GroupBy.
apply
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 grouping method.
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.
See also
pipe
Apply function to the full GroupBy object instead of to each group.
aggregate
Apply aggregate function to the GroupBy object.
transform
Apply function column-by-column to the GroupBy object.
Series.apply
Apply a function to a Series.
DataFrame.apply
Apply a function to each row or column of a DataFrame.