How to substract the values of two different dataframes with the same column names and number of rows and store them into a new dataframe

Question:

i have two different dataframes with the same indexes and also the same column names and I want to substract each corrensponding value of them (for example df3[1,1]=df2[1,1]-df1[1,1]) and create a new dataframe with the new values. The dtypes of both dataframes are float64.

I tried the below and worked fine but it seems to me that it may exist a simpler way to do it.

df3=df2.select_dtypes(include=np.number)-df1.select_dtypes(include=np.number)

Can you please advise on an alternate way?

Thank you in advance for your support!

Asked By: Panvas

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Answers:

You can do this in a shorter manner:

import pandas as pd
import numpy as np

df1 = pd.DataFrame(np.random.rand(5, 3), index=['a', 'b', 'c', 'd', 'e'], columns=['col1', 'col2', 'col3'])
df2 = pd.DataFrame(np.random.rand(5, 3), index=['a', 'b', 'c', 'd', 'e'], columns=['col1', 'col2', 'col3'])

df3 = df2.sub(df1)

print(df3)

which retunrs:

       col1      col2      col3
a -0.263918  0.621965 -0.222294
b  0.939496 -0.448462  0.010776
c -0.762741 -0.053359  0.628212
d -0.316622  0.054509  0.297014
e  0.027428  0.065722  0.149325
Answered By: Serge de Gosson de Varennes