Find the column name which has the maximum value for each row

Question

I have a DataFrame like this one:

In [7]:
frame.head()
Out[7]:
Communications and Search   Business    General Lifestyle
0   0.745763    0.050847    0.118644         


        

Answer 1

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)).

Answer 2

And if you want to produce a column containing the name of the column with the maximum value but considering only a subset of columns then you use a variation of @ajcr's answer:

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

Answer 3

You could apply on dataframe and get argmax() of each row via axis=1

In [144]: df.apply(lambda x: x.argmax(), axis=1)
Out[144]:
0    Communications
1          Business
2    Communications
3    Communications
4          Business
dtype: object

---

Here's a benchmark to compare how slow apply method is to idxmax() for len(df) ~ 20K

In [146]: %timeit df.apply(lambda x: x.argmax(), axis=1)
1 loops, best of 3: 479 ms per loop

In [147]: %timeit df.idxmax(axis=1)
10 loops, best of 3: 47.3 ms per loop