe7akLCvN9TzVnvtdxMyOqTNDBpgpubR9Csdx0Bw/rOCES1EDTjbidERt6iKQFOKEwZ6p4b5kAWZFVF7kSL1KnS5S0yXG0oYV0itfpWbeIMNQ4G+b0dDzzFomHyzi+qYGiTscWUHtjUpIIQDu7TaKlHaKFHhZlZG0o62B0JUYt1QNhLV1wZdvX7mvFtK1ylYZDtb2UkaMb22Rtz1KQGmOdpsMKwv4jPf/kYw/yN9/3mvMyKV8VCXlofuD/8/EH2br3cHCxM8UmkwlmFoJQ1uhiHl4XiWKKFNwGBnNKKPXSlRIuV62yOGkc6mGpRoPvc8fRhOoSjsgYk64pngfYEW0yMeSXcAGuauEHoprjEgHvYpfSs5JpSiBKtKCeY5ZqjuU52MywkXFDKMO5UCYlwZ880eU5tK1gNU45XrC87zuZJmQTF45xaSCqaDb4oiHhKjEG6iAl/ImxijVC+4QmIzmkzKPPKUXCcCjcp8adk6DwufD0viP8+z96kr/8ruNqcb+q45xPyMd3HuRf/t5jHDjWs9D3dKULrZhkipTaOCpx7il0mOdmhkH1EHKadF3cyEo+vWto6KSmaCfCkIoBcQNpJHJfmZQQ8e26glWJc2T2xWEu0ypgq34lHLA0pKhCBhGQGse51BztB6PLiXp+mL6vaDcJK4D4p1SCAyR8H90D/CHBnyinJUvpVM5DE3nF2oBkepZsej0tmVu1G2SRLRz53g4lrRRapTQnxymhvRPazYpVY6DGdkra6lUPdLqUdpaAB7btZc/hedavWnbmb6IlFCcE6ojIUyJyr4jcIyJ35cf+uIjcLyImIneezGtPZ/zKF55k7+GjVK/MzU1wPClncc4atzSyLYqRguHVMHE6LXSTSWIujbniU/OcHE9YfJjqllv+fYBAneSoIxhAJi3J0mwmD4nFU7GueVeMbTK4KrW30eWYGoYyIesRMzstJUAS7cbNCh/BnxjVlFy5QhxTi/OhQ6RWjTGF5vZIOkcFnpIg1iIpjKaa3vpeyb83dLrtbkqukFW1RKPjY51IHgkaitqI8CXVEApaujhKdLnq5ZW6EG7Ih48O/MtPPcJwnqkKnAzK+o2W5vcBPwh89mW89rTF1RtWMdGSyF9sHyzmhaiU3OoAq0Hk9kQlC8EXFU/R4UYKkCbDWBPg0dS46XFYhNKGHbmXKUhUioTvoEebJ+0gJ7muRcmHQghVWa1Bai+aiTVFWiMFs9LSENTcOWkJIeSNH+1vq2rqCUIRkpMjGbwtIVuSDcaHw5h9QIA0o10bjL6MNO4sqcUjqaTnmuMRgdJWvwJ5NfMUvjIQy3HnFEUmE9UcJpMJKkrphKf3HOZf/f4jp/uWWdLxssce7v6guz98Oi/m5cSfeMs13LRpbfhPuONFobYzU/SLQx3wWsfz0FwJ2hniSFZPldysyNUoNCqpVaNaT+mUSTcXiKC2AUawf4I2J1OEMfuuZnKqAv0wYNXwGtbfRTUYPumN0RhCklv6zZ3YxBCDSX7cSiKVkjVHldrUz7OdDv/IGLV4roDVzLfQu5HxOj0//wV25nH1415mvDTAmBiRJk29SVMm8GUEUcJ6jypI/A5CoijIEYFE59m7WZqTh4q2hVaIEY4K2w+cXzIfJ5qQTlia353W4ycTJ/RaEflLInKXiNz1/PPPn/AX74ryN7/7Zn7wjZtjiwPFJE5DtRqe0HrTo4Ecu4nFDZJtpKoiNYxZ6lChtnlYPr2BkG1M4gCMbZi1yQA2LhRXtzQaHRJiyjldJl9IMMr0F5DXRM7xjCaPobz+6ov4Hz50G99926VJyctq45Xm1yh5TeO36QS/tDeGYYG+9lmRe/oaSnbNvMdrhT5axfFy6oDZQB3i42GOM0SrbqELVAdnGHoW+mH8+RhTucm2XRJSH55VNhJZXRBrpPw8d6cLX25z4RZ7rOdTnGhCvt3d3wC8H/hrIvLOk3iPE3qtu3/Y3e909zsvvvjkBW+/69ZLeccNF0c72IehZ0Dwhbmm4IYn7S0pXdLoabHnuNAPkRClICrp39H4msEmMZHcmYwkKBIrHS7RElsaigoSfM1SxoqGCkWF5ZPCFReu4k3XXcSqZRMsJfhDt6YNyp1OlNs2reEn33EtGy9YwQ+9cTM/fudVgVaaxxqXD5FsQ/BxRYyrLlwR1nRFkLkO7QpzpWRVLnRFYgSiGj4jpcSYZZGEh5T4twCAFIrS5WqYSv5bp5S5cLhyie/dLdytrCn0DYbbwMLCkOAW4Bo7myqoOuqGloY0R4KGxi0cOjrPvVv2nfT9cK7GCaGsiy3NReQjhKX5iZwdT+m1Jxvfe/vl3L9tHzsPWo4FGL3k46mcblWe2xI2/TxRoUub3RiT5ElUDPdQmYPGV83JpSi176lemXg3jjagi5FBDtARwQdn7cqO9958GW+8ej0XrV7G0YWBv7/la7k6lVW2De9RLr1wOd//+iuZ66aJcuVFK0dVtzIpjB6OCGhh47oV/L3vey1/9PguvvbMPu7ZuifXucA7icIqAl0qmRMPnOwXFkWCOpoPCA/wKfRxGiYrY4us+f7tevIHltRDZ64LrVutwY+1anjpgqtbNI8OcQIGqB7qA6gyP5w/VfJbVsgXszQ/kS9+Kq99ObFu5Rx/53tvZfNFq+k0W1cRlpXC2uUTqsSNbwhDHVgYekiAJmZ0sZI1Aa7beAEfeN0mLlu7Mpk4gZwiysIwYIm0Sqd00lQGSsD+ibRKwvlu8IarN/A/feh2vvu2y7hodUD5n314J0f6msmr4WU4xPLyRSs7fuxNm9l80eoXfI+fvP9ZQsw5W0PVHGkQiKsHWPK26y/mg3dcHt4bTay5UQRHckMDUXVsJcfwhG9SgEtLjDeCsJfjnyZZO8I8JONJGjYWY5eck5T8GWlJ6UqNEZCIgA1p+Z7AmzXToqbmfn7EqVia/zHgnwEXA78tIve4+/cstjR/sdeeiW+kxdoVE/6H77uN37xnC/uPDnQq3HjpGl676UIe3LaXX/rc4xwbhnAINkbGTMDzOSfUwo9921VceeFKvuuWjXz0a9v5zMPPcayvKVch4/oQCaB0gXYEOISkC1QALapwxUUrWTn3wh/3mhUdNlhUVnFKKUlGEP7st1/PjZeGkeihYz2//fVtbLpwFbuPDMno8UhEDClBo1szmfBdt07Naa5cv4rL1q1g694jkWAWrbOlpKUnbU5Sl9UX7UM2il/1NNjxICgMTggnw2gZUGnKADm71PhlB7UOwNOKoI1l4rxYkugeniMlSQu5QA70Q88Fywqvv/LC032bLNk4FUvzjwAfOc7HR0vzF3vtKxEfuuPKb/rY6666iDu37+cPH34ezy36ajVHHNGGmQuXXrCcKy8Mz/m5UvihN23mXa+5hH/8Ww9wZH6IFlNBatyQYf9tQNiJK06tEhKIAChXXbj6m67nzqs38NjzR3jH9Ru4aNUyHnh2P199eg/L5jquWL9i/LyjfeWzD+9kSMFlw1NCJLiig8GauQl/7Ttv4OoN0/fZc3ieXQePjWiqS0NK0/gmZychNJD7VBnqUwR2uogcLl3tfR0btz4C5M61MA+wJlbCPMY/mvpzGpAV4tHCuga1zo0uN5slRZVVOi5fv+oF89FXe5zzTB2AIwsDdz25m08+uIND85W1Kyd84LbLufOab/YI/BNvvppOhGWTwh8+uotDx+YToImbQ9x56/UbgNhk/8qTe3jLtet5582X8lfefQP/7vNPsv/IseBy5mxw9fIJB44ujGfB4JSGbEeJIQQP7djH7ZvXveBa5jrlT7/16vHvb71uA2+9bsM3XfPFa5bzJ992LU/tOsjaFctQFY71A6uWdXzk7m2sngg/9Z4bX5CMAB+5eyvzvWNW6YchF5clW8mUkZSS51d7gR3d4HFus1oxKxQJTZxqFZP4e4yOBkop4bY1roJBUogwE8wrXS4wS9IEG0LdGD+WZAJyjlwNOoFjtbLvyALrVp4fa1nnbEIenh/4+H3b+fKTe5mvA4eOBRkahINH5/nwZx7hiecvw51RYvCp3YdY6I2f+LZrAHj9lev5Z598kCN9ODrdevkFHOl7vuPGDVRz7t2yn8N14FMPPsehhYG/8M4b+H/98OvYsf8oT+w8xL3b93P7FWvZdOFKPnHfdr74+B7MKwWjkm5YophIehdeyI2Xrn1Z3++LJeuD2w5w7SWruObiFybjkYWB+7btwXzANVBV0ea0FT+pkuR6TZmekbsLaU0nwUTKBw+ptlC6AG8mCgu901enSI5i8FBj1w6TYAu5GVZKLoaHVIpV8nxKvE+j+KXVXkkwbsfeYzy16zB3bJ4l5JKNJ3Ye5F99+jH2HjqGdCUAFJS+H8KDsYCifOrB5+gUntlzlKsuWsWtmy5g+WSKJV53yWr++/fehGrhiguXp3tUtF4PbN/PsX6Ic6A6Dzx7kIPHetYsn3Dp2hVcunYFb7h6PR+/fztfeXIXd16zgd0HFtiy/xglW7iFvmfwkAE5Viv/6a4t/L0PvryEfLH4777rpuN+fOVcx59/5w388089QuiqC5NUQNAmiJdzWLdsJRd1ho2Wx4jERsuavW+2+zGXRVrS5j6kxBZHtK3xerMauKwZLk51w2vJ0cdUoqQlvSV5tyvC5etWfOO396qNczIhv/jUHvYf65PVEk9brwPaCVY9eaPxW50fjEd3HuSx5w/x+w/t4L23XMp1l6wZv9Y1l1zwgq/92HMH+bUvPsWWfUfAmjqdcPDIPH/vN76GiPCWa9azZddBdhw8xuG+UlC27J3nf/mh218gx/9PP/YQD+7cByidFl5pWuZtm9bxPbddxice2IFRw2LPASTbyjgDusrISW2hCJbKBlicsEvS7FxqAkrxb5rGO7jhmtIlwuiPqR66PCNHmNwsSSeuRj7AAwrykamkzNfK3U/v4f2vvfyV/eGdpTgnE/L1m9fx6QefG9d8SqfhxUFA+ZZMEJOmTRpVz1z4na9v5YFt+3JEANdcsoa3XnsRGy5Yxn/56la+8tQejswHmqriSY0rDBhH5nsKzqcf2YHVRCgpWBH2HlngC4/v4m03TAWa/ty7ruPrW/eybe8RrrtkDXde/cr73v/AG67k8ecP8dCz+yjJbY0q1NY5NECaxUayJABknhPGSE5tyHFsQEeVLBorbLSEbv8bFbPJlQSLKdrgwWLHsv1uVGN1KyqsUxT6OtBRuHjtCr7t2m9u1V+tcU4m5Ka1K1imzpEai7uN2hYc1Irmt6XENkdvddTLUS08tesQnXZ4gS17jvDpR55lZTfh6BDon4QsTNyvg4MM+DCgkzmaMoZ2ZFIGcWDDmjluvuyF7egFKya844azr6D2jhsv4ZHt+2NxG2jjh9jmSBkObwoDEZIqB6KxPRO+P8lbJcgVbbujio883oayRoWLRLcUnc7ijKZ6ugRdKgXxcs1L4s0mdKxbuZy//b23svY8MuU55xJyqMb//vGHOFrjyRrL/TYSpJVuFOnFhT7FiaV003OQKqaWO3ygFI4sDCO87hbnv7muS41RgdLFTVgERpqr4x5UtL/4rutZv3pp7u5JDv0dWDlXOHp0wBgYakVLF2MaGEnnMBV31q6gg1BFcA81hdJ1iJZsU2N00mQ4QkdWcGmWCVEto3ISTCgkqIhJXrccjXRtEbs6125Yw09/8NZX/Gd1tuOcS0gRYdKldosLWjzXe2L9V1VDnrHGPl5RZUgJDM8zVNH06OhizEHkLkM1StLIgsearBMRSu7rFesCQhLHTJgU4YffeAVXX/TNc8alEtddvIYfesOVzJvwfXds4u6n9/BrX3yafYePxjncQ8GuLEZZVbFuQtcFByfOlEEIly6IAoPFSGVO04bOm+ZOB1g6Ug/BJmrKCMRxgmaTnvPLUV7EjaLCO246f9rUxfGy16/OVhQVNq1bBSSEPg71Uxem7ylA13W86zWXcfXFa1g+6VBNq4A8KonGkNsF6jBQhz7QPg09US0pSRF073SC0kTmQ6aiuHP9xjVL3izmotXL+O7br+D77tgEwBuvWh/50Va4CPK4l+ntYBpar3Ndx7dffwnL57qkvglSA7jpUCaU2PDQEoR0idehHdopOlEGj51PN4NaGSyoh0N6Xyopr0IcFzZesIK3XnvyCwavhjjnKiTAj7xxM194fHdURAtpjaEGo+Q1V1zIj7/5ajoVVswV1iyfsH3fUZ7dd5Rf+eJTHDrax7nG+nGnT0sBCQFfLTJ2WSaOWKFqtGFBKo/0X9Yp33XrJj7wuk1n+8dx0vHIjgPsP9KnK3oQuNV8kd9jPKmv37iW77ztMl5/5YW86ZqL+IXPPMqRozVMYH2qKFDU8FS2kpR2RBr1PNzBoIzizcXyZ+7hQlY9gLM2h/y/vfv6UIA/D+OcTMiVyzu+/YYNfPaR5xnqMHIqC8EF/ca51eXrVnD5uhXcevlaHtqxnx17j3L303t4ZvdhmvmMFonWl7BKa9v5oQvluMciMFQuWbeSP/+uG7hmw6pX/ps/DeEE4NSVOcTiSDxXlO+57VL+xZ98M1f/9G/zpqvW82e//TpKnqtvvuwC/uI7r+fnP/EQbWApbX7oqbiTCdqOBs2KQfNh1rY/RUpIYRIJHPICSpkI33XbpVyy9vyZO35jnJMJKSL8xFuvYcPqZXzknm2xiGsOxXlu39EXfd3yucIdm9fDZnjf6zbx8Xu38xt3PxM2aqShjUalJU1pAsiAIoYWuGXTOv7s268/p6lcN116Af/wB25n+aQw1JA3mSyqSE/97AeO+7pbLl8bO5ZO6rA2/bo4n+s4P0y1AEmlvvA7QKSpujfHzKikhlBKbNj84Bs2n/kfwBKOczIhIZLyfbdvYtP6VSxUY1mnTFRZuezEtTwttwDbsrE0GZBYc4+BN/CBO6/iwpVzdApvuWbDq4Ls3BhL3Um2hqkymWipj0hpqnmEzk6XKu2eyK2Mg5Z06xJGa3Sies6Vwh9/4zcvBJxvcc4mZIvXXrHuZb92WdFIyhHtExb6BeZKB0VYs3wZ33/HFbzzprM/S1wqccHyjoNHF0ZxaavpfDUCZJXihZrqDEFCJ1xEqoYEp+Z5PLtcdaHrmvzz+R3nfEKeStx42TpuuXw/tToXrVpGb8ZdT+7ipsvX85rL1/D6Ky/ksvOIR3ki8XM/+ga++MRuPvPw8zy9+yALPkAq76mDdEAJNQIhGDeqXejQSsw3S545w7MyEvbmjRd807bK+RjndUJeceFK/uZ3v2b8+74jC9xx1YW8+ZrzcwZ2ovGWay/iLddexDO7D/O/f/R+FjL5ml6OIHSEZXqxkKP0pNV1JVUOxDEfYKggysFjC+PX/427tvDwcwf4/tdfwa2Xn14y/lKP8zohvzHWrZybJeNJxOaLVvGhOzez7/ACh49VVq+I0cUfPvo8h/o8CiAoNXwqaXYIKTVCrFiJCtv2HOOBbfv4159/jP1HFrhuw9oXWBucLzFLyFmcUrz3OKSIx547yOFdh+gmhWGc3Erq9ICrhXclIbcjKhwdKv/fTz0SWx9amJsTLj0Pjwvn5/R1Fmc03njNRXzXbZfz//zQa4NV5TEW8diCRqqmh2XsYgUBqDl6wcpOGTzIF+dbzCrkLE57vPeWqJrPH5ynrzUt4oMIMNWrtiZLh1tQElfPddy++WK+59bLuHTt8rP3DZzFmCXkLM5I7D40z8997D52HTjKMg2+sYkzDJWudEgJBzBSRGui8IHbL+c9t2z8ll/71RyzhJzFGYlD8wPmSle62PpIYkAX0qy4D5DbISu75fzMB25h47qVZ/uyz3rMEnIWZyS+/ORulk+UQ06IODupVcu4C4k7l6xdzg+98apZMmbMEnIWZyT2Hl5g5/4j4W2ZHFZqyIAEe1V43x2X8/13XJHSHrOAGco6izMQ/9cXn+L5g2kj56FOB043CeMepXDpuhV88PZNs2T8hpgl5CxOe9y3bT/P7Dky6vZMOuXKC1fxk00UWowfedPmkya2nw9xQj+RU7Q0f5+IPCwij4nIT5+uC5/F0oxPPvgsOw8cwW1gsPCeHBZ6vu26i3jjNRdz62VrWbdyGVeuPzd3Sc90nMwZ8t3uvmvR35ul+S+82AskPLX/OfBdwFbgyyLym+7+wMu52Fks/bj1snV8ft0qnt13lJJUHBc4dHQAQtjZzF6gXzuLaZxpS/M3A4+5+xPuvgD8GvD9L/c9Z7H047J1K+gtHL+aaQ4ifPSBZ3lw+36AWTK+RJxpS/NNwJZFf9+aH/umeLmW5rNYWvFHjz/PnsMLVJsuMIsIxeCZ3UfYtvcIW/YcPtuXuWTjRFvWt7v7dhG5BPhdEXnI3U/EBfl4ENpxt1Dd/cPAhwHuvPPO2abqORhf37qXj3xlK+FZOdXKEQwT5cEdB/hvX9+O4KxeNsGBay9ZzV9+1/Vn+9KXTJxQhVxsS054Qr75BL/+VmCxLsMVwPaTucBZnDvxq3/0FAeO9iF2bKmhrKkD4M5D2/dRMRbM2Xd0gb2Hj3HZecpZfbE4o5bmwJeBG0TkGhGZA34M+M2Xe7GzWNpx82VruWHDSswrUitmPbWveDXMBqoZXlNMLPSpuew8Vpg7XpxIhdwIfF5EvgZ8CfjtZmkuIluBtxKW5h8HEJHLReSjAO4+AD8FfBx4EPh1d7//THwjszj78W3XXcRTe48hFChhRKQaYtZoCUU6N9wHrPaYGfdt3cuXHp9hBi3Efekd1+68806/6667zvZlzOIk459+8iEe2rYvlQEkqHIlxavSnEdRRJw6GKWEtwoOV164kls3XcgfOw+U50Tkbnc/7ux+hj/P4rTE//SbX+eRZw/gEgrm6o6rk9Y6eDXCtyj3IIuEFYSH/cDWvUfZdOGMYD5LyFmccnx96z52HVxgqKGj0ywJFMVccZHwDSkFKLinXZaGFKQDHcKbr33l/TOXWsy2PWbxsmO+H/j1Lz3FXU/tZ6gWchx4JKFVpKQZrEVhdKx5o4eAcg1LdXHoxbhny17uuPLCs/1tndWYJeQsXnb87n3P8vnHd8WYw43BDFHFzcLZmnRJFjA3ikwQCz+x8PjxsCAQxV1eYGdwvsYsIWfxsqMCmKZ3JnSlwyysIAvNDTks/bxKcFhx3IyBSrFAYNeumePQQn/eabAeL2YJOYuXHSsnHUg4pOBQ3JEiI8rqGoa4qoSBbjokS4GJAaq87fpL+NNvu5q+r9/y/c6HmPUIs3jZ8Y4bL2H1smWjoQ5dCWlHJCUfayrLgUogrxL/HGisCI8/tx8RYW5uVhtglpCzOIVYMVf46Q+8hm+/+ZKQ5jBPy4BUJx9KWPqJpqtOjDkAug5wZ+N5KIb8UjFLyFmcUly8ZjlvuXbD6JYc2lWeolYBr4YfZESzrlszN+HOay7iL77zhrN05UszZgk5i1OO6y5ejYZ4DjZUBKe3gTpUrHdqOl/hYSpQzdl3tOfB7fv5zMPPne3LX1IxS8hZnHJ86oEd9O64KpsuWs1PvfdmLlqxglIKdEopMQpxM6wOWA1pjwNH5nl058GzfflLKmYn6VmccpQivPc1l7N6+YRrL17FzZet5U+941oefi6S7S3XXMQn7n+Wx587xOYNq7j5sjXcs2U/4Nxx5fqze/FLLGbk8lnM4hWOGbl8FrM4R2KWkLOYxRKKWULOYhZLKGYJOYtZLKGYJeQsZrGEYpaQs5jFEopZQs5iFksoZgk5i1ksoZgl5CxmsYRiSTJ1ROR54OmzfR2LYgOw61t+1tKI2bWeuThd13uVu198vH9Ykgm51EJE7noxqtNSi9m1nrl4Ja531rLOYhZLKGYJOYtZLKGYJeSJxYfP9gWcRMyu9czFGb/e2RlyFrNYQjGrkLOYxRKKWULOYhZLKGYJ+S1CRIqIfFVEfutsX8u3ChF5SkTuFZF7RGRJSy6IyDoR+U8i8pCIPCgibz3b13S8EJGb8ufZ/jsgIn/jTL3fTFPnW8d/T5jNXnC2L+QE493ufi4M238e+Ji7/3C6ay9JLzp3fxi4A+LhDGwDPnKm3m9WIV8iROQK4APAL53ta3k1hYhcALwT+GUAd19w931n9aJOLL4TeNzdzxiLbJaQLx3/FPg7gH2Lz1sq4cAnRORuEflLZ/tiXiKuBZ4H/k0eB35JRFad7Ys6gfgx4P88k28wS8gXCRH5ILDT3e8+29dyEvF2d38D8H7gr4nIO8/2Bb1IdMAbgH/p7q8HDgM/fXYv6aUj2+oPAf/xTL7PLCFfPN4OfEhEngJ+DXiPiPwfZ/eSXjrcfXv+707inPPms3tFLxpbga3u/sX8+38iEnQpx/uBr7j7GZVanyXki4S7/4y7X+HuVxOtyu+5+588y5f1oiEiq0RkTfsz8N3AfWf3qo4f7r4D2CIiN+WHvhN44Cxe0onEj3OG21WYoayvptgIfEREIH6vv+ruHzu7l/SS8deBX8lW8AngJ8/y9bxoiMhK4LuAv3zG32tGnZvFLJZOzFrWWcxiCcUsIWcxiyUUs4ScxSyWUMwSchazWEIxS8hZzGIJxSwhZzGLJRSzhJzFLJZQ/P8Bao1faOfdhEgAAAAASUVORK5CYII=",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"nl_map_cbs = gpd.read_file(r'../data/shape/Netherlands_shapefile/CBS_vk500_2020_v1.shp')\n",
"nl_map_cbs.to_crs(epsg=4326).plot()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Het verwerken van de 500m bij 500m vierkanten kaar duurde heel lang (langer dan een half uur) op de laptop, en is dus niet ideaal tenzij we dit niveau van detail écht nodig hebben. Er is namelijk nog een andere kaart met dezelfde gegevens beschikbaar, maar met een grid van 500 bij 500 meter in plaats van 100 bij 100. Laten we dus kijken hoe vaak een stemlokaal dichterbij dan 100 meter van de dichtstbijzijnde andere is. De makkelijkste manier om dat te doen zonder alle punten met alle andere te vergelijken (heel veel moeite), is een extra dataframe maken als een kopie, alle indexen 1 opschuiven (want alle stemlokalen zijn al in een volgorde van clustering), en dan de laagste afstand bekijken."
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"11165 0.002608\n",
"1021 0.004853\n",
"3196 0.004875\n",
"1923 2.693202\n",
"3757 3.609362\n",
" ... \n",
"7444 253385.654588\n",
"9711 263408.187856\n",
"4392 266925.200994\n",
"9297 271954.076837\n",
"0 NaN\n",
"Name: distance, Length: 11670, dtype: float64\n"
]
}
],
"source": [
"df_shifted = df_geojson_clean.to_crs('EPSG:28992')\n",
"\n",
"df_shifted['geometry (shifted)'] = df_shifted['geometry'].shift(periods=1)\n",
"df_shifted['distance'] = df_shifted['geometry'].distance(df_shifted['geometry (shifted)'])\n",
"df_shifted.sort_values(['distance'], inplace=True, ascending=True)\n",
"zero_mask_booth = df_shifted['distance'] == 0.000000\n",
"df_shifted = df_shifted[~zero_mask_booth]\n",
"print(df_shifted['distance'])"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We kunnen dus vaststellen dat afstanden van onder de 500 meter waarschijnlijk zeldzaam zijn, en we verder kunnen gaan met de 500 meter bij 500 meter kaart. Laten we nu dus een projectie proberen te maken met de bevolkingsdichtheid erop om het te vergelijken met de stemlokalen en hun posities en clustering."
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"['c28992r500', 'INWONER', 'MAN', 'VROUW', 'INW_014', 'INW_1524', 'INW_2544', 'INW_4564', 'INW_65PL', 'P_NL_ACHTG', 'P_WE_MIG_A', 'P_NW_MIG_A', 'AANTAL_HH', 'TOTHH_EENP', 'TOTHH_MPZK', 'HH_EENOUD', 'HH_TWEEOUD', 'GEM_HH_GR', 'WONING', 'WONVOOR45', 'WON_4564', 'WON_6574', 'WON_7584', 'WON_8594', 'WON_9504', 'WON_0514', 'WON_1524', 'WON_MRGEZ', 'P_KOOPWON', 'P_HUURWON', 'WON_HCORP', 'WON_NBEW', 'WOZWONING', 'UITKMINAOW', 'OAD', 'STED', 'geometry']\n"
]
},
{
"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>c28992r500</th>\n",
" <th>INWONER</th>\n",
" <th>geometry</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>267</th>\n",
" <td>E2050N6110</td>\n",
" <td>5</td>\n",
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" <tr>\n",
" <th>269</th>\n",
" <td>E2060N6110</td>\n",
" <td>15</td>\n",
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" <td>E2055N6105</td>\n",
" <td>20</td>\n",
" <td>POLYGON ((205500.000 611000.000, 206000.000 61...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>293</th>\n",
" <td>E2060N6105</td>\n",
" <td>185</td>\n",
" <td>POLYGON ((206000.000 611000.000, 206500.000 61...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>294</th>\n",
" <td>E2065N6105</td>\n",
" <td>340</td>\n",
" <td>POLYGON ((206500.000 611000.000, 207000.000 61...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>151071</th>\n",
" <td>E1970N3075</td>\n",
" <td>10</td>\n",
" <td>POLYGON ((197000.000 308000.000, 197500.000 30...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>151073</th>\n",
" <td>E1980N3075</td>\n",
" <td>90</td>\n",
" <td>POLYGON ((198000.000 308000.000, 198500.000 30...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>151074</th>\n",
" <td>E1985N3075</td>\n",
" <td>15</td>\n",
" <td>POLYGON ((198500.000 308000.000, 199000.000 30...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>151100</th>\n",
" <td>E1980N3070</td>\n",
" <td>5</td>\n",
" <td>POLYGON ((198000.000 307500.000, 198500.000 30...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>151106</th>\n",
" <td>E1920N3065</td>\n",
" <td>20</td>\n",
" <td>POLYGON ((192000.000 307000.000, 192500.000 30...</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>70656 rows × 3 columns</p>\n",
"</div>"
],
"text/plain": [
" c28992r500 INWONER geometry\n",
"267 E2050N6110 5 POLYGON ((205000.000 611500.000, 205500.000 61...\n",
"269 E2060N6110 15 POLYGON ((206000.000 611500.000, 206500.000 61...\n",
"292 E2055N6105 20 POLYGON ((205500.000 611000.000, 206000.000 61...\n",
"293 E2060N6105 185 POLYGON ((206000.000 611000.000, 206500.000 61...\n",
"294 E2065N6105 340 POLYGON ((206500.000 611000.000, 207000.000 61...\n",
"... ... ... ...\n",
"151071 E1970N3075 10 POLYGON ((197000.000 308000.000, 197500.000 30...\n",
"151073 E1980N3075 90 POLYGON ((198000.000 308000.000, 198500.000 30...\n",
"151074 E1985N3075 15 POLYGON ((198500.000 308000.000, 199000.000 30...\n",
"151100 E1980N3070 5 POLYGON ((198000.000 307500.000, 198500.000 30...\n",
"151106 E1920N3065 20 POLYGON ((192000.000 307000.000, 192500.000 30...\n",
"\n",
"[70656 rows x 3 columns]"
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"print(list(nl_map_cbs))\n",
"nl_map_dst = nl_map_cbs.drop(columns=['MAN', 'VROUW', 'INW_014', 'INW_1524', 'INW_2544', 'INW_4564', 'INW_65PL', 'P_NL_ACHTG', 'P_WE_MIG_A', 'P_NW_MIG_A', 'AANTAL_HH', 'TOTHH_EENP', 'TOTHH_MPZK', 'HH_EENOUD', 'HH_TWEEOUD', 'GEM_HH_GR', 'WONING', 'WONVOOR45', 'WON_4564', 'WON_6574', 'WON_7584', 'WON_8594', 'WON_9504', 'WON_0514', 'WON_1524', 'WON_MRGEZ', 'P_KOOPWON', 'P_HUURWON', 'WON_HCORP', 'WON_NBEW', 'WOZWONING', 'UITKMINAOW', 'OAD', 'STED'])\n",
"zero_mask_pop = nl_map_dst['INWONER'] == -99997\n",
"nl_map_dst = nl_map_dst[~zero_mask_pop]\n",
"nl_map_dst"
]
},
{
"cell_type": "code",
"execution_count": 47,
"metadata": {},
"outputs": [],
"source": [
"import folium\n",
"from folium import plugins\n",
"\n",
"map = folium.Map(location = [52.155, 5.3875], zoom_start = 9, tiles=\"cartodbdark_matter\", prefer_canvas=True)\n",
"\n",
"nl_map_dst.to_crs(epsg=4326)\n",
"#Make sure the index is a string so folium can read it correctly as a key.\n",
"nl_map_dst['c28992r500'] = nl_map_dst['c28992r500'].apply(lambda x: str(x))\n",
"\n",
"folium.Choropleth(\n",
" geo_data = nl_map_dst,\n",
" name=\"Bevolkingsdichtheid\",\n",
" data = nl_map_dst,\n",
" columns = [\"c28992r500\", \"INWONER\"],\n",
" key_on = 'feature.properties.c28992r500',\n",
" fill_color = 'RdPu',\n",
" nan_fill_color= 'white',\n",
" fill_opacity = 0.7,\n",
" nan_fill_opacity = 0.7,\n",
" line_opacity = 0,\n",
" legend_name = 'Bevolkingsdichtheid',\n",
" smooth_factor = 1.0,\n",
" show=False\n",
").add_to(map)\n",
"\n",
"# Renders the map to an HTML file and displays it in an embed.\n",
"def embed_map(m):\n",
" #from IPython.display import IFrame\n",
" m.save('index.html')\n",
" #return IFrame('index.html', width='100%', height='750px')"
]
},
{
"cell_type": "code",
"execution_count": 48,
"metadata": {},
"outputs": [],
"source": [
"df_geojson_clean_hmp = [[point.xy[1][0], point.xy[0][0]] for point in df_geojson_clean.geometry]\n",
"\n",
"plugins.HeatMap(df_geojson_clean_hmp, name=\"Stemlokalen Heatmap\").add_to(map)\n",
"\n",
"folium.LayerControl().add_to(map)\n",
"\n",
"\n",
"\n",
"embed_map(map)\n",
"\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 11,
"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>c28992r500</th>\n",
" <th>INWONER</th>\n",
" <th>geometry</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>267</th>\n",
" <td>E2050N6110</td>\n",
" <td>5</td>\n",
" <td>POINT (205250.000 611250.000)</td>\n",
" </tr>\n",
" <tr>\n",
" <th>269</th>\n",
" <td>E2060N6110</td>\n",
" <td>15</td>\n",
" <td>POINT (206250.000 611250.000)</td>\n",
" </tr>\n",
" <tr>\n",
" <th>292</th>\n",
" <td>E2055N6105</td>\n",
" <td>20</td>\n",
" <td>POINT (205750.000 610750.000)</td>\n",
" </tr>\n",
" <tr>\n",
" <th>293</th>\n",
" <td>E2060N6105</td>\n",
" <td>185</td>\n",
" <td>POINT (206250.000 610750.000)</td>\n",
" </tr>\n",
" <tr>\n",
" <th>294</th>\n",
" <td>E2065N6105</td>\n",
" <td>340</td>\n",
" <td>POINT (206750.000 610750.000)</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" c28992r500 INWONER geometry\n",
"267 E2050N6110 5 POINT (205250.000 611250.000)\n",
"269 E2060N6110 15 POINT (206250.000 611250.000)\n",
"292 E2055N6105 20 POINT (205750.000 610750.000)\n",
"293 E2060N6105 185 POINT (206250.000 610750.000)\n",
"294 E2065N6105 340 POINT (206750.000 610750.000)"
]
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"nl_map_dst_points = nl_map_dst\n",
"nl_map_dst_points['geometry'] = nl_map_dst_points['geometry'].centroid\n",
"nl_map_dst_points.head()"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {
"scrolled": false
},
"outputs": [
{
"data": {
"text/plain": [
"<AxesSubplot:ylabel='Frequency'>"
]
},
"execution_count": 17,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAAA24AAANZCAYAAAB3Lm1yAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjUuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/YYfK9AAAACXBIWXMAAAsTAAALEwEAmpwYAAAicElEQVR4nO3dfbCmd13f8c+XLEjCQ6lmsTQBF2wMUkZIWCia1kqQNhiF2ooNI9YylPQBKbS2Ghim2j86E2daHpwiNTwozwjhoZQUEBREOxDYABaSwEBDgAU0y5MBZAiBb/84d+AkObs52ZzrnO+efb1mzux9X+c+1/XdyW92897ruq+7ujsAAADMdbudHgAAAIAjE24AAADDCTcAAIDhhBsAAMBwwg0AAGA44QYAADDcuHCrqhdV1TVV9eFNvv7nq+qKqrq8ql6x9HwAAADbraZ9jltV/XiSryZ5SXff/xZee1qSVyc5u7u/VFV37+5rtmNOAACA7TLujFt3vyvJF9dvq6ofrKq3VNVlVfUnVXXf1beemOS53f2l1c+KNgAAYNcZF26HcVGSJ3f3g5L8hyS/vdr+Q0l+qKr+T1W9p6rO2bEJAQAAFrJnpwe4JVV15yQ/luQ1VXXD5u9Z/bonyWlJfiLJqUn+pKru391f3uYxAQAAFjM+3LJ2VvDL3f3ADb53MMl7uvubST5RVR/NWsi9bxvnAwAAWNT4SyW7+9qsRdljkqTWPGD17Tckedhq+8lZu3Tyqp2YEwAAYCnjwq2qXpnk3UlOr6qDVfWEJL+Q5AlV9WdJLk/y6NXL35rkC1V1RZJ3JPmP3f2FnZgbAABgKeM+DgAAAIAbG3fGDQAAgBsbdXOSk08+ufft27fTYwAAAOyIyy677PPdvfem20eF2759+3LgwIGdHgMAAGBHVNUnN9ruUkkAAIDhhBsAAMBwwg0AAGA44QYAADCccAMAABhOuAEAAAwn3AAAAIYTbgAAAMMtFm5VdXpVfXDd17VV9dSljgcAALBb7Vlqx9390SQPTJKqOiHJZ5K8fqnjAQAA7Fbbdankw5P8v+7+5DYdDwAAYNfYrnA7L8krN/pGVZ1fVQeq6sChQ4e2aRwAAIBjx+LhVlV3SPKoJK/Z6PvdfVF37+/u/Xv37l16HAAAgGPOdpxxe2SS93f3X2zDsQAAAHad7Qi3x+Ywl0kCAABwyxYNt6o6KckjkrxuyeMAAADsZot9HECSdPdfJfm+JY8BAACw223XXSUBAAA4SsINAABgOOEGAAAwnHADAAAYTrgBAAAMJ9wAAACGE24AAADDCTcAAIDhhBsAAMBwwg0AAGA44QYAADCccAMAABhOuAEAAAwn3AAAAIYTbgAAAMMJNwAAgOGEGwAAwHDCDQAAYDjhBgAAMJxwAwAAGG7PTg9wLNh3wSVbtq+rLzx3y/YFAAAcH5xxAwAAGE64AQAADCfcAAAAhhNuAAAAwwk3AACA4YQbAADAcMINAABgOOEGAAAwnHADAAAYTrgBAAAMJ9wAAACGE24AAADDCTcAAIDhhBsAAMBwwg0AAGA44QYAADCccAMAABhOuAEAAAwn3AAAAIbbs9MDHG/2XXDJlu3r6gvP3bJ9AQAAcznjBgAAMJxwAwAAGE64AQAADCfcAAAAhhNuAAAAwwk3AACA4YQbAADAcMINAABgOOEGAAAwnHADAAAYTrgBAAAMJ9wAAACGE24AAADDCTcAAIDhhBsAAMBwwg0AAGA44QYAADCccAMAABhOuAEAAAwn3AAAAIYTbgAAAMMJNwAAgOGEGwAAwHDCDQAAYDjhBgAAMJxwAwAAGE64AQAADCfcAAAAhhNuAAAAwwk3AACA4YQbAADAcMINAABgOOEGAAAwnHADAAAYTrgBAAAMJ9wAAACGE24AAADDCTcAAIDhhBsAAMBwwg0AAGA44QYAADCccAMAABhOuAEAAAwn3AAAAIYTbgAAAMMJNwAAgOGEGwAAwHDCDQAAYDjhBgAAMJxwAwAAGE64AQAADCfcAAAAhhNuAAAAwwk3AACA4YQbAADAcMINAABgOOEGAAAwnHADAAAYTrgBAAAMJ9wAAACGE24AAADDCTcAAIDhhBsAAMBwwg0AAGA44QYAADDcouFWVXerqour6iNVdWVV/eiSxwMAANiN9iy8/+ckeUt3/1xV3SHJSQsfDwAAYNdZLNyq6q5JfjzJP0+S7r4uyXVLHQ8AAGC3WvJSyfskOZTkd6vqA1X1gqq6001fVFXnV9WBqjpw6NChBccBAAA4Ni0ZbnuSnJnked19RpKvJbngpi/q7ou6e39379+7d++C4wAAAByblgy3g0kOdvelq+cXZy3kAAAAuBUWC7fu/vMkn66q01ebHp7kiqWOBwAAsFstfVfJJyd5+eqOklclefzCxwMAANh1Fg237v5gkv1LHgMAAGC3W/QDuAEAALjthBsAAMBwwg0AAGA44QYAADCccAMAABhOuAEAAAwn3AAAAIYTbgAAAMMJNwAAgOGEGwAAwHDCDQAAYDjhBgAAMJxwAwAAGE64AQAADCfcAAAAhhNuAAAAwwk3AACA4YQbAADAcMINAABgOOEGAAAwnHADAAAYTrgBAAAMJ9wAAACGE24AAADDCTcAAIDhhBsAAMBwwg0AAGA44QYAADCccAMAABhOuAEAAAwn3AAAAIYTbgAAAMMJNwAAgOGEGwAAwHDCDQAAYDjhBgAAMJxwAwAAGE64AQAADCfcAAAAhhNuAAAAwwk3AACA4YQbAADAcMINAABgOOEGAAAwnHADAAAYTrgBAAAMJ9wAAACGE24AAADDCTcAAIDhhBsAAMBwwg0AAGA44QYAADCccAMAABhOuAEAAAwn3AAAAIYTbgAAAMMJNwAAgOGEGwAAwHDCDQAAYDjhBgAAMJxwAwAAGE64AQAADCfcAAAAhhNuAAAAwwk3AACA4YQbAADAcMINAABgOOEGAAAwnHADAAAYTrgBAAAMJ9wAAACGE24AAADDCTcAAIDhhBsAAMBwwg0AAGA44QYAADCccAMAABhOuAEAAAwn3AAAAIYTbgAAAMMJNwAAgOGEGwAAwHDCDQAAYDjhBgAAMJxwAwAAGE64AQAADCfcAAAAhhNuAAAAwwk3AACA4YQbAADAcMINAABgOOEGAAAwnHADAAAYTrgBAAAMJ9wAAACGE24AAADDCTcAAIDhhBsAAMBwwg0AAGA44QYAADCccAMAABhOuAEAAAwn3AAAAIYTbgAAAMMJNwAAgOH2LLnzqro6yVeSfCvJ9d29f8njAQAA7EaLhtvKw7r789twHAAAgF3JpZIAAADDLR1uneQPquqyqjp/4WMBAADsSktfKnlWd3+2qu6e5G1V9ZHuftf6F6yC7vwkude97rXwOAAAAMeeRc+4dfdnV79ek+T1SR6ywWsu6u793b1/7969S44DAABwTFos3KrqTlV1lxseJ/kHST681PEAAAB2qyUvlfz+JK+vqhuO84rufsuCxwMAANiVFgu37r4qyQOW2j8AAMDxwscBAAAADCfcAAAAhhNuAAAAwwk3AACA4YQbAADAcMINAABgOOEGAAAwnHADAAAYTrgBAAAMJ9wAAACGE24AAADDCTcAAIDhhBsAAMBwwg0AAGA44QYAADCccAMAABhOuAEAAAwn3AAAAIYTbgAAAMMJNwAAgOGEGwAAwHDCDQAAYDjhBgAAMJxwAwAAGE64AQAADCfcAAAAhhNuAAAAwwk3AACA4YQbAADAcMINAABgOOEGAAAwnHADAAAYTrgBAAAMJ9wAAACGE24AAADDCTcAAIDhhBsAAMBwwg0AAGA44QYAADCccAMAABhOuAEAAAwn3AAAAIYTbgAAAMMJNwAAgOGEGwAAwHDCDQAAYDjhBgAAMJxwAwAAGE64AQAADCfcAAAAhhNuAAAAwwk3AACA4YQbAADAcMINAABgOOEGAAAwnHADAAAYTrgBAAAMJ9wAAACGE24AAADDCTcAAIDhhBsAAMBwwg0AAGA44QYAADCccAMAABhOuAEAAAwn3AAAAIYTbgAAAMMJNwAAgOGEGwAAwHDCDQAAYDjhBgAAMJxwAwAAGE64AQAADCfcAAAAhhNuAAAAwwk3AACA4YQbAADAcMINAABgOOEGAAAwnHADAAAYTrgBAAAMJ9wAAACGE24AAADDCTcAAIDhhBsAAMBwwg0AAGA44QYAADCccAMAABhOuAEAAAwn3AAAAIYTbgAAAMMJNwAAgOGEGwAAwHDCDQAAYDjhBgAAMJxwAwAAGE64AQAADCfcAAAAhhNuAAAAwwk3AACA4YQbAADAcMINAABgOOEGAAAwnHADAAAYTrgBAAAMJ9wAAACGWzzcquqEqvpAVb1p6WMBAADsRttxxu0pSa7chuMAAADsSouGW1WdmuTcJC9Y8jgAAAC72dJn3J6d5FeTfPtwL6iq86vqQFUdOHTo0MLjAAAAHHsWC7eq+ukk13T3ZUd6XXdf1N37u3v/3r17lxoHAADgmLXkGbezkjyqqq5O8qokZ1fVyxY8HgAAwK60WLh199O6+9Tu3pfkvCR/1N2PW+p4AAAAu5XPcQMAABhuz3YcpLvfmeSd23EsAACA3cYZNwAAgOGEGwAAwHDCDQAAYDjhBgAAMJxwAwAAGE64AQAADCfcAAAAhhNuAAAAwwk3AACA4YQbAADAcMINAABgOOEGAAAwnHADAAAYTrgBAAAMJ9wAAACGE24AAADDCTcAAIDhhBsAAMBwwg0AAGA44QYAADCccAMAABhOuAEAAAy3qXCrqvsvPQgAAAAb2+wZt/9RVe+tqn9TVXdbciAAAABubFPh1t1/N8kvJLlnkgNV9YqqesSikwEAAJDkVrzHrbs/luQZSX4tyd9P8ltV9ZGq+sdLDQcAAMDm3+P2I1X1rCRXJjk7yc909w+vHj9rwfkAAACOe3s2+br/nuT5SZ7e3V+/YWN3f7aqnrHIZAAAACTZfLj9VJKvd/e3kqSqbpfkjt39V9390sWmAwAAYNPvcXt7khPXPT9ptQ0AAICFbTbc7tjdX73hyerxScuMBAAAwHqbDbevVdWZNzypqgcl+foRXg8AAMAW2ex73J6a5DVV9dnV83sk+aeLTAQAAMCNbCrcuvt9VXXfJKcnqSQf6e5vLjoZAAAASTZ/xi1JHpxk3+pnzqiqdPdLFpkKAACA79hUuFXVS5P8YJIPJvnWanMnEW4AAAAL2+wZt/1J7tfdveQwAAAA3Nxm7yr54SR/Y8lBAAAA2Nhmz7idnOSKqnpvkm/csLG7H7XIVAAAAHzHZsPtN5YcAgAAgMPb7McB/HFV/UCS07r77VV1UpITlh0NAACAZJPvcauqJya5OMnvrDadkuQNC80EAADAOpu9OcmTkpyV5Nok6e6PJbn7UkMBAADwXZsNt29093U3PKmqPVn7HDcAAAAWttlw++OqenqSE6vqEUlek+R/LTcWAAAAN9hsuF2Q5FCSDyX5l0n+d5JnLDUUAAAA37XZu0p+O8nzV18AAABso02FW1V9Ihu8p62777PlEwEAAHAjm/0A7v3rHt8xyWOSfO/WjwMAAMBNbeo9bt39hXVfn+nuZyc5e9nRAAAASDZ/qeSZ657eLmtn4O6yyEQAAADcyGYvlfxv6x5fn+TqJD+/5dMAAABwM5u9q+TDlh4EAACAjW32Usl/f6Tvd/czt2YcAAAAburW3FXywUneuHr+M0neleTTSwwFAADAd2023E5OcmZ3fyVJquo3krymu//FUoMBAACwZlMfB5DkXkmuW/f8uiT7tnwaAAAAbmazZ9xemuS9VfX6JJ3kZ5O8ZLGpAAAA+I7N3lXyv1TVm5P8vdWmx3f3B5YbCwAAgBts9lLJJDkpybXd/ZwkB6vq3gvNBAAAwDqbCreq+vUkv5bkaatNt0/ysqWGAgAA4Ls2e8btZ5M8KsnXkqS7P5vkLksNBQAAwHdtNtyu6+7O2o1JUlV3Wm4kAAAA1ttsuL26qn4nyd2q6olJ3p7k+cuNBQAAwA1u8a6SVVVJfj/JfZNcm+T0JP+pu9+28GwAAABkE+HW3V1Vb+juByURawAAANtss5dKvqeqHrzoJAAAAGxoUx/AneRhSf5VVV2dtTtLVtZOxv3IUoMBAACw5ojhVlX36u5PJXnkNs0DAADATdzSGbc3JDmzuz9ZVa/t7n+yDTMBAACwzi29x63WPb7PkoMAAACwsVsKtz7MYwAAALbJLV0q+YCqujZrZ95OXD1OvntzkrsuOh0AAABHDrfuPmG7BgEAAGBjm/0cNwAAAHaIcAMAABhOuAEAAAwn3AAAAIYTbgAAAMMJNwAAgOGEGwAAwHDCDQAAYDjhBgAAMJxwAwAAGE64AQAADCfcAAAAhhNuAAAAwwk3AACA4YQbAADAcMINAABgOOEGAAAwnHADAAAYTrgBAAAMJ9wAAACGE24AAADDCTcAAIDhhBsAAMBwwg0AAGA44QYAADCccAMAABhOuAEAAAwn3AAAAIYTbgAAAMMJNwAAgOGEGwAAwHDCDQAAYLjFwq2q7lhV762qP6uqy6vqPy91LAAAgN1sz4L7/kaSs7v7q1V1+yR/WlVv7u73LHhMAACAXWexcOvuTvLV1dPbr756qeMBAADsVou+x62qTqiqDya5JsnbuvvSDV5zflUdqKoDhw4dWnIcAACAY9Ki4dbd3+ruByY5NclDqur+G7zmou7e39379+7du+Q4AAAAx6Rtuatkd385yTuTnLMdxwMAANhNlryr5N6qutvq8YlJfjLJR5Y6HgAAwG615F0l75HkxVV1QtYC8dXd/aYFjwcAALArLXlXyf+b5Iyl9g8AAHC82Jb3uAEAAHD0hBsAAMBwwg0AAGA44QYAADCccAMAABhOuAEAAAwn3AAAAIYTbgAAAMMJNwAAgOGEGwAAwHDCDQAAYDjhBgAAMJxwAwAAGE64AQAADCfcAAAAhhNuAAAAwwk3AACA4YQbAADAcMINAABgOOEGAAAwnHADAAAYTrgBAAAMJ9wAAACGE24AAADDCTcAAIDhhBsAAMBwwg0AAGA44QYAADCccAMAABhOuAEAAAwn3AAAAIYTbgAAAMMJNwAAgOGEGwAAwHDCDQAAYDjhBgAAMJxwAwAAGE64AQAADCfcAAAAhhNuAAAAwwk3AACA4YQbAADAcMINAABgOOEGAAAwnHADAAAYTrgBAAAMJ9wAAACGE24AAADDCTcAAIDhhBsAAMBwwg0AAGA44QYAADCccAMAABhOuAEAAAwn3AAAAIYTbgAAAMMJNwAAgOGEGwAAwHDCDQAAYDjhBgAAMJxwAwAAGE64AQAADCfcAAAAhhNuAAAAwwk3AACA4YQbAADAcMINAABgOOEGAAAwnHADAAAYTrgBAAAMJ9wAAACGE24AAADDCTcAAIDhhBsAAMBwwg0AAGA44QYAADCccAMAABhOuAEAAAwn3AAAAIYTbgAAAMMJNwAAgOGEGwAAwHDCDQAAYDjhBgAAMJxwAwAAGE64AQAADCfcAAAAhhNuAAAAwwk3AACA4YQbAADAcMINAABgOOEGAAAwnHADAAAYTrgBAAAMJ9wAAACGE24AAADDCTcAAIDhhBsAAMBwwg0AAGA44QYAADCccAMAABhOuAEAAAy3Z6cH4Ojtu+CSLdvX1Reeu2X7AgAAtpYzbgAAAMMJNwAAgOEWC7equmdVvaOqrqyqy6vqKUsdCwAAYDdb8j1u1yf5le5+f1XdJcllVfW27r5iwWMCAADsOoudcevuz3X3+1ePv5LkyiSnLHU8AACA3Wpb3uNWVfuSnJHk0u04HgAAwG6yeLhV1Z2TvDbJU7v72g2+f35VHaiqA4cOHVp6HAAAgGPOouFWVbfPWrS9vLtft9Fruvui7t7f3fv37t275DgAAADHpCXvKllJXpjkyu5+5lLHAQAA2O2WPON2VpJfTHJ2VX1w9fVTCx4PAABgV1rs4wC6+0+T1FL7BwAAOF5sy10lAQAAOHrCDQAAYDjhBgAAMJxwAwAAGE64AQAADCfcAAAAhhNuAAAAwwk3AACA4YQbAADAcMINAABgOOEGAAAwnHADAAAYTrgBAAAMJ9wAAACGE24AAADDCTcAAIDhhBsAAMBwwg0AAGA44QYAADCccAMAABhOuAEAAAwn3AAAAIYTbgAAAMMJNwAAgOGEGwAAwHDCDQAAYDjhBgAAMJxwAwAAGE64AQAADCfcAAAAhhNuAAAAwwk3AACA4YQbAADAcMINAABgOOEGAAAwnHADAAAYTrgBAAAMJ9wAAACGE24AAADDCTcAAIDhhBsAAMBwwg0AAGA44QYAADCccAMAABhOuAEAAAwn3AAAAIYTbgAAAMMJNwAAgOGEGwAAwHDCDQAAYDjhBgAAMJxwAwAAGE64AQAADCfcAAAAhhNuAAAAwwk3AACA4YQbAADAcMINAABgOOEGAAAwnHADAAAYTrgBAAAMJ9wAAACGE24AAADDCTcAAIDhhBsAAMBwwg0AAGA44QYAADCccAMAABhOuAEAAAwn3AAAAIYTbgAAAMMJNwAAgOGEGwAAwHDCDQAAYDjhBgAAMJxwAwAAGE64AQAADCfcAAAAhhNuAAAAwwk3AACA4YQbAADAcMINAABgOOEGAAAwnHADAAAYTrgBAAAMJ9wAAACGE24AAADDCTcAAIDhhBsAAMBwwg0AAGA44QYAADCccAMAABhOuAEAAAwn3AAAAIYTbgAAAMMJNwAAgOGEGwAAwHDCDQAAYDjhBgAAMJxwAwAAGE64AQAADCfcAAAAhhNuAAAAwwk3AACA4YQbAADAcMINAABguMXCrapeVFXXVNWHlzoGAADA8WDJM26/l+ScBfcPAABwXFgs3Lr7XUm+uNT+AQAAjhc7/h63qjq/qg5U1YFDhw7t9DgAAADj7Hi4dfdF3b2/u/fv3bt3p8cBAAAYZ8fDDQAAgCMTbgAAAMMt+XEAr0zy7iSnV9XBqnrCUscCAADYzfYstePufuxS+wYAADieuFQSAABgOOEGAAAwnHADAAAYTrgBAAAMJ9wAAACGE24AAADDCTcAAIDhhBsAAMBwwg0AAGA44QYAADCccAMAABhOuAEAAAwn3AAAAIYTbgAAAMMJNwAAgOGEGwAAwHDCDQAAYDjhBgAAMJxwAwAAGE64AQAADCfcAAAAhhNuAAAAwwk3AACA4YQbAADAcMINAABgOOEGAAAwnHADAAAYTrgBAAAMJ9wAAACGE24AAADDCTcAAIDhhBsAAMBwwg0AAGA44QYAADCccAMAABhOuAEAAAy3Z6cHYIZ9F1yyZfu6+sJzt2xfAACAM24AAADjCTcAAIDhhBsAAMBwwg0AAGA44QYAADCccAMAABhOuAEAAAwn3AAAAIYTbgAAAMMJNwAAgOGEGwAAwHDCDQAAYDjhBgAAMJxwAwAAGE64AQAADCfcAAAAhhNuAAAAwwk3AACA4YQbAADAcMINAABgOOEGAAAwnHADAAAYTrgBAAAMJ9wAAACGE24AAADDCTcAAIDhhBsAAMBwwg0AAGA44QYAADCccAMAABhOuAEAAAwn3AAAAIYTbgAAAMMJNwAAgOGEGwAAwHDCDQAAYDjhBgAAMJxwAwAAGE64AQAADCfcAAAAhhNuAAAAwwk3AACA4fbs9ADsPvsuuGTL9nX1hedu2b4AAOBY5YwbAADAcMINAABgOOEGAAAwnHADAAAYTrgBAAAMJ9wAAACGE24AAADDCTcAAIDhhBsAAMBwe3Z6ADiSfRdcsmX7uvrCc7dsXwAAsJ2ccQMAABhOuAEAAAwn3AAAAIbzHjeOG94vBwDAscoZNwAAgOGEGwAAwHAulYSj4LJLAAC2kzNuAAAAwznjBjvM2TsAAG6JM24AAADDCTcAAIDhXCoJu4jLLgEAdifhBmxIBAIAzCHcgMWJQACA20a4AccUEQgAHI+EG3Dc2soInEqcAsDusGi4VdU5SZ6T5IQkL+juC5c8HgA3NjVOBSUA3DqLhVtVnZDkuUkekeRgkvdV1Ru7+4qljgnAsWHqJa/mAmCqJc+4PSTJx7v7qiSpqlcleXQS4QbAlpl6VtFcwC3xDyncGkuG2ylJPr3u+cEkf+emL6qq85Ocv3r61ar66IIzHY2Tk3x+p4dg17GuWIJ1xRKsK5ZgXSWp39zpCXaV3bSmfmCjjUuGW22wrW+2ofuiJBctOMdtUlUHunv/Ts/B7mJdsQTriiVYVyzBumKrHQ9r6nYL7vtgknuue35qks8ueDwAAIBdaclwe1+S06rq3lV1hyTnJXnjgscDAADYlRa7VLK7r6+qX07y1qx9HMCLuvvypY63oLGXcXJMs65YgnXFEqwrlmBdsdV2/Zqq7pu97QwAAIBBlrxUEgAAgC0g3AAAAIYTbkdQVedU1Uer6uNVdcFOz8NcVXXPqnpHVV1ZVZdX1VNW27+3qt5WVR9b/frX1/3M01Zr66NV9Q/XbX9QVX1o9b3fqqqNPlqD40hVnVBVH6iqN62eW1fcJlV1t6q6uKo+svpz60etK26Lqvp3q7//PlxVr6yqO1pTHI2qelFVXVNVH163bcvWUlV9T1X9/mr7pVW1b1t/g7eBcDuMqjohyXOTPDLJ/ZI8tqrut7NTMdj1SX6lu384yUOTPGm1Xi5I8ofdfVqSP1w9z+p75yX520nOSfLbqzWXJM/L2ofSn7b6Omc7fyOM9JQkV657bl1xWz0nyVu6+75JHpC19WVdcVSq6pQk/zbJ/u6+f9ZuSnderCmOzu/l5v/dt3ItPSHJl7r7byV5VpJj5mPQhdvhPSTJx7v7qu6+Lsmrkjx6h2diqO7+XHe/f/X4K1n7n6BTsrZmXrx62YuT/KPV40cneVV3f6O7P5Hk40keUlX3SHLX7n53r9056CXrfobjUFWdmuTcJC9Yt9m64qhV1V2T/HiSFyZJd1/X3V+OdcVtsyfJiVW1J8lJWfvsXmuKW62735XkizfZvJVraf2+Lk7y8GPlzK5wO7xTknx63fODq21wRKtT7mckuTTJ93f355K1uEty99XLDre+Tlk9vul2jl/PTvKrSb69bpt1xW1xnySHkvzu6hLcF1TVnWJdcZS6+zNJ/muSTyX5XJK/7O4/iDXF1tnKtfSdn+nu65P8ZZLvW2zyLSTcDm+j8vbZCRxRVd05yWuTPLW7rz3SSzfY1kfYznGoqn46yTXdfdlmf2SDbdYVN7UnyZlJntfdZyT5WlaXHR2GdcURrd5v9Ogk907yN5Pcqaoed6Qf2WCbNcXROJq1dMyuM+F2eAeT3HPd81OzdtofNlRVt89atL28u1+32vwXq9P1Wf16zWr74dbXwdXjm27n+HRWkkdV1dVZu1z77Kp6WawrbpuDSQ5296Wr5xdnLeSsK47WTyb5RHcf6u5vJnldkh+LNcXW2cq19J2fWV3a+9dy80szRxJuh/e+JKdV1b2r6g5Ze+PjG3d4JoZaXRv9wiRXdvcz133rjUl+afX4l5L8z3Xbz1vd2ejeWXvT7HtXp/+/UlUPXe3zn637GY4z3f207j61u/dl7c+gP+rux8W64jbo7j9P8umqOn216eFJroh1xdH7VJKHVtVJq7Xw8Ky919uaYqts5Vpav6+fy9rfrcfEGbc9Oz3AVN19fVX9cpK3Zu3uSC/q7st3eCzmOivJLyb5UFV9cLXt6UkuTPLqqnpC1v5ie0ySdPflVfXqrP3P0vVJntTd31r93L/O2h2VTkzy5tUXrGddcVs9OcnLV/8weVWSx2ftH3OtK2617r60qi5O8v6srZEPJLkoyZ1jTXErVdUrk/xEkpOr6mCSX8/W/r33wiQvraqPZ+1M23nb8NvaEnWMBCYAAMBxy6WSAAAAwwk3AACA4YQbAADAcMINAABgOOEGAAAwnHADAAAYTrgBAAAM9/8BoGTV14+RhV4AAAAASUVORK5CYII=",
"text/plain": [
"<Figure size 1080x1080 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"import numpy as np\n",
"\n",
"from scipy.spatial import cKDTree\n",
"from shapely.geometry import Point\n",
"\n",
"def ckdnearest(gdA, gdB):\n",
"\n",
" nA = np.array(list(gdA.geometry.apply(lambda x: (x.x, x.y))))\n",
" nB = np.array(list(gdB.geometry.apply(lambda x: (x.x, x.y))))\n",
" btree = cKDTree(nB)\n",
" dist, idx = btree.query(nA, k=1)\n",
" gdB_nearest = gdB.iloc[idx].drop(columns=\"geometry\").reset_index(drop=True)\n",
" gdf = pd.concat(\n",
" [\n",
" gdA.reset_index(drop=True),\n",
" gdB_nearest,\n",
" pd.Series(dist, name='dist')\n",
" ], \n",
" axis=1)\n",
"\n",
" return gdf\n",
"\n",
"#error bar is +- sqrt(250²*2)m ≈ +-353.553390593m\n",
"df_nearest = ckdnearest(nl_map_dst_points.to_crs(epsg=28992), df_geojson_clean.to_crs(epsg=28992))\n",
"\n",
"#ax = df_nearest.plot.bar(x='INWONER', y='dist')\n",
"df_nearest['dist'].plot(kind=\"hist\", bins=40, weights=df_nearest['INWONER'], figsize=(15,15))"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [
{
"ename": "SyntaxError",
"evalue": "invalid syntax (745234620.py, line 3)",
"output_type": "error",
"traceback": [
"\u001b[0;36m Input \u001b[0;32mIn [13]\u001b[0;36m\u001b[0m\n\u001b[0;31m dfwims.\u001b[0m\n\u001b[0m ^\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m invalid syntax\n"
]
}
],
"source": [
"df_wims = pd.read_csv(r'../data/wims.csv')\n",
"print(df_wims)\n",
"dfwims."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"#de eerste vijf rijen zijn meta-data en kunnen we gerust weghalen voor nu \n",
"df_gr_gr = pd.read_csv(r'../data/stemmen/01_Groningen/osv4-3_telling_gr2022_groningen.csv', skiprows=5, header=None, delimiter=';')\n",
"print(df_gr_gr)\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"De data is heel gecompliceerd, dus we moeten het bruikbaar maken in pandas. Met hoe de data eruit ziet in een CSV in libre office willen we een constructie maken van de verschillende onderdelen. We hebben de data van de stemlokalen apart al, die kunnen we dus negeren. We willen de data van de lijsten apart hebben. "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"TODO:mobiele stemlokalen eruit filteren die NIET 0,0 zijn\n",
"TODO:gooi dichtheid data van niet verkiezingsgemeente weg\n",
"TODO:datastandaard duitse verkiezingen stemlokaalafstand opzoeken"
]
}
],
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