Health expenditure and life expectancy

Source: HealthExpenditure/healthexpenditure.Rmd

The graph emphasizes a descriptive comparison: the United States is an outlier in spending relative to life expectancy, while Mexico is highlighted as another reference country.

Code

from pathlib import Path
import pandas as pd
import matplotlib.pyplot as plt

root = Path("../../ROS-Examples")
health = pd.read_table(root / "HealthExpenditure/data/healthdata.txt", sep=r"\s+")
health.head()

	country	spending	lifespan
0	Australia	3357	81.4
1	Austria	3763	80.1
2	Belgium	3595	79.8
3	Canada	3895	80.7
4	Czech	1626	77.0

All countries

Code

colors = health.country.where(health.country.isin(["USA", "Mexico"]), other="other")
colors = colors.map({"USA": "red", "Mexico": "red", "other": "black"})
fig, ax = plt.subplots(figsize=(8, 6))
for _, r in health.iterrows():
    ax.text(r.spending, r.lifespan, r.country, color=colors.loc[r.name], fontsize=8)
ax.set_xlim(0, 1.05*health.spending.max())
ax.set_xlabel("Health care spending (PPP US$)")
ax.set_ylabel("Life expectancy (years)")

Text(0, 0.5, 'Life expectancy (years)')

Less cluttered display

Code

remove = health.country.isin(["Netherlands", "Belgium", "Germany", "Ireland", "Iceland", "Greece", "Italy", "Sweden", "UK"])
fig, ax = plt.subplots(figsize=(8, 6))
for _, r in health.loc[~remove].iterrows():
    col = "red" if r.country in ["USA", "Mexico"] else "black"
    ax.text(r.spending, r.lifespan, r.country, color=col, fontsize=9)
for x in [2000, 4000, 6000]:
    ax.axvline(x, color="lightgray", linewidth=.7)
for y in [74, 76, 78, 80, 82]:
    ax.axhline(y, color="lightgray", linewidth=.7)
ax.set_xlim(0, 1.05*health.spending.max())
ax.set_xlabel("Health care spending (PPP US$)")
ax.set_ylabel("Life expectancy (years)")

Text(0, 0.5, 'Life expectancy (years)')