6. Life expectancy by country.

import numpy as np import pandas as pd import matplotlib.pyplot as plt #1 data = pd.read_csv("country_data.csv") print(data.head())

               Country  Life Expectancy          GDP
0          Afghanistan         58.19375   340.015425
1              Albania         75.15625  2119.726679
2              Algeria         73.61875  2847.853392
3               Angola         49.01875  1975.143045
4  Antigua and Barbuda         75.05625  9759.305728

life_expectancy = data["Life Expectancy"]

#2-3 life_expectancy_quartiles = np.quantile(life_expectancy, [0.25, 0.5, 0.75]) print(life_expectancy_quartiles)

[62.325     72.525     75.4421875]

#4 plt.hist(life_expectancy) plt.show()

#5-6 dp = data["GDP"]

#7 median_gdp = np.quantile(gdp, 0.5) print(median_gdp)

2938.0781155

#8 low_gdp = data[data['GDP'] <= median_gdp] high_gdp = data[data['GDP'] > median_gdp]

#9 low_gdp_quartiles = np.quantile(low_gdp["Life Expectancy"], [0.25, 0.5, 0.75]) print(low_gdp_quartiles)

[56.3375  64.34375 71.7375 ]

#10 high_gdp_quartiles = np.quantile(high_gdp["Life Expectancy"], [0.25,0.5,0.75]) print(high_gdp_quartiles)

[72.965625 75.15625  80.521875]

#11 plt.hist(high_gdp["Life Expectancy"], alpha = 0.5, label = "High GDP") plt.hist(low_gdp["Life Expectancy"], alpha = 0.5, label = "Low GDP") plt.legend() plt.show()

#FINAL..