xorbits.pandas.DataFrame.applymap#

DataFrame.applymap(func: Callable, na_action: str = None, skip_infer: bool = False, **kwds)#

Apply a function to a Dataframe elementwise.

Deprecated since version 2.1.0(pandas): DataFrame.applymap has been deprecated. Use DataFrame.map instead.

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.

  • na_action ({None, 'ignore'}, default None) – If ‘ignore’, propagate NaN values, without passing them to func.

  • **kwargs – Additional keyword arguments to pass as keywords arguments to func.

Returns

Transformed DataFrame.

Return type

DataFrame

See also

DataFrame.apply

Apply a function along input axis of DataFrame.

DataFrame.map

Apply a function along input axis of DataFrame.

DataFrame.replace

Replace values given in to_replace with value.

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.map(lambda x: len(str(x)))  
   0  1
0  3  4
1  5  5
skip_infer: bool, default False

Whether infer dtypes when dtypes or output_type is not specified.

This docstring was copied from pandas.core.frame.DataFrame.