Method rank

pandas/core/generic.py:9425–9582

Compute numerical data ranks (1 through n) along axis. By default, equal values are assigned a rank that is the average of the ranks of those values. Parameters ---------- axis : {0 or 'index', 1 or 'columns'}, default 0 Index to direct

(
        self,
        axis: Axis = 0,
        method: Literal["average", "min", "max", "first", "dense"] = "average",
        numeric_only: bool = False,
        na_option: Literal["keep", "top", "bottom"] = "keep",
        ascending: bool = True,
        pct: bool = False,
    )

    @final
    def rank(
        self,
        axis: Axis = 0,
        method: Literal["average", "min", "max", "first", "dense"] = "average",
        numeric_only: bool = False,
        na_option: Literal["keep", "top", "bottom"] = "keep",
        ascending: bool = True,
        pct: bool = False,
    ) -> Self:
        """
        Compute numerical data ranks (1 through n) along axis.

        By default, equal values are assigned a rank that is the average of the
        ranks of those values.

        Parameters
        ----------
        axis : {0 or 'index', 1 or 'columns'}, default 0
            Index to direct ranking.
            For `Series` this parameter is unused and defaults to 0.
        method : {'average', 'min', 'max', 'first', 'dense'}, default 'average'
            How to rank the group of records that have the same value (i.e. ties):

            * average: average rank of the group
            * min: lowest rank in the group
            * max: highest rank in the group
            * first: ranks assigned in order they appear in the array
            * dense: like 'min', but rank always increases by 1 between groups.

        numeric_only : bool, default False
            For DataFrame objects, rank only numeric columns if set to True.

            .. versionchanged:: 2.0.0
                The default value of ``numeric_only`` is now ``False``.

        na_option : {'keep', 'top', 'bottom'}, default 'keep'
            How to rank NaN values:

            * keep: assign NaN rank to NaN values
            * top: assign lowest rank to NaN values
            * bottom: assign highest rank to NaN values

        ascending : bool, default True
            Whether or not the elements should be ranked in ascending order.
        pct : bool, default False
            Whether or not to display the returned rankings in percentile
            form.

        Returns
        -------
        same type as caller
            Return a Series or DataFrame with data ranks as values.

        See Also
        --------
        core.groupby.DataFrameGroupBy.rank : Rank of values within each group.
        core.groupby.SeriesGroupBy.rank : Rank of values within each group.