Street and Proximity to MRT (Credits leexa90).ipynb

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   "source": [
    "#CSV file taken from github user leexa90 on his amazing project of HDB resale price which found the lat/long of each street\n",
    "#using Google API and also promixity to MRT\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "locations = pd.read_csv('train_mrt.csv.gz')"
   ]
  },
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   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "locations = locations[['street_name','dist_nearestMRT']]"
   ]
  },
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   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
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       "       dist_nearestMRT\n",
       "count    748300.000000\n",
       "mean          0.795073\n",
       "std           0.407394\n",
       "min           0.034139\n",
       "25%           0.484982\n",
       "50%           0.735347\n",
       "75%           1.034326\n",
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   "source": [
    "locations.describe()"
   ]
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   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "locations.to_csv('street_to_MRT.csv')"
   ]
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