Method reindex

pandas/core/frame.py:5857–6103

Conform DataFrame 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 ----------

(
        self,
        labels=None,
        *,
        index=None,
        columns=None,
        axis: Axis | None = None,
        method: ReindexMethod | None = None,
        copy: bool | lib.NoDefault = lib.no_default,
        level: Level | None = None,
        fill_value: Scalar | None = np.nan,
        limit: int | None = None,
        tolerance=None,
    )

        return super().set_axis(labels, axis=axis, copy=copy)

    def reindex(
        self,
        labels=None,
        *,
        index=None,
        columns=None,
        axis: Axis | None = None,
        method: ReindexMethod | None = None,
        copy: bool | lib.NoDefault = lib.no_default,
        level: Level | None = None,
        fill_value: Scalar | None = np.nan,
        limit: int | None = None,
        tolerance=None,
    ) -> DataFrame:
        """
        Conform DataFrame 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
        ----------

        labels : array-like, optional
            New labels / index to conform the axis specified by 'axis' to.
        index : array-like, optional
            New labels for the index. Preferably an Index object to avoid
            duplicating data.
        columns : array-like, optional
            New labels for the columns. Preferably an Index object to avoid
            duplicating data.
        axis : int or str, optional
            Axis to target. Can be either the axis name ('index', 'columns')
            or number (0, 1).
        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.