def pivot_apply(df, column, index, func, *args, **kwargs):
    """
    Apply a function to each group of a column

    The function is kind of equivalent to R's *tapply*.

    Parameters
    ----------
    df : dataframe
        Dataframe to be pivoted
    column : str
        Column to apply function to.
    index : str
        Column that will be grouped on (and whose unique values
        will make up the index of the returned dataframe)
    func : function
        Function to apply to each column group. It *should* return
        a single value.
    *args : tuple
        Arguments to ``func``
    **kwargs : dict
        Keyword arguments to ``func``

    Returns
    -------
    out : dataframe
        Dataframe with index ``index`` and column ``column`` of
        computed/aggregate values .
    """
    def _func(x):
        return func(x, *args, **kwargs)

    return df.pivot_table(column, index, aggfunc=_func)[column]
Apply a function to each group of a column

    The function is kind of equivalent to R's *tapply*.

    Parameters
    ----------
    df : dataframe
        Dataframe to be pivoted
    column : str
        Column to apply function to.
    index : str
        Column that will be grouped on (and whose unique values
        will make up the index of the returned dataframe)
    func : function
        Function to apply to each column group. It *should* return
        a single value.
    *args : tuple
        Arguments to ``func``
    **kwargs : dict
        Keyword arguments to ``func``

    Returns
    -------
    out : dataframe
        Dataframe with index ``index`` and column ``column`` of
        computed/aggregate values .