Question
Asked By – markov zain
I have a DataFrame like this one:
Communications and Search Business General Lifestyle
0 0.745763 0.050847 0.118644 0.084746
0 0.333333 0.000000 0.583333 0.083333
0 0.617021 0.042553 0.297872 0.042553
0 0.435897 0.000000 0.410256 0.153846
0 0.358974 0.076923 0.410256 0.153846
I want to get the column name which has maximum value for each row. The desired output is like this:
Communications and Search Business General Lifestyle Max
0 0.745763 0.050847 0.118644 0.084746 Communications
0 0.333333 0.000000 0.583333 0.083333 Business
0 0.617021 0.042553 0.297872 0.042553 Communications
0 0.435897 0.000000 0.410256 0.153846 Communications
0 0.358974 0.076923 0.410256 0.153846 Business
Now we will see solution for issue: Find the column name which has the maximum value for each row
Answer
You can use idxmax
with axis=1
to find the column with the greatest value on each row:
>>> df.idxmax(axis=1)
0 Communications
1 Business
2 Communications
3 Communications
4 Business
dtype: object
To create the new column ‘Max’, use df['Max'] = df.idxmax(axis=1)
.
To find the row index at which the maximum value occurs in each column, use df.idxmax()
(or equivalently df.idxmax(axis=0)
).
This question is answered By – Alex Riley
This answer is collected from stackoverflow and reviewed by FixPython community admins, is licensed under cc by-sa 2.5 , cc by-sa 3.0 and cc by-sa 4.0