Method reindex

pandas/core/series.py:5299–5533

Conform Series to new index with optional filling logic. Places NA/NaN in locations having no value in the previous index. A new object is produced unless the new index is equivalent to the current one and ``copy=False``. Parameters ----------

(  # type: ignore[override]
        self,
        index=None,
        *,
        axis: Axis | None = None,
        method: ReindexMethod | None = None,
        copy: bool | lib.NoDefault = lib.no_default,
        level: Level | None = None,
        fill_value: Scalar | None = None,
        limit: int | None = None,
        tolerance=None,
    )

    # error: Cannot determine type of 'reindex'

    def reindex(  # type: ignore[override]
        self,
        index=None,
        *,
        axis: Axis | None = None,
        method: ReindexMethod | None = None,
        copy: bool | lib.NoDefault = lib.no_default,
        level: Level | None = None,
        fill_value: Scalar | None = None,
        limit: int | None = None,
        tolerance=None,
    ) -> Series:
        """
        Conform Series to new index with optional filling logic.

        Places NA/NaN in locations having no value in the previous index. A new object
        is produced unless the new index is equivalent to the current one and
        ``copy=False``.

        Parameters
        ----------
        index : scalar, list-like, dict-like or function, optional
            A scalar, list-like, dict-like or functions transformations to
            apply to that axis' values.
        axis : {0 or 'index'}, default 0
            The axis to rename. For `Series` this parameter is unused and defaults to 0.
        method : {None, 'backfill'/'bfill', 'pad'/'ffill', 'nearest'}
            Method to use for filling holes in reindexed DataFrame.
            Please note: this is only applicable to DataFrames/Series with a
            monotonically increasing/decreasing index.

            * None (default): don't fill gaps
            * pad / ffill: Propagate last valid observation forward to next
              valid.
            * backfill / bfill: Use next valid observation to fill gap.
            * nearest: Use nearest valid observations to fill gap.

        copy : bool, default False
            This keyword is now ignored; changing its value will have no
            impact on the method.

            .. deprecated:: 3.0.0

                This keyword is ignored and will be removed in pandas 4.0. Since
                pandas 3.0, this method always returns a new object using a lazy
                copy mechanism that defers copies until necessary
                (Copy-on-Write). See the `user guide on Copy-on-Write
                <https://pandas.pydata.org/docs/dev/user_guide/copy_on_write.html>`__
                for more details.

        level : int or name
            Broadcast across a level, matching Index values on the
            passed MultiIndex level.
        fill_value : scalar, default np.nan
            Value to use for missing values. Defaults to NaN, but can be any
            "compatible" value.
        limit : int, default None
            Maximum number of consecutive elements to forward or backward fill.