pandas.DataFrame.applymap

DataFrame.applymap(self, func) [source]

Apply a function to a Dataframe elementwise.

This method applies a function that accepts and returns a scalar to every element of a DataFrame.

Parameters:	func : callable Python function, returns a single value from a single value.
Returns:	DataFrame Transformed DataFrame.

See also

DataFrame.apply

Apply a function along input axis of DataFrame.

Notes

In the current implementation applymap calls func twice on the first column/row to decide whether it can take a fast or slow code path. This can lead to unexpected behavior if func has side-effects, as they will take effect twice for the first column/row.

Examples

>>> df = pd.DataFrame([[1, 2.12], [3.356, 4.567]])
>>> df
       0      1
0  1.000  2.120
1  3.356  4.567

>>> df.applymap(lambda x: len(str(x)))
   0  1
0  3  4
1  5  5

Note that a vectorized version of func often exists, which will be much faster. You could square each number elementwise.

>>> df.applymap(lambda x: x**2)
           0          1
0   1.000000   4.494400
1  11.262736  20.857489

But it’s better to avoid applymap in that case.

>>> df ** 2
           0          1
0   1.000000   4.494400
1  11.262736  20.857489