{ "cells": [ { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "# 計算・図示用のパッケージの読み込み\n", "\n", "import pandas as pd\n", "import matplotlib.pyplot as plt\n", "\n", "# 日本語の文字化け防止\n", "\n", "import matplotlib as mpl\n", "font = {\"family\":\"IPAexGothic\"}\n", "mpl.rc('font', **font)" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "# データの読み込み\n", "\n", "df = pd.read_csv(\n", " 'TED_1_MAR20181.csv', index_col=[3,1]).drop(\n", " columns=['REGION', 'COUNTRY', 'MEASURE', '2018']).loc[\n", " 'Per Capita Income growth']" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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1950195119521953195419551956195719581959...2008200920102011201220132014201520162017
ISO
DZANaN-12-15179216...1021112211
AGONaN222-46-384-1...10-100131-1-4-1
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2 rows × 68 columns

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" ], "text/plain": [ " 1950 1951 1952 1953 1954 1955 1956 1957 1958 1959 ... 2008 2009 2010 \\\n", "ISO ... \n", "DZA NaN -1 2 -1 5 1 7 9 2 16 ... 1 0 2 \n", "AGO NaN 2 2 2 -4 6 -3 8 4 -1 ... 10 -1 0 \n", "\n", " 2011 2012 2013 2014 2015 2016 2017 \n", "ISO \n", "DZA 1 1 1 2 2 1 1 \n", "AGO 0 1 3 1 -1 -4 -1 \n", "\n", "[2 rows x 68 columns]" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# データの最初の2行\n", "\n", "df.head(2)" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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1950195119521953195419551956195719581959...2008200920102011201220132014201520162017
ISO
CHN1NaN191011-9760-2-5...58128576334
CHN2NaNNaNNaN1325132187...109109887777
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2 rows × 68 columns

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" ], "text/plain": [ " 1950 1951 1952 1953 1954 1955 1956 1957 1958 1959 ... 2008 2009 2010 \\\n", "ISO ... \n", "CHN1 NaN 19 10 11 -9 7 6 0 -2 -5 ... 5 8 12 \n", "CHN2 NaN NaN NaN 13 2 5 13 2 18 7 ... 10 9 10 \n", "\n", " 2011 2012 2013 2014 2015 2016 2017 \n", "ISO \n", "CHN1 8 5 7 6 3 3 4 \n", "CHN2 9 8 8 7 7 7 7 \n", "\n", "[2 rows x 68 columns]" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# 中国のデータ\n", "# 'CHN1' はConference Boardが再計算\n", "# 'CHN2' は中国の公式データ\n", "\n", "df[df.index.str.contains('CHN')]" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [], "source": [ "#　'CHN1' を削除 \n", "\n", "df = df.drop('CHN1', axis=0)" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(123, 68)" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# データの行と列\n", "\n", "df.shape" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "Index: 123 entries, DZA to GBR\n", "Data columns (total 68 columns):\n", "1950 0 non-null object\n", "1951 100 non-null object\n", "1952 100 non-null object\n", "1953 101 non-null object\n", "1954 101 non-null object\n", "1955 101 non-null object\n", "1956 101 non-null object\n", "1957 101 non-null object\n", "1958 101 non-null object\n", "1959 101 non-null object\n", "1960 101 non-null object\n", "1961 102 non-null object\n", "1962 102 non-null object\n", "1963 102 non-null object\n", "1964 102 non-null object\n", "1965 102 non-null object\n", "1966 102 non-null object\n", "1967 102 non-null object\n", "1968 102 non-null object\n", "1969 102 non-null object\n", "1970 102 non-null object\n", "1971 103 non-null object\n", "1972 103 non-null object\n", "1973 103 non-null object\n", "1974 103 non-null object\n", "1975 103 non-null object\n", "1976 103 non-null object\n", "1977 103 non-null object\n", "1978 103 non-null object\n", "1979 103 non-null object\n", "1980 103 non-null object\n", "1981 121 non-null object\n", "1982 121 non-null object\n", "1983 121 non-null object\n", "1984 121 non-null object\n", "1985 121 non-null object\n", "1986 122 non-null object\n", "1987 122 non-null object\n", "1988 122 non-null object\n", "1989 122 non-null object\n", "1990 122 non-null object\n", "1991 123 non-null object\n", "1992 123 non-null object\n", "1993 123 non-null object\n", "1994 123 non-null object\n", "1995 123 non-null object\n", "1996 123 non-null object\n", "1997 123 non-null object\n", "1998 123 non-null object\n", "1999 123 non-null object\n", "2000 123 non-null object\n", "2001 123 non-null object\n", "2002 123 non-null object\n", "2003 123 non-null object\n", "2004 123 non-null object\n", "2005 123 non-null object\n", "2006 123 non-null object\n", "2007 123 non-null object\n", "2008 123 non-null object\n", "2009 123 non-null object\n", "2010 123 non-null object\n", "2011 123 non-null object\n", "2012 123 non-null object\n", "2013 123 non-null object\n", "2014 123 non-null object\n", "2015 123 non-null object\n", "2016 123 non-null object\n", "2017 123 non-null object\n", "dtypes: object(68)\n", "memory usage: 66.3+ KB\n" ] } ], "source": [ "# データのタイプと 'NaN' の確認\n", "\n", "df.info()" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [], "source": [ "# データを数値タイプに変換\n", "\n", "df = df.apply(pd.to_numeric)" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [], "source": [ "# それぞれの国の平均成長率を計算\n", "\n", "s_mean = df.mean(axis=1)" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "4.358208955223881" ] }, "execution_count": 10, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# 日本の平均成長率\n", "\n", "s_mean['JPN']" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "7.030769230769231" ] }, "execution_count": 11, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# 平均成長率の最大値\n", "\n", "s_mean.max()" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "-1.0149253731343284" ] }, "execution_count": 12, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# 平均成長率の最小値\n", "\n", "s_mean.min()" ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "8.04569460390356" ] }, "execution_count": 13, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# 最大値と最小値の差\n", "\n", "s_mean.max() - s_mean.min()" ] }, { "cell_type": "code", "execution_count": 22, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# ヒストグラムの作成・表示・保存\n", "\n", "plt.subplots(figsize=[10,6])\n", "plt.suptitle('図1：1人当たり実質GDP平均成長率（％; 124カ国, 1951〜2017年）', \\\n", " fontsize=20, horizontalalignment='left', y=1.0, x=0.08)\n", "plt.title(\"（データ出所：The Conference Board Total Economy Database, March 2018）\", \\\n", " fontsize=15, horizontalalignment='left', x=0.02)\n", "plt.ylabel(\"国の数\", fontsize=17)\n", "plt.hist(s_mean, bins=16, color=\"lightgreen\", edgecolor='black', linewidth=1.2)\n", "plt.savefig('histogram.pdf')" ] }, { "cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# ヒストグラムの作成・表示・保存（英語版）\n", "\n", "plt.subplots(figsize=[10,6])\n", "plt.suptitle('Figure 1： Average growth rate of GDP per capita (%; 124 countries, 1951〜2017)', \n", " fontsize=16, horizontalalignment='left', y=1.0, x=0.08)\n", "plt.title(\"Data: The Conference Board Total Economy Database, March 2018\", \\\n", " fontsize=15, horizontalalignment='left', x=0.09)\n", "plt.ylabel(\"No of Countries\", fontsize=17)\n", "plt.hist(s_mean, bins=16, color=\"lightgreen\", edgecolor='black', linewidth=1.2)\n", "plt.savefig('histogram_eng.pdf')" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "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": "3.6.6" }, "toc": { "base_numbering": 1, "nav_menu": {}, "number_sections": true, "sideBar": true, "skip_h1_title": false, "title_cell": "Table of Contents", "title_sidebar": "Contents", "toc_cell": false, "toc_position": {}, "toc_section_display": true, "toc_window_display": false } }, "nbformat": 4, "nbformat_minor": 2 }