Lerenn Lerenn - 4 days ago 7
Python Question

Pandas (Python) - Update column of a dataframe from another one with conditions

I had a problem and I found a solution but I feel it's the wrong way to do it.
Maybe, there is a more 'canonical' way to do it.

Problem

I have two dataframe that I would like to merge without having extra column and without erasing existing infos. Example :

Existing dataframe (df)

A A2 B
0 1 4 0
1 2 5 1


Dataframe to merge (df2)

A A2 B
0 1 4 2
1 3 5 2


I would like to update
df
with
df2
if columns 'A' and 'A2' corresponds.
The result would be (:

A A2 B
0 1 4 2.0 <= Update value ONLY
1 2 5 1.0


Here is my solution, but I think it's not a really good one.

import pandas as pd

df = pd.DataFrame([[1,4,0],[2,5,1]],columns=['A','A2','B'])

df2 = pd.DataFrame([[1,4,2],[3,5,2]],columns=['A','A2','B'])

df = df.merge(df2,on=['A', 'A2'],how='left')
df['B_y'].fillna(0, inplace=True)
df['B'] = df['B_x']+df['B_y']
df = df.drop(['B_x','B_y'], axis=1)
print(df)


Does anyone has a better way to do ?
Thanks !

Answer

Yes, it can be done without merge:

rows = (df[['A','A2']] == df2[['A','A2']]).all(axis=1)
df.loc[rows,'B'] = df2.loc[rows,'B']
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