philshem/swiss_housing_dataviz.ipynb

## swiss_housing_dataviz.ipynb
{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "swiss_housing_dataviz.ipynb",
      "provenance": [],
      "collapsed_sections": [],
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/gist/philshem/e95601c4d66269a3e57d06d34408fde4/swiss_housing_dataviz.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "KH6hbAORTgGc",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "# imports\n",
        "import pandas as pd"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "9f8Bo5zbVFE6",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "# load the csv as a pandas dataframe\n",
        "df = pd.read_csv('https://www.bfs.admin.ch/bfsstatic/dam/assets/10027475/appendix', encoding = \"ISO-8859-1\", sep= ';', skiprows = 2, skipfooter = 4, engine = 'python')"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "2sPihAsrerOq",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 130
        },
        "outputId": "24510b62-ad49-45ce-97c7-52df7f6254b4"
      },
      "source": [
        "# rename column with Cantons\n",
        "df.columns.values[0] = 'Kanton'\n",
        "print(df.columns)"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Index(['Kanton', 'Total', 'Swiss household, one person',\n",
            "       'Swiss household, two or more persons',\n",
            "       'Swiss-foreign household, two or more persons',\n",
            "       'Foreign household, one person',\n",
            "       'Foreign household, two or more persons'],\n",
            "      dtype='object')\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "DzFAmxRFXguq",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "# only use swiss totals, no individual cantons\n",
        "df = df[df.Kanton == 'CH']\n",
        "#print(df)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "YV12e2ZWd_M4",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 289
        },
        "outputId": "0d24471a-a528-4a15-81fa-da536d728a48"
      },
      "source": [
        "# plot CH results\n",
        "ax = df.plot(x = 'Kanton', y = ['Swiss household, one person',\n",
        "       'Foreign household, one person',\n",
        "       'Swiss household, two or more persons',\n",
        "       'Swiss-foreign household, two or more persons',\n",
        "       'Foreign household, two or more persons'], kind = 'bar')\n",
        "\n",
        "ax.set_ylabel('square meters, per person')\n",
        "ax.set_xlabel('')\n",
        "ax.legend(loc='best', bbox_to_anchor=(1, 0.5))"
      ],
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.legend.Legend at 0x7fe925ac14a8>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 7
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAo4AAAD9CAYAAAAyJ/amAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nrkJggg==\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    }
  ]
}