Method sum

pandas/core/series.py:7878–7976

Return the sum of the values over the requested axis. This is equivalent to the method ``numpy.sum``. Parameters ---------- axis : {index (0)} Axis for the function to be applied on. For `Series` this parameter is unused and defaults

(
        self,
        axis: Axis | None = None,
        skipna: bool = True,
        numeric_only: bool = False,
        min_count: int = 0,
        **kwargs,
    )

    @deprecate_nonkeyword_arguments(Pandas4Warning, allowed_args=["self"], name="sum")
    def sum(
        self,
        axis: Axis | None = None,
        skipna: bool = True,
        numeric_only: bool = False,
        min_count: int = 0,
        **kwargs,
    ):
        """
        Return the sum of the values over the requested axis.

        This is equivalent to the method ``numpy.sum``.

        Parameters
        ----------
        axis : {index (0)}
            Axis for the function to be applied on.
            For `Series` this parameter is unused and defaults to 0.

            .. warning::

                The behavior of DataFrame.sum with ``axis=None`` is deprecated,
                in a future version this will reduce over both axes and return a scalar
                To retain the old behavior, pass axis=0 (or do not pass axis).

            .. versionadded:: 2.0.0

        skipna : bool, default True
            Exclude NA/null values when computing the result.
        numeric_only : bool, default False
            Include only float, int, boolean columns. Not implemented for Series.

        min_count : int, default 0
            The required number of valid values to perform the operation. If fewer than
            ``min_count`` non-NA values are present the result will be NA.
        **kwargs
            Additional keyword arguments to be passed to the function.

        Returns
        -------
        scalar or Series (if level specified)
            Sum of the values for the requested axis.

        See Also
        --------
        numpy.sum : Equivalent numpy function for computing sum.
        Series.mean : Mean of the values.
        Series.median : Median of the values.
        Series.std : Standard deviation of the values.
        Series.var : Variance of the values.
        Series.min : Minimum value.
        Series.max : Maximum value.

        Examples
        --------
        >>> idx = pd.MultiIndex.from_arrays(
        ...     [["warm", "warm", "cold", "cold"], ["dog", "falcon", "fish", "spider"]],
        ...     names=["blooded", "animal"],