Apply function to each cell in DataFrame

I have a dataframe that may look like this:

A        B        C
foo      bar      foo bar
bar foo  foo      bar

I want to look through every element of each row (or every element of each column) and apply the following function to get the subsequent DF:

def foo_bar(x):
    return x.replace('foo', 'wow')

A        B        C
wow      bar      wow bar
bar wow  wow      bar

Is there a simple one-liner that can apply a function to each cell?

This is a simplistic example so there may be an easier way to execute this specific example other than applying a function, but what I am really asking about is how to apply a function in every cell within a dataframe.

Answers:

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Method 1

You can use applymap() which is concise for your case.

df.applymap(foo_bar)

#     A       B       C
#0  wow     bar wow bar
#1  bar wow wow     bar

Another option is to vectorize your function and then use apply method:

import numpy as np
df.apply(np.vectorize(foo_bar))
#     A       B       C
#0  wow     bar wow bar
#1  bar wow wow     bar

Method 2

I guess you could use np.vectorize:

>>> df[:] = np.vectorize(foo_bar)(df)
>>> df
       A    B    C
foo  bar  wow  bar
bar  wow  wow  bar
>>>

This might be quicker, since it’s using numpy.

All methods was sourced from stackoverflow.com or stackexchange.com, is licensed under cc by-sa 2.5, cc by-sa 3.0 and cc by-sa 4.0