Faịlụ:Public and private health expenditure by country.svg

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Nkówá Health expenditure by type of financing, 2019 (OECD Health)
Ǹgụ́ụ̀bọ̀chị̀
Mkpọlọ́gwụ̀ Orü ọnwé, Data from OECD Health
https://stats.oecd.org/Index.aspx?DataSetCode=SHA#
Odé ákwụ́kwọ́ Yuasan
Ọdà
(Í jí kwá usòrò nke)
CC-0

Graph data

import matplotlib as mpl
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=["Government/compulsory schemes"], ascending=False)
df = df.drop('Government/compulsory schemes', axis=1)
df = df.fillna(0).T

mpl.rcParams['axes.xmargin'] = 0.02
plt.rcParams['axes.prop_cycle'] = cycler(color=['#93CDDD', '#957ccb', '#E69717', '#D83227', '#A3DF6E', '#d7352b', '#ffd924', '#a652c1', '#686d69'])

fig, ax = plt.subplots(figsize=(12, 6))
for i in range( len(df) ):
	ax.bar(df.columns, df.iloc[i] , width=0.7, bottom=df.iloc[:i].sum())

plt.rcParams['font.family'] = 'sans-serif'
plt.rcParams['font.sans-serif'] = ['Noto Sans Display']

plt.subplots_adjust(left=0.08, bottom=0.19, right=0.98, top=0.93)

plt.title("Health expenditure by type of financing, 2019 (OECD SOCX)", fontsize=18)
plt.tick_params(labelsize=10, pad=4)

ax.legend(df.index, fontsize=9,  loc='center', ncol=5,  frameon=True, facecolor="#dddddd",
			bbox_to_anchor=(0., -0.28, 1., .102) )
ax.set_axisbelow(True)

plt.xticks(df.columns, rotation=70, size=9)
plt.yticks(fontsize=13)
plt.ylabel("% of Health expenditure", size=13)
plt.ylim([0,100])

ax.minorticks_on()
plt.grid(which='major',color='#999999',linestyle='-', axis="y")
plt.grid(which='minor',color='#cccccc',linestyle='--', axis="y")

plt.savefig("image.svg")

Nkwényé

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depicts Bekee

Ụfọdụ uru na-enweghị ihe Wikidata

27 Jenụwarị 2014

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