Housing.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "Housing.ipynb",
      "version": "0.3.2",
      "provenance": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
  },
  "cells": [
    {
      "metadata": {
        "id": "qEWQ3ZVyrQsU",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "import os\n",
        "import tarfile\n",
        "from six.moves import urllib\n",
        "\n",
        "DOWNLOAD_ROOT = \"https://raw.githubusercontent.com/ageron/handson-ml/master/\"\n",
        "HOUSING_PATH = os.path.join(\"datasets\", \"housing\")\n",
        "HOUSING_URL = DOWNLOAD_ROOT + \"datasets/housing/housing.tgz\"\n",
        "\n",
        "def fetch_housing_data(housing_url=HOUSING_URL, housing_path=HOUSING_PATH):\n",
        "    if not os.path.isdir(housing_path):\n",
        "        os.makedirs(housing_path)\n",
        "    tgz_path = os.path.join(housing_path, \"housing.tgz\")\n",
        "    urllib.request.urlretrieve(housing_url, tgz_path)\n",
        "    housing_tgz = tarfile.open(tgz_path)\n",
        "    housing_tgz.extractall(path=housing_path)\n",
        "    housing_tgz.close()"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "nTVDBunKrwYB",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "import pandas as pd\n",
        "\n",
        "def load_housing_data(housing_path=HOUSING_PATH):\n",
        "    csv_path = os.path.join(housing_path, \"housing.csv\")\n",
        "    return pd.read_csv(csv_path)\n"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "bQTzPefpsFz9",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "bf8a4f1a-8f9e-49b7-f1bd-f3bb0d8fc270"
      },
      "cell_type": "code",
      "source": [
        "housing = load_housing_data()\n",
        "housing.head()\n",
        "housing.info()\n",
        "housing[\"ocean_proximity\"].value_counts()\n",
        "housing.describe()\n",
        "housing.hist()"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "error",
          "ename": "FileNotFoundError",
          "evalue": "ignored",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mFileNotFoundError\u001b[0m                         Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-3-9ba8f2435111>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mhousing\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mload_housing_data\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      2\u001b[0m \u001b[0mhousing\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mhead\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      3\u001b[0m \u001b[0mhousing\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0minfo\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      4\u001b[0m \u001b[0mhousing\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"ocean_proximity\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mvalue_counts\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      5\u001b[0m \u001b[0mhousing\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdescribe\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m<ipython-input-2-bff1dc1ab873>\u001b[0m in \u001b[0;36mload_housing_data\u001b[0;34m(housing_path)\u001b[0m\n\u001b[1;32m      3\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mload_housing_data\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mhousing_path\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mHOUSING_PATH\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      4\u001b[0m     \u001b[0mcsv_path\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mos\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpath\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mjoin\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mhousing_path\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m\"housing.csv\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 5\u001b[0;31m     \u001b[0;32mreturn\u001b[0m \u001b[0mpd\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mread_csv\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcsv_path\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
            "\u001b[0;32m/usr/local/lib/python3.6/dist-packages/pandas/io/parsers.py\u001b[0m in \u001b[0;36mparser_f\u001b[0;34m(filepath_or_buffer, sep, delimiter, header, names, index_col, usecols, squeeze, prefix, mangle_dupe_cols, dtype, engine, converters, true_values, false_values, skipinitialspace, skiprows, nrows, na_values, keep_default_na, na_filter, verbose, skip_blank_lines, parse_dates, infer_datetime_format, keep_date_col, date_parser, dayfirst, iterator, chunksize, compression, thousands, decimal, lineterminator, quotechar, quoting, escapechar, comment, encoding, dialect, tupleize_cols, error_bad_lines, warn_bad_lines, skipfooter, skip_footer, doublequote, delim_whitespace, as_recarray, compact_ints, use_unsigned, low_memory, buffer_lines, memory_map, float_precision)\u001b[0m\n\u001b[1;32m    707\u001b[0m                     skip_blank_lines=skip_blank_lines)\n\u001b[1;32m    708\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 709\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0m_read\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfilepath_or_buffer\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkwds\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    710\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    711\u001b[0m     \u001b[0mparser_f\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__name__\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.6/dist-packages/pandas/io/parsers.py\u001b[0m in \u001b[0;36m_read\u001b[0;34m(filepath_or_buffer, kwds)\u001b[0m\n\u001b[1;32m    447\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    448\u001b[0m     \u001b[0;31m# Create the parser.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 449\u001b[0;31m     \u001b[0mparser\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mTextFileReader\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfilepath_or_buffer\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwds\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    450\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    451\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0mchunksize\u001b[0m \u001b[0;32mor\u001b[0m \u001b[0miterator\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.6/dist-packages/pandas/io/parsers.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, f, engine, **kwds)\u001b[0m\n\u001b[1;32m    816\u001b[0m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0moptions\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'has_index_names'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mkwds\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'has_index_names'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    817\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 818\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_make_engine\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mengine\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    819\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    820\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mclose\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.6/dist-packages/pandas/io/parsers.py\u001b[0m in \u001b[0;36m_make_engine\u001b[0;34m(self, engine)\u001b[0m\n\u001b[1;32m   1047\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m_make_engine\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mengine\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'c'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1048\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mengine\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;34m'c'\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1049\u001b[0;31m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mCParserWrapper\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mf\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0moptions\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1050\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1051\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mengine\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;34m'python'\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.6/dist-packages/pandas/io/parsers.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, src, **kwds)\u001b[0m\n\u001b[1;32m   1693\u001b[0m         \u001b[0mkwds\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'allow_leading_cols'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mindex_col\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mFalse\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1694\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1695\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_reader\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mparsers\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mTextReader\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msrc\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwds\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1696\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1697\u001b[0m         \u001b[0;31m# XXX\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32mpandas/_libs/parsers.pyx\u001b[0m in \u001b[0;36mpandas._libs.parsers.TextReader.__cinit__\u001b[0;34m()\u001b[0m\n",
            "\u001b[0;32mpandas/_libs/parsers.pyx\u001b[0m in \u001b[0;36mpandas._libs.parsers.TextReader._setup_parser_source\u001b[0;34m()\u001b[0m\n",
            "\u001b[0;31mFileNotFoundError\u001b[0m: File b'datasets/housing/housing.csv' does not exist"
          ]
        }
      ]
    },
    {
      "metadata": {
        "id": "d9SGnv1HwBwf",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 878
        },
        "outputId": "66c2088c-586d-4697-86d0-a35c8005aa95"
      },
      "cell_type": "code",
      "source": [
        "%matplotlib inline   \n",
        "import matplotlib.pyplot as plt\n",
        "housing.hist(bins=50, figsize=(20,15))\n",
        "plt.show()"
      ],
      "execution_count": 26,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAABIwAAANdCAYAAAD2k+erAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
            "text/plain": [
              "<matplotlib.figure.Figure at 0x7f9beabc90b8>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    }
  ]
}