import pandas as pd # create two series with different indexes ser1 = pd.Series([1, 2, 3], index=['a', 'b', 'c']) ser2 = pd.Series([4, 5, 6, 7], index=['c', 'd', 'e', 'f']) # align the series aligned_ser1, aligned_ser2 = ser1.align(ser2, fill_value=0) print(aligned_ser1) # Output: # a 1 # b 2 # c 3 # d 0 # e 0 # f 0 print(aligned_ser2) # Output: # a 0 # b 0 # c 4 # d 5 # e 6 # f 7
import pandas as pd # create two series with different indexes ser1 = pd.Series([1, 2, 3], index=['a', 'b', 'c']) ser2 = pd.Series([4, 5, 6, 7], index=['c', 'd', 'e', 'f']) # align the series aligned_ser1, aligned_ser2 = ser1.align(ser2, fill_value=0) # calculate correlation corr = aligned_ser1.corr(aligned_ser2) print(corr) # Output: -0.33806170189140634The pandas package library is used to work with data frames and has functions for data manipulation, merging, cleaning, and more. The Series align function is included in the pandas library.