If this was my dataframe
| a | b | c |
|---|---|---|
| 12 | 5 | 0.1 |
| 9 | 7 | 8 |
| 1.1 | 2 | 12.9 |
I can use the following code to get the max values in each row... (12) (9) (12.9)
df = df.max(axis=1)
But I don't know would you get the max values only comparing columns a & b (12, 9, 2)
Assuming one wants to consider only the columns a and b, and store the maximum value in a new column called max, one can do the following
df['max'] = df[['a', 'b']].max(axis=1)
[Out]:
a b c max
0 12.0 5 0.1 12.0
1 9.0 7 8.0 9.0
2 1.1 2 12.9 2.0
One can also do that with a custom lambda function, as follows
df['max'] = df[['a', 'b']].apply(lambda x: max(x), axis=1)
[Out]:
a b c max
0 12.0 5 0.1 12.0
1 9.0 7 8.0 9.0
2 1.1 2 12.9 2.0
As per OP's request, if one wants to create a new column, max_of_all, that one will use to store the maximum value for all the dataframe columns, one can use the following
df['max_of_all'] = df.max(axis=1)
[Out]:
a b c max max_of_all
0 12.0 5 0.1 12.0 12.0
1 9.0 7 8.0 9.0 9.0
2 1.1 2 12.9 2.0 12.9