pandas.DataFrame.apply — pandas 0.16.2 documentation (original) (raw)

func : function

Function to apply to each column/row

axis : {0 or ‘index’, 1 or ‘columns’}, default 0

• 0 or ‘index’: apply function to each column
• 1 or ‘columns’: apply function to each row

broadcast : boolean, default False

For aggregation functions, return object of same size with values propagated

reduce : boolean or None, default None

Try to apply reduction procedures. If the DataFrame is empty, apply will use reduce to determine whether the result should be a Series or a DataFrame. If reduce is None (the default), apply’s return value will be guessed by calling func an empty Series (note: while guessing, exceptions raised by func will be ignored). If reduce is True a Series will always be returned, and if False a DataFrame will always be returned.

raw : boolean, default False

If False, convert each row or column into a Series. If raw=True the passed function will receive ndarray objects instead. If you are just applying a NumPy reduction function this will achieve much better performance

args : tuple

Positional arguments to pass to function in addition to the array/series

Additional keyword arguments will be passed as keywords to the function