How can I get the multiple column names based on a value in pandas python?

Question

I've a dataframe that contains normalized values. From each row I can obtain the maxvalue, but now I want to get also the corresponding column names.

For example df:

|----------------------------------------|
|    a    |     b     |   c   | 'newcol' |
|----------------------------------------|
|  0.960  |    1.00   | 1.00  |  b, c    |
|----------------------------------------|
|  0.922  |    0.955  | 0.971 |  c       |
|----------------------------------------|

So i want to create this newcol containing the column names that have the max values. I've tried df.idxmax(axis=1) however this returns only the first column with the max value

Find all indices of maximum in Pandas DataFrame Tries to solve the same problem however the data is stored in a list instead of a new column in same df

Does this answer your question? Find all indices of maximum in Pandas DataFrame — Stefan
– Stefan, Commented Oct 22, 2020 at 9:09

jezrael · Accepted Answer · 2020-10-22 07:12:53Z

1

Use DataFrame.dot for compare all columns with maximum:

df['newcol'] = df.eq(df.max(axis=1), axis=0).dot(df.columns + ',').str.strip(',')
print (df)
       a      b      c newcol
0  0.960  1.000  1.000    b,c
1  0.922  0.955  0.971      c

answered Oct 22, 2020 at 7:12

jezrael

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1 Comment

Erik Over a year ago

That is working indeed, thanks for the fast response

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