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Remove duplicate values across columns in pandas dataframe, without removing entire row

I would like to drop all values which are duplicates across a subset of two or more columns, without removing the entire row.

Dataframe:

    A   B   C
0   foo g   A
1   foo g   G
2   yes y   B
3   bar y   B

Desired result:

    A   B   C
0   foo g   A
1   NaN NaN G
2   yes y   B
3   bar Nan NaN

I have tried the drop_duplicates() feature by grouping data into new data frames by columns and then re-appending them together, but this had its own issues.

I have also tried this solution and this one, but still am stuck. Any guidance would be much appreciated.

(updated original question)



source https://stackoverflow.com/questions/75751595/remove-duplicate-values-across-columns-in-pandas-dataframe-without-removing-ent

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