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We can see that it returned a series of maximum values where the index is column name and values are the maxima from each column. How to find the maximum values of every row? To find the maximum value of each row, call the max() method on the Dataframe object with an argument axis = 1.
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.
Maximum value of a column in R can be calculated by using max() function. Max() Function takes column name as argument and calculates the maximum value of that column.
max() in R The max() is a built-in R function that finds the maximum value of the vector or data frame. It takes the R object as an input and returns the maximum value out of it. To find the maximum value of vector elements, data frame, and columns, use the max() function.
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)).
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)
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
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