Method all

pandas/core/series.py:7632–7733

Return whether all elements are True, potentially over an axis. Returns True unless there at least one element within a series or along a Dataframe axis that is False or equivalent (e.g. zero or empty). Parameters ---------- axis : {0 or 'in

(
        self,
        axis: Axis = 0,
        bool_only: bool = False,
        skipna: bool = True,
        **kwargs,
    )

    @deprecate_nonkeyword_arguments(Pandas4Warning, allowed_args=["self"], name="all")
    def all(
        self,
        axis: Axis = 0,
        bool_only: bool = False,
        skipna: bool = True,
        **kwargs,
    ) -> bool:
        """
        Return whether all elements are True, potentially over an axis.

        Returns True unless there at least one element within a series or
        along a Dataframe axis that is False or equivalent (e.g. zero or
        empty).

        Parameters
        ----------
        axis : {0 or 'index', 1 or 'columns', None}, default 0
            Indicate which axis or axes should be reduced. For `Series` this parameter
            is unused and defaults to 0.

            * 0 / 'index' : reduce the index, return a Series whose index is the
              original column labels.
            * 1 / 'columns' : reduce the columns, return a Series whose index is the
              original index.
            * None : reduce all axes, return a scalar.

        bool_only : bool, default False
            Include only boolean columns. Not implemented for Series.
        skipna : bool, default True
            Exclude NA/null values. If the entire row/column is NA and skipna is
            True, then the result will be True, as for an empty row/column.
            If skipna is False, then NA are treated as True, because these are not
            equal to zero.
        **kwargs : any, default None
            Additional keywords have no effect but might be accepted for
            compatibility with NumPy.

        Returns
        -------
        Series or scalar
            If axis=None, then a scalar boolean is returned.
            Otherwise a Series is returned with index matching the index argument.

        See Also
        --------
        Series.all : Return True if all elements are True.
        DataFrame.any : Return True if one (or more) elements are True.

        Examples
        --------
        **Series**

        >>> pd.Series([True, True]).all()
        True
        >>> pd.Series([True, False]).all()
        False
        >>> pd.Series([], dtype="float64").all()
        True