Method value_counts

pandas/core/frame.py:8560–8707

Return a Series containing the frequency of each distinct row in the DataFrame. Parameters ---------- subset : Hashable or a sequence of the previous, optional Columns to use when counting unique combinations. normalize : bool, default False

(
        self,
        subset: IndexLabel | None = None,
        normalize: bool = False,
        sort: bool = True,
        ascending: bool = False,
        dropna: bool = True,
    )

        )

    def value_counts(
        self,
        subset: IndexLabel | None = None,
        normalize: bool = False,
        sort: bool = True,
        ascending: bool = False,
        dropna: bool = True,
    ) -> Series:
        """
        Return a Series containing the frequency of each distinct row in the DataFrame.

        Parameters
        ----------
        subset : Hashable or a sequence of the previous, optional
            Columns to use when counting unique combinations.
        normalize : bool, default False
            Return proportions rather than frequencies.
        sort : bool, default True
            Stable sort by frequencies when True. Preserve the order of the data
            when False.

            .. versionchanged:: 3.0.0

                Prior to 3.0.0, ``sort=False`` would sort by the columns values.

            .. versionchanged:: 3.0.0

                Prior to 3.0.0, the sort was unstable.
        ascending : bool, default False
            Sort in ascending order.
        dropna : bool, default True
            Do not include counts of rows that contain NA values.

        Returns
        -------
        Series
            Series containing the frequency of each distinct row in the DataFrame.

        See Also
        --------
        Series.value_counts: Equivalent method on Series.

        Notes
        -----
        The returned Series will have a MultiIndex with one level per input
        column but an Index (non-multi) for a single label. By default, rows
        that contain any NA values are omitted from the result. By default,
        the resulting Series will be sorted by frequencies in descending order so that
        the first element is the most frequently-occurring row.

        Examples
        --------
        >>> df = pd.DataFrame(
        ...     {"num_legs": [2, 4, 4, 6], "num_wings": [2, 0, 0, 0]},
        ...     index=["falcon", "dog", "cat", "ant"],
        ... )
        >>> df
                num_legs  num_wings