0_calcPLZareas.ipynb

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     "text": [
      "190\n"
     ]
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   "source": [
    "import geopandas as gpd\n",
    "from geopandas.geoseries import *\n",
    "import numpy as np\n",
    "\n",
    "# source: Amt für Statistik Berlin-Brandenburg: Postleitzahlen\n",
    "# https://fbinter.stadt-berlin.de/fb/index.jsp?loginkey=zoomStart&mapId=plz@senstadt&bbox=367109,5805216,418853,5832317\n",
    "plz = gpd.read_file('source/plz.geojson')\n",
    "print(len(plz)) # 190 PLZs\n",
    "\n",
    "plr = gpd.read_file('source/LOR_Planungsraeume_2019.geojson')\n",
    "\n",
    "plr_data = pd.read_csv('source/LOR_Planungsraeume_2019.csv', sep=';')\n",
    "plr_data.rename(columns={'Planungsraum': 'PLANUNGSRAUM', 'Bezirksregion': 'BEZIRKSREGION'}, inplace=True)\n",
    "\n",
    "plr = plr.merge(plr_data, on=['PLANUNGSRAUM', 'BEZIRKSREGION'])\n",
    "\n",
    "df = pd.DataFrame(columns = ['PLR', 'PLR_NAME', 'PLZ'])\n",
    "df['PLZ'] = np.empty((len(plr), 0)).tolist()\n",
    "\n",
    "# match Planungsraum with PLZ areas\n",
    "for indexPLR, rowPLR in plr.iterrows():\n",
    "    df.loc[indexPLR, 'PLR'] = rowPLR.Schlüssel\n",
    "    df.loc[indexPLR, 'PLR_NAME'] = rowPLR.PLANUNGSRAUM\n",
    "    for indexPLZ, rowPLZ in plz.iterrows():\n",
    "        if rowPLZ.geometry.intersects(rowPLR.geometry):\n",
    "            df.loc[indexPLR, 'PLZ'].append(str(rowPLZ.spatial_name))\n",
    "\n",
    "df.to_csv('output/PLR2PLZ.csv')\n",
    "\n",
    "\n",
    "\n",
    "df2 = pd.DataFrame(columns = ['PLZ', 'PLR'])\n",
    "df2['PLR'] = np.empty((len(plz), 0)).tolist()\n",
    "\n",
    "# match PLZ area with Planungsräume\n",
    "for indexPLZ, rowPLZ in plz.iterrows():\n",
    "    df2.loc[indexPLZ, 'PLZ'] = rowPLZ.spatial_name\n",
    "    for indexPLR, rowPLR in plr.iterrows():\n",
    "        if rowPLR.geometry.intersects(rowPLZ.geometry):\n",
    "            df2.loc[indexPLZ, 'PLR'].append(rowPLR.Schlüssel)\n",
    "\n",
    "df2.to_csv('output/PLZ2PLR.csv')"
   ]
  }
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