import matplotlib.pyplot as plt import pandas as pd import numpy as np df = pd.read_csv("data.tsv", index_col=0 , sep = "\t") fig, ax = plt.subplots(figsize=(12, 5)) x = np.arange(df.index.size) ax.bar(x-0.1, df["2012"] , color="#F79646", width=0.5, bottom=0) ax.bar(x+0.3, df["2050"] , color="#C6A389", width=0.3, bottom=0) ax.legend(df.columns, fontsize=14, ncol=2, loc='upper right', frameon=True, facecolor="#dddddd") ax.set_axisbelow(True) plt.rcParams['font.family'] = 'sans-serif' plt.rcParams['font.sans-serif'] = ['Noto Sans Display'] plt.subplots_adjust(left=0.07, bottom=0.17, right=0.99, top=0.9) plt.title("Old-age support ratio (OECD Society at Glance 2014)", fontsize=20) plt.tick_params(labelsize=10, pad=4) plt.xticks(x, df.index, rotation=55, size=9) plt.ylabel("Number of working-age (20-64)\n per old-age (65+)", size=11) plt.yticks(fontsize=11) plt.ylim([0,9]) ax.minorticks_on() plt.grid(which='major',color='#999999',linestyle='-', axis="y") plt.grid(which='minor',color='#eeeeee',linestyle='--', axis="y") plt.savefig("image.svg")