import pandas as pd, numpy as np
Sales16 = pd.DataFrame({‘revenue’: [100, 200, 250, 275, 300, 350]})
Sales17 = pd.DataFrame({‘revenue’: [100, 200, np.nan, 275, np.nan, 350]})
print(Sales17.combine_first(Sales16)) # combine_first used to fill the missing values of Sales17 with the corresponding values of Sales16