{ "cells": [ { "cell_type": "markdown", "metadata": { "colab_type": "text", "id": "MSKoKElq1kF4" }, "source": [ "# Matplotlib 入門\n", "\n", "グラフの描画を行う際は [Matplotlib](https://matplotlib.org/) が便利です。\n", "Colab では標準で Matplotlib を使ってプロットを行うと描画結果がノートブック上に表示されます。\n", "Matplotlib は `matplotlib.pyplot` を `plt` という別名をつけて読み込むのが一般的です。" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "colab": {}, "colab_type": "code", "id": "dehoAfTINPN-" }, "outputs": [], "source": [ "%matplotlib inline\n", "import matplotlib.pyplot as plt" ] }, { "cell_type": "markdown", "metadata": { "colab_type": "text", "id": "nD6RSWpgWBpz" }, "source": [ "この章で用いるデータセットは前章と同じように Colab で用意されているサンプルデータを使用します。\n", "Colab 以外で実行する場合は、[こちら](https://download.mlcc.google.com/mledu-datasets/california_housing_train.csv)からデータをダウンロードして、`sample_data` というディレクトリ以下に設置してください。\n", "\n", "まず、Pandas で CSV ファイルを読み込みます。" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "colab": {}, "colab_type": "code", "id": "jhsL4iKnjyGL" }, "outputs": [ { "data": { "text/html": [ "
\n", " | longitude | \n", "latitude | \n", "housing_median_age | \n", "total_rooms | \n", "total_bedrooms | \n", "population | \n", "households | \n", "median_income | \n", "median_house_value | \n", "
---|---|---|---|---|---|---|---|---|---|
0 | \n", "-114.31 | \n", "34.19 | \n", "15.0 | \n", "5612.0 | \n", "1283.0 | \n", "1015.0 | \n", "472.0 | \n", "1.4936 | \n", "66900.0 | \n", "
1 | \n", "-114.47 | \n", "34.40 | \n", "19.0 | \n", "7650.0 | \n", "1901.0 | \n", "1129.0 | \n", "463.0 | \n", "1.8200 | \n", "80100.0 | \n", "
2 | \n", "-114.56 | \n", "33.69 | \n", "17.0 | \n", "720.0 | \n", "174.0 | \n", "333.0 | \n", "117.0 | \n", "1.6509 | \n", "85700.0 | \n", "
3 | \n", "-114.57 | \n", "33.64 | \n", "14.0 | \n", "1501.0 | \n", "337.0 | \n", "515.0 | \n", "226.0 | \n", "3.1917 | \n", "73400.0 | \n", "
4 | \n", "-114.57 | \n", "33.57 | \n", "20.0 | \n", "1454.0 | \n", "326.0 | \n", "624.0 | \n", "262.0 | \n", "1.9250 | \n", "65500.0 | \n", "