Day_20.ipynb

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   "source": [
    "import geopandas as gpd\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "ca66d465-c810-42c6-a211-f56d141ca5a5",
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   "source": [
    "df = gpd.read_file(r'data/A_Zipcodes2010wData.shp')\n",
    "bdf = pd.read_csv(r'data/newbusinesses.csv', parse_dates=[9])\n",
    "bdf['year'] = pd.DatetimeIndex(bdf.entityformdate).year\n",
    "bdf['month'] = pd.DatetimeIndex(bdf.entityformdate).month\n",
    "bdf['day'] = pd.DatetimeIndex(bdf.entityformdate).day"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "30e04113-8606-495f-a3a7-85da3a6de459",
   "metadata": {},
   "outputs": [],
   "source": [
    "merged = df.merge(bdf, left_on='ZIPCODE', right_on='principalzipcode')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "e81067ee-468a-4ced-931f-fdb25ecabdd4",
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   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "saving empty 2012_1\n",
      "saving empty 2012_2\n",
      "saving empty 2012_3\n",
      "saving empty 2012_4\n",
      "saving empty 2012_5\n",
      "saving empty 2012_6\n",
      "saving empty 2012_7\n",
      "saving empty 2012_8\n",
      "saving empty 2012_9\n",
      "saving empty 2012_10\n",
      "saving empty 2012_11\n",
      "saving results from 2012_12\n",
      "saving results from 2013_1\n",
      "saving results from 2013_2\n",
      "saving results from 2013_3\n",
      "saving results from 2013_4\n",
      "saving results from 2013_5\n",
      "saving results from 2013_6\n",
      "saving results from 2013_7\n",
      "saving results from 2013_8\n",
      "saving results from 2013_9\n",
      "saving results from 2013_10\n",
      "saving results from 2013_11\n",
      "saving results from 2013_12\n",
      "saving results from 2014_1\n",
      "saving results from 2014_2\n",
      "saving results from 2014_3\n",
      "saving results from 2014_4\n",
      "saving results from 2014_5\n",
      "saving results from 2014_6\n",
      "saving results from 2014_7\n",
      "saving results from 2014_8\n",
      "saving results from 2014_9\n",
      "saving results from 2014_10\n",
      "saving results from 2014_11\n",
      "saving results from 2014_12\n",
      "saving results from 2015_1\n",
      "saving results from 2015_2\n",
      "saving results from 2015_3\n",
      "saving results from 2015_4\n",
      "saving results from 2015_5\n",
      "saving results from 2015_6\n",
      "saving results from 2015_7\n",
      "saving results from 2015_8\n",
      "saving results from 2015_9\n",
      "saving results from 2015_10\n",
      "saving results from 2015_11\n",
      "saving results from 2015_12\n",
      "saving results from 2016_1\n",
      "saving results from 2016_2\n",
      "saving results from 2016_3\n",
      "saving results from 2016_4\n",
      "saving results from 2016_5\n",
      "saving results from 2016_6\n",
      "saving results from 2016_7\n",
      "saving results from 2016_8\n",
      "saving results from 2016_9\n",
      "saving results from 2016_10\n",
      "saving results from 2016_11\n",
      "saving results from 2016_12\n",
      "saving results from 2017_1\n",
      "saving results from 2017_2\n",
      "saving results from 2017_3\n",
      "saving results from 2017_4\n",
      "saving results from 2017_5\n",
      "saving results from 2017_6\n",
      "saving results from 2017_7\n",
      "saving results from 2017_8\n",
      "saving results from 2017_9\n",
      "saving results from 2017_10\n",
      "saving results from 2017_11\n",
      "saving results from 2017_12\n",
      "saving results from 2018_1\n",
      "saving results from 2018_2\n",
      "saving results from 2018_3\n",
      "saving results from 2018_4\n",
      "saving results from 2018_5\n",
      "saving results from 2018_6\n",
      "saving results from 2018_7\n",
      "saving results from 2018_8\n",
      "saving results from 2018_9\n",
      "saving results from 2018_10\n",
      "saving results from 2018_11\n",
      "saving results from 2018_12\n",
      "saving results from 2019_1\n",
      "saving results from 2019_2\n",
      "saving results from 2019_3\n",
      "saving results from 2019_4\n",
      "saving results from 2019_5\n",
      "saving results from 2019_6\n",
      "saving results from 2019_7\n",
      "saving results from 2019_8\n",
      "saving results from 2019_9\n",
      "saving results from 2019_10\n",
      "saving results from 2019_11\n",
      "saving results from 2019_12\n",
      "saving results from 2020_1\n",
      "saving results from 2020_2\n",
      "saving results from 2020_3\n",
      "saving results from 2020_4\n",
      "saving results from 2020_5\n",
      "saving results from 2020_6\n",
      "saving results from 2020_7\n",
      "saving results from 2020_8\n",
      "saving results from 2020_9\n",
      "saving results from 2020_10\n",
      "saving results from 2020_11\n",
      "saving results from 2020_12\n",
      "saving results from 2021_1\n",
      "saving results from 2021_2\n",
      "saving results from 2021_3\n",
      "saving results from 2021_4\n",
      "saving results from 2021_5\n",
      "saving results from 2021_6\n",
      "saving results from 2021_7\n",
      "saving results from 2021_8\n",
      "saving results from 2021_9\n",
      "saving results from 2021_10\n",
      "saving results from 2021_11\n",
      "saving empty 2021_12\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 1440x1440 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "region = [-109.5, -101.5, 36.75, 41.25]\n",
    "\n",
    "for year in range(2012,2022,1):\n",
    "    for month in range(1,13,1):\n",
    "        plt.close()\n",
    "    #print(merged[merged.entityformdate == single_date.strftime(\"%Y-%m-%d\")].year)\n",
    "        fig, ax = plt.subplots(1, figsize=(20,20))\n",
    "        ax.set_xlim(region[0], region[1])\n",
    "        ax.set_ylim(region[2], region[3])\n",
    "        ax.set_title(f'{year} {month}', fontsize=25)\n",
    "        df.plot(facecolor='None', edgecolor='lightgray', ax=ax)\n",
    "        subdf = merged[(merged.month==month)&(merged.year==year)].dissolve(by='ZIPCODE', aggfunc='count')\n",
    "        if subdf.empty:\n",
    "            print(f'saving empty {year}_{month}')\n",
    "            plt.savefig(f'data/results/{year}_{month}.png')\n",
    "            plt.clf()\n",
    "        else:\n",
    "            subdf.plot(column='NAME10', vmin=0, vmax=50, ax=ax, legend=True)\n",
    "            print(f'saving results from {year}_{month}')\n",
    "            plt.savefig(f'data/results/{year}_{month}.png')\n",
    "            plt.clf()\n",
    "    "
   ]
  },
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