pandas.DataFrame.transform — pandas 0.24.0rc1 documentation (original) (raw)

DataFrame. transform(func, axis=0, *args, **kwargs)[source]¶

Call func on self producing a DataFrame with transformed values and that has the same axis length as self.

New in version 0.20.0.

Parameters:	func : function, str, list or dict Function to use for transforming the data. If a function, must either work when passed a DataFrame or when passed to DataFrame.apply. Accepted combinations are: function string function name list of functions and/or function names, e.g. [np.exp. 'sqrt'] dict of axis labels -> functions, function names or list of such. axis : {0 or ‘index’, 1 or ‘columns’}, default 0 If 0 or ‘index’: apply function to each column. If 1 or ‘columns’: apply function to each row. args Positional arguments to pass to func. *kwargs Keyword arguments to pass to func.
Returns:	DataFrame A DataFrame that must have the same length as self.
Raises:	ValueError : If the returned DataFrame has a different length than self.

Parameters:

func : function, str, list or dict Function to use for transforming the data. If a function, must either work when passed a DataFrame or when passed to DataFrame.apply. Accepted combinations are: function string function name list of functions and/or function names, e.g. [np.exp. 'sqrt'] dict of axis labels -> functions, function names or list of such. axis : {0 or ‘index’, 1 or ‘columns’}, default 0 If 0 or ‘index’: apply function to each column. If 1 or ‘columns’: apply function to each row. *args Positional arguments to pass to func. **kwargs Keyword arguments to pass to func.

Returns:

DataFrame A DataFrame that must have the same length as self.

Raises:

ValueError : If the returned DataFrame has a different length than self.

Examples

df = pd.DataFrame({'A': range(3), 'B': range(1, 4)}) df A B 0 0 1 1 1 2 2 2 3 df.transform(lambda x: x + 1) A B 0 1 2 1 2 3 2 3 4

Even though the resulting DataFrame must have the same length as the input DataFrame, it is possible to provide several input functions:

s = pd.Series(range(3)) s 0 0 1 1 2 2 dtype: int64 s.transform([np.sqrt, np.exp]) sqrt exp 0 0.000000 1.000000 1 1.000000 2.718282 2 1.414214 7.389056