Replace every value in pandas.DataFrame row with the count of that value

Question

I would like to replace the values in my pd.DataFrame, df with counts of the value in row.

import pandas as pd

df = pd.DataFrame({
  'foo': [3,3,1,1,1,2],
  'bar': [4,4,1,3,3,3]
}).transpose()

	0	1	2	3	4	5
foo	3	3	1	1	1	2
bar	4	4	1	3	3	3

I would expect to see:

	0	1	2	3	4	5
foo	2	2	3	3	3	1
bar	2	2	1	3	3	3

Unable to determine a solution using .apply().

What is the most sensible way of achieving the above?

Chris · Accepted Answer · 2021-08-19 07:08:34Z

1

One way using pandas.Series.value_counts with map:

df.apply(lambda x: x.map(x.value_counts()), axis=1)

Output:

     0  1  2  3  4  5
foo  2  2  3  3  3  1
bar  2  2  1  3  3  3

answered Aug 19, 2021 at 7:08

Chris

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