OECD_Social_Expenditure_by_Braunch.svg
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Summary
Description OECD Social Expenditure by Braunch.svg | Social Expenditure as % of GDP by Braunch, (OECD 2019) |
Date | |
Source |
Own work
, Data from OECD SOCX
https://stats.oecd.org/Index.aspx?DataSetCode=SOCX_AGG |
Author | Yuasan |
Permission
( Reusing this file ) |
CC-0 |
Licensing
I, the copyright holder of this work, hereby publish it under the following license:
This file is made available under the Creative Commons CC0 1.0 Universal Public Domain Dedication . | |
The person who associated a work with this deed has dedicated the work to the
public domain
by waiving all of their rights to the work worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law. You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission.
http://creativecommons.org/publicdomain/zero/1.0/deed.en CC0 Creative Commons Zero, Public Domain Dedication false false |
Graph data
import numpy as np
from cycler import cycler
import matplotlib.pyplot as plt
import pandas as pd
df = pd.read_csv("data.tsv", index_col=0 , sep = "\t")
df = df.sort_values(by=["Total"], ascending=True).fillna(0)
df1 = df.drop('Total', axis=1).T
#plt.rcParams["axes.prop_cycle"] = plt.cycler("color", plt.get_cmap("tab20")(np.linspace(0,1,12)))
plt.rcParams['axes.prop_cycle'] = cycler(color=['#e5961d', '#4DAF4A', '#B15928', '#3b95d3', '#7FC97F', '#d7352b', '#ffd924', '#a652c1', '#686d69'])
fig, ax = plt.subplots(figsize=(14, 7))
for i in range( len(df1) ):
ax.bar(df1.columns, df1.iloc[i] , width=0.7, bottom=df1.iloc[:i].sum())
ax.legend(df.columns, fontsize=13, loc='upper left', ncol=2, 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=0.05, bottom=0.14, right=0.98, top=0.92)
plt.title("Social expenditure as % of GDP, by Branch (OECD,2019)", fontsize=25)
plt.tick_params(labelsize=10, pad=4)
plt.xticks(df.index, rotation=70, size=10)
plt.yticks(fontsize=13)
plt.ylabel("% of GDP", size=15)
ax.minorticks_on()
plt.grid(which='major',color='#999999',linestyle='-', axis="y")
plt.grid(which='minor',color='#e3e3e3',linestyle='--', axis="y")
plt.savefig("image.svg")