import matplotlib.pyplot as plt
from cycler import cycler
import pandas as pd
df = pd.read_csv("data.tsv", index_col=0 , sep = "\t").T
dfline = df.loc['Effective copayment rate'] # line
dfbar = df.loc['Medical cost per capita'] # bar
fig, ax = plt.subplots(figsize=(8, 5))
ax2 = ax.twinx()
plt.rcParams['font.family'] = 'sans-serif'
plt.rcParams['font.sans-serif'] = ['Noto Sans Display']
plt.subplots_adjust(left=0.09, bottom=0.15, right=0.92, top=0.88)
plt.setp(ax.get_xticklabels(), fontsize=9)
plt.setp(ax.get_yticklabels(), fontsize=9)
ax.set_xlabel("Population Age group", fontsize=10)
ax.bar(dfbar.index, dfbar, color="#FAAA69", width=0.6)
ax.set_axisbelow(True)
ax.tick_params(axis='x', labelrotation=35)
ax.set_ylim([0,1600])
ax.set_ylabel("Annual medical cost (Thousand JPY)", fontsize=10)
ax.legend(['Medical cost'] ,facecolor="#eeeeee", fontsize=11,loc='upper left' )
ax.minorticks_on()
ax.grid(which='major',color='#999999',linestyle='-', axis="y")
ax.grid(which='minor',color='#dddddd',linestyle='--', axis="y")
ax2.set_prop_cycle( plt.rcParams['axes.prop_cycle'] )
ax2.set_axisbelow(True)
ax2.plot(dfline)
ax2.set_ylim([0,40])
ax2.set_ylabel("Copayment Rate (Percentage)", fontsize=10)
ax2.legend(['Copayment Rate'] ,facecolor="#eeeeee" ,fontsize=11,loc='upper right' )
plt.title("Annual medical cost and copayment rate in Japan\n by age group, 2020 (OECD Economic Survey 2024)", fontsize=14)
plt.tick_params(labelsize=9, pad=4)
plt.yticks(fontsize=9)
plt.savefig("image.svg")