text_plain_output_1.png
import matplotlib.pyplot as plt

import matplotlib.pyplot as plt

import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)

import seaborn as sns

data2015 = pd.read_csv('../input/2015.csv')
data2016 = pd.read_csv('../input/2016.csv')
data2017 = pd.read_csv('../input/2017.csv')

data2015.corr()

f,ax = plt.subplots(figsize=(18, 18))
sns.heatmap(data2015.corr(), annot=True, linewidths=.5, fmt= '.1f',ax=ax)
plt.show()

import matplotlib.pyplot as plt

fig, axes = plt.subplots(nrows=2, ncols=2)

df1.plot(ax=axes[0,0])
df2.plot(ax=axes[0,1])
...

fig, axes = plt.subplots(figsize=(10, 10), nrows=2, ncols=2)
data_updated = data2015.rename(index=str, columns={'Happiness Rank': 'Happiness_Rank', 'Standard Error': 'Standard_Error'})
data_2015U = data_updated.rename(index=str, columns={'Happiness Score': 'Happiness_Score'})
data_2015U = data_2015U.rename(index=str, columns={'Economy (GDP per Capita)': 'Economy', 'Dystopia Residual': 'Dystopia_Residual', 'Health (Life Expectancy)': 'Health', 'Trust (Government Corruption)': 'Trust'})
plt.legend(loc='upper right')
data_2015U = data_2015U.set_index('Happiness_Rank')
data_2015U.Happiness_Score.plot(ax=axes[0, 0], kind='line', color='red', title='Happiness Score', linewidth=1, grid=True, linestyle=':')
data_2015U.Family.plot(ax=axes[0, 1], kind='line', color='green', title='Family', linewidth=1, grid=True, linestyle=':')
data_2015U.Economy.plot(ax=axes[1, 0], kind='line', color='yellow', title='Economy', linewidth=1, grid=True, linestyle=':')
data_2015U.Health.plot(ax=axes[1, 1], kind='line', color='blue', title='Health', linewidth=1, grid=True, linestyle=':')