import matplotlib.pyplot as plt
from cycler import cycler
import pandas as pd
import matplotlib.ticker as ticker

df = pd.read_csv("data.tsv", index_col=0 , sep = "\t").T

fig, ax = plt.subplots(figsize=(10, 6))
ax2 = ax.twinx()
plt.rcParams['font.family'] = 'sans-serif'
plt.rcParams['font.sans-serif'] = ['Noto Sans']
plt.subplots_adjust(left=0.10, bottom=0.18, right=0.99, top=0.90)

ax.bar(df.index, df['Tax']* -1, color="#9467bd", label="Tax")
ax.bar(df.index, df['Social Insurance'] *-1 , color="#e377c2", bottom=df['Tax']*-1, label="Social Insurance")
ax.bar(df.index, df['Cash Benefits'], color="#2ca02c", label="Cash Benefits")
ax.bar(df.index, df['Service Benefits'], color="#98DF8A", label="Service Benefits", bottom=df['Cash Benefits'] ) 
ax.axhspan(-250,0, color="lightblue", alpha=0.4 , zorder=-10)	

ax.set_ylim([-250,800])
ax.set_axisbelow(True)
ax.set_xlabel("Householder Age", fontsize=12)
ax.set_ylabel("Income,Tax and Transfers (10,000 JPY)", fontsize=14)
ax.margins(0.05)

ax2.set_prop_cycle( plt.rcParams['axes.prop_cycle'] )
ax2.plot(df["Raw Income"], lw=3, label="Raw Income", ls="--")
ax2.plot(df["Redistributed Income"], lw=3, label="Redistributed Income")
ax2.set_ylim([-250,800])
ax2.set_yticklabels([])
ax2.set_yticks([])
ax2.margins(0.05)

lines, labels = ax.get_legend_handles_labels()
lines2, labels2 = ax2.get_legend_handles_labels()
fig.legend(lines + lines2, labels + labels2, facecolor="#eeeeee" ,
           ncol=6, fontsize=10,loc='lower center')

plt.title("Income redistribution in Japan by age \n(MHLW Income redistribution survey, 2023)", fontsize=15)
plt.tick_params(labelsize=9, pad=4)
plt.grid(which='major',color='#cccccc',linestyle='-', axis="y")
plt.setp(ax.get_xticklabels(), fontsize=11, rotation=30)
plt.setp(ax.get_yticklabels(), fontsize=10 )

ax.minorticks_on()
ax.yaxis.set_major_locator(ticker.MultipleLocator(100))
ax.grid(False, which='minor', axis="x")
ax.grid(True, which='major',color='#cccccc',linestyle='-', axis="y")
ax.grid(True, which='minor',color='#eeeeee',linestyle='--', axis="y")

plt.savefig("image.svg")