Apply function func group-wise and combine the results together.
The function passed to apply must take a dataframe as its first
argument and return a DataFrame, Series or scalar. apply will
then take care of combining the results back together into a single
dataframe or series. apply is therefore a highly flexible
While apply is a very flexible method, its downside is that
using it can be quite a bit slower than using more specific methods
like agg or transform. Pandas offers a wide range of method that will
be much faster than using apply for their specific purposes, so try to
use them before reaching for apply.
A callable that takes a dataframe as its first argument, and
returns a dataframe, a series or a scalar. In addition the
callable may take positional and keyword arguments.
Optional positional and keyword arguments to pass to func.
Apply function to the full GroupBy object instead of to each group.
Apply aggregate function to the GroupBy object.
Apply function column-by-column to the GroupBy object.
Apply a function to a Series.
Apply a function to each row or column of a DataFrame.