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Summary

Description
English: Health expenditure by funciton of health care, 2018 (OECD Stat)
Date
Source Own work, Data from OECD. https://stats.oecd.org/Index.aspx?DataSetCode=SHA
Author Yuasan

Graph data

import matplotlib.pyplot as plt
import pandas as pd

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

fig, ax = plt.subplots(figsize=(16, 8))
ax.bar(df.index, df["Inpatient"] , color="#93CDDD", width=0.7, bottom=0)
ax.bar(df.index, df["Outpatient"], color="#957ccb", width=0.7, bottom=df["Inpatient"] )
ax.bar(df.index, df["Long-term care"], color="#E69717", width=0.7 , bottom=df["Inpatient"]+df["Outpatient"] )
ax.bar(df.index, df["Ancillary services"] , color="#D83227", width=0.7,  bottom=df["Inpatient"]+df["Outpatient"] + df["Long-term care"]  )
ax.bar(df.index, df["Medical goods"] , color="#3cb371", width=0.7, bottom=df["Inpatient"]+df["Outpatient"] + df["Long-term care"] + df["Ancillary services"] )
ax.bar(df.index, df["Preventive care"] , color="#D676AB", width=0.7, bottom=df["Inpatient"]+df["Outpatient"] + df["Long-term care"] + df["Ancillary services"] + df["Medical goods"] )
ax.bar(df.index, df["Administration"] , color="#a52a2a", width=0.7, bottom=df["Inpatient"]+df["Outpatient"] + df["Long-term care"] + df["Ancillary services"] + df["Medical goods"] + df["Preventive care"])
ax.bar(df.index, df["Others"] , color="#aaa", width=0.7, bottom=df["Inpatient"]+df["Outpatient"] + df["Long-term care"] + df["Ancillary services"] + df["Medical goods"] + df["Preventive care"] +  df["Administration"] )

ax.legend(df.columns, fontsize=12, ncol=5, loc='center' ,bbox_to_anchor=(0., -0.23, 1., .102) )
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=0.22, right=0.96, top=0.8)

plt.title("Health expenditure by function, 2018 (OECD Health)", fontsize=28)
plt.tick_params(labelsize=10, pad=4)
plt.xticks(df.index, rotation=40, size=9)

plt.ylim([0,16])
plt.ylabel("% of GDP", size=15)
plt.yticks(fontsize=13)
plt.grid(which='major',color='#cccccc',linestyle='-', axis="y")
plt.subplots_adjust(top =0.88)

plt.savefig("image.svg")
==Licensing==
I, the copyright holder of this work, hereby publish it under the following license:
Creative Commons CC-Zero 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.

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21 April 2014

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Date/TimeThumbnailDimensionsUserComment
current16:24, 18 August 2021Thumbnail for version as of 16:24, 18 August 20211,440 × 720 (132 KB)Yuasan2018 data
07:53, 21 April 2014Thumbnail for version as of 07:53, 21 April 2014753 × 495 (100 KB)YuasanUser created page with UploadWizard

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