How to Find the Column Name with the Maximum Value for Each Row in a DataFrame?

Find Column Name with Maximum Value for Each Row

Many datasets have rows representing different entities, each with multiple columns representing data about the entities. Sometimes, it becomes necessary to identify the specific column that contains the maximum value for each row. This task can be achieved using the idxmax() function.

In the given example, we have a DataFrame with four columns: "Communications and Search," "Business," "General," and "Lifestyle." We want to create a new column, "Max," that contains the column name corresponding to the maximum value of each row.

To do this, we can use idxmax(axis=1) to find the column index with the maximum value:

df.idxmax(axis=1)

# Output:
0    Communications
1          Business
2    Communications
3    Communications
4          Business
dtype: object

This gives us the column labels, but we can convert them to the corresponding column names:

df['Max'] = df.idxmax(axis=1)

The resulting DataFrame will look like this:

communications and search	business	general	lifestyle	max
0.745763	0.050847	0.118644	0.084746	Communications
0.333333	0.000000	0.583333	0.083333	Business
0.617021	0.042553	0.297872	0.042553	Communications
0.435897	0.000000	0.410256	0.153846	Communications
0.358974	0.076923	0.410256	0.153846	Business

Note that idxmax() can also be used to find the row index at which the maximum value occurs in each column, using df.idxmax() (or df.idxmax(axis=0)).

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