Merge dataframes based on column values with duplicated rows

Question

I want to merge two dataframes based on equal column values. The problem is that one of my columns have duplicated row values, which cannot be drop since it's correlated to another columns. Here's an example of my two dataframes:

Essentialy, I want to merge this two dataframes based on equal values of FromPatchID (df1) and Id (df2) columns, in order to get something like this:

FromPatchID ToPatchID ... Id MMM LB 1 1 ... 1 26.67 27.67 1 2 ... 1 26.67 27.67 1 3 ... 1 26.67 27.67 2 1 ... 2 26.50 27.50 3 1 ... 3 26.63 27.63

I already tried a simple merge with df_merged = pd.merge(df1, df2, on=['FromPatchID','Id']), but I got KeyError indicating to check for duplicates in FromPatchID column.

RJ Adriaansen · Accepted Answer · 2021-08-27 18:53:09Z

2

You have to specify the different column names to match on with left_on and right_on. Also specify how='right' to use only keys from the right frame.

df_merged = pd.merge(df1, df2, left_on='FromPatchID', right_on='Id', how='right')

answered Aug 27, 2021 at 18:53

RJ Adriaansen

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Gabriel Lucas Over a year ago

It worked, thank you! The only point is that I had to specify how='left' instead of 'right' to merge within the whole range of my df1 :)

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