application_vnd.jupyter.stderr_output_1.png
import matplotlib.pyplot as plt

import matplotlib.pyplot as plt

import seaborn as sns

import seaborn as sns
sns.set()

(sns.get_dataset_names(), len(sns.get_dataset_names()))

healthexp = sns.load_dataset('healthexp')
healthexp

top_spending_countrys = healthexp[['Country', 'Life_Expectancy']]
top_spending_countrys

Spending_USD_by_year = healthexp.groupby('Year')['Spending_USD'].sum()
Spending_USD_by_year

regional_Spending_and_Life_Expectancy = healthexp.groupby('Country')[['Year', 'Spending_USD', 'Life_Expectancy']].sum()
plt.figure(figsize=(10, 6))
sns.heatmap(data=regional_Spending_and_Life_Expectancy, cmap='YlGnBu', annot=True, fmt='.1f')
plt.title('regional_Spending_and_Life_Expectancy')
plt.xlabel('Features')
plt.ylabel('Country')
plt.show()