Method sample

pandas/core/generic.py:5842–5994

Return a random sample of items from an axis of object. You can use `random_state` for reproducibility. Parameters ---------- n : int, optional Number of items from axis to return. Cannot be used with `frac`. Default = 1 if `frac` =

(
        self,
        n: int | None = None,
        frac: float | None = None,
        replace: bool = False,
        weights=None,
        random_state: RandomState | None = None,
        axis: Axis | None = None,
        ignore_index: bool = False,
    )

    @final
    def sample(
        self,
        n: int | None = None,
        frac: float | None = None,
        replace: bool = False,
        weights=None,
        random_state: RandomState | None = None,
        axis: Axis | None = None,
        ignore_index: bool = False,
    ) -> Self:
        """
        Return a random sample of items from an axis of object.

        You can use `random_state` for reproducibility.

        Parameters
        ----------
        n : int, optional
            Number of items from axis to return. Cannot be used with `frac`.
            Default = 1 if `frac` = None.
        frac : float, optional
            Fraction of axis items to return. Cannot be used with `n`.
        replace : bool, default False
            Allow or disallow sampling of the same row more than once.
        weights : str or ndarray-like, optional
            Default ``None`` results in equal probability weighting.
            If passed a Series, will align with target object on index. Index
            values in weights not found in sampled object will be ignored and
            index values in sampled object not in weights will be assigned
            weights of zero.
            If called on a DataFrame, will accept the name of a column
            when axis = 0.
            Unless weights are a Series, weights must be same length as axis
            being sampled.
            If weights do not sum to 1, they will be normalized to sum to 1.
            Missing values in the weights column will be treated as zero.
            Infinite values not allowed.
            When replace = False will not allow ``(n * max(weights) / sum(weights)) > 1``
            in order to avoid biased results. See the Notes below for more details.
        random_state : int, array-like, BitGenerator, np.random.RandomState, np.random.Generator, optional
            If int, array-like, or BitGenerator, seed for random number generator.
            If np.random.RandomState or np.random.Generator, use as given.
            Default ``None`` results in sampling with the current state of np.random.
        axis : {0 or 'index', 1 or 'columns', None}, default None
            Axis to sample. Accepts axis number or name. Default is stat axis
            for given data type. For `Series` this parameter is unused and defaults to `None`.
        ignore_index : bool, default False
            If True, the resulting index will be labeled 0, 1, …, n - 1.

        Returns
        -------
        Series or DataFrame
            A new object of same type as caller containing `n` items randomly
            sampled from the caller object.

        See Also
        --------
        DataFrameGroupBy.sample: Generates random samples from each group of a