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

df = pd.read_csv("data.tsv", index_col=0 , sep = "\t")
df1 = df.drop('Total', axis=1)
df2 = df.T.loc['Total']

fig, ax = plt.subplots(figsize=(10, 5))
ax.bar(df.index, df["0-19"] , width=1.7)
ax.bar(df.index, df["20-64"], width=1.7, bottom=df["0-19"] )
ax.bar(df.index, df["65-74"] , width=1.7, bottom=df["0-19"] + df["20-64"] )
ax.bar(df.index, df["75+"] , width=1.7, bottom=df["0-19"] + df["20-64"]+ df["65-74"] )

ax2 = ax.twinx()
ax2.plot(df2, label="Total", color="#5c1a86")

ax.legend(df1.columns, fontsize=12, ncol=4, loc='upper right',  frameon=True, facecolor="#dddddd")
ax.set_ylim([0,150000])
ax2.set_ylim([0,150000])

plt.rcParams['font.family'] = 'sans-serif'
plt.rcParams['font.sans-serif'] = ['Noto Sans Display']
plt.subplots_adjust(left=0.09, bottom=0.12, right=0.98, top=0.91)

plt.title("Population Trends in Japan, by Age (IPSS Population statistics)", fontsize=15)
plt.tick_params(labelsize=10, pad=4)
ax.set_xlabel("Historic and Projected", size=10)
ax.set_ylabel("1000 Population", size=12)

plt.setp(ax.get_xticklabels(), fontsize=8, rotation=75)
plt.setp(ax.get_yticklabels(), fontsize=9 )
ax.xaxis.set_major_locator(ticker.MultipleLocator(5))
ax.yaxis.set_major_locator(ticker.MultipleLocator(20000))

ax2.set_yticklabels([])
ax2.set_yticks([])

ax.minorticks_on()
ax.set_axisbelow(True)
ax2.set_axisbelow(True)
ax.grid(True, which='major',color='#cccccc',linestyle='-', axis="y")
ax.grid(True, which='minor',color='#eeeeee',linestyle='--', axis="y")
ax2.grid(None,which='major')

plt.savefig("image.svg")