04_cannabis_dispensary_locations.ipynb

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   "source": [
    "## Dispensary Location Data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Imports"
   ]
  },
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   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import geopandas\n",
    "import geopandas.tools\n",
    "from shapely.geometry import Point\n",
    "import pickle"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Open & Process Data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Data was downloaded from the SF Open Data website"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
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    "deletable": true,
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   "outputs": [],
   "source": [
    "dispensary_locations = pd.read_csv('Cannabis_GeocodeFinal.csv')\n",
    "dispensary_locations['lat_lng'] = dispensary_locations['the_geom'].apply(lambda x: x[x.find(\"(\")+1:x.find(\")\")])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "dispensary_locations = dispensary_locations[dispensary_locations['Location_T'] == 'Fixed']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "dispensary_locations = dispensary_locations[['Business_N','the_geom','lat_lng']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "dispensary_locations['lat'] = dispensary_locations['lat_lng'].apply(lambda x: float(x.split(' ')[0]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
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    "deletable": true,
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   },
   "outputs": [],
   "source": [
    "dispensary_locations['lng'] = dispensary_locations['lat_lng'].apply(lambda x: float(x.split(' ')[1]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
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   },
   "outputs": [],
   "source": [
    "dispensary_locations.drop(['Business_N','the_geom','lat_lng'], axis=1, inplace=True)\n",
    "dispensary_locations['geometry'] = dispensary_locations.apply(lambda row: Point(row['lat'], row['lng']), axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
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   },
   "outputs": [],
   "source": [
    "dispensary_locations.drop(['lat','lng'], axis=1, inplace=True)\n",
    "dispensary_locations = geopandas.GeoDataFrame(dispensary_locations, geometry='geometry')"
   ]
  },
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   "source": [
    "dispensary_locations.crs = {\"init\": \"epsg:4326\"}\n",
    "dispensary_locations"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Save Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
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   "outputs": [],
   "source": [
    "pickle.dump(dispensary_locations, open('dispensary_locations.pkl', 'wb'))"
   ]
  }
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