{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# All of that stuff above is unnecccccessary\n",
    "## we just need to do this \\/"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import geocoder\n",
    "import json\n",
    "import gmplot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "dataset = pd.read_csv('Datasets/Brightkite.csv', index_col=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['UserID', 'Latitude', 'Longitude', 'PlaceID'], dtype='object')"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dataset.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([   0,    1,    2, ..., 2964, 2965, 2966], dtype=int64)"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dataset['UserID'].unique()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "key = 'AiEfap-qUoZalL1qK8ollM-SwVdoJFemh60tHo0EeraVYP8V4WPJXAVD2YjqzgA1'\n",
    "#geo = geocoder.bing([45.15,-75.14], method='reverse', key = key)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "dict_keys(['address', 'bbox', 'city', 'confidence', 'country', 'lat', 'lng', 'ok', 'postal', 'quality', 'raw', 'state', 'status', 'street'])\n"
     ]
    }
   ],
   "source": [
    "dic = geo.json\n",
    "print(dic.keys())\n",
    "test = gmplot.GoogleMapPlotter(30.3164945, \n",
    "                                78.03219179999999, 13)\n",
    "test.draw('testmap.html')"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}