Function searchsorted

pandas/core/algorithms.py:1229–1310

Find indices where elements should be inserted to maintain order. Find the indices into a sorted array `arr` (a) such that, if the corresponding elements in `value` were inserted before the indices, the order of `arr` would be preserved. Assuming that `arr` is sorted: ===

(
    arr: ArrayLike,
    value: NumpyValueArrayLike | ExtensionArray,
    side: Literal["left", "right"] = "left",
    sorter: NumpySorter | None = None,
)

def searchsorted(
    arr: ArrayLike,
    value: NumpyValueArrayLike | ExtensionArray,
    side: Literal["left", "right"] = "left",
    sorter: NumpySorter | None = None,
) -> npt.NDArray[np.intp] | np.intp:
    """
    Find indices where elements should be inserted to maintain order.

    Find the indices into a sorted array `arr` (a) such that, if the
    corresponding elements in `value` were inserted before the indices,
    the order of `arr` would be preserved.

    Assuming that `arr` is sorted:

    ======  ================================
    `side`  returned index `i` satisfies
    ======  ================================
    left    ``arr[i-1] < value <= self[i]``
    right   ``arr[i-1] <= value < self[i]``
    ======  ================================

    Parameters
    ----------
    arr: np.ndarray, ExtensionArray, Series
        Input array. If `sorter` is None, then it must be sorted in
        ascending order, otherwise `sorter` must be an array of indices
        that sort it.
    value : array-like or scalar
        Values to insert into `arr`.
    side : {'left', 'right'}, optional
        If 'left', the index of the first suitable location found is given.
        If 'right', return the last such index.  If there is no suitable
        index, return either 0 or N (where N is the length of `self`).
    sorter : 1-D array-like, optional
        Optional array of integer indices that sort array a into ascending
        order. They are typically the result of argsort.

    Returns
    -------
    array of ints or int
        If value is array-like, array of insertion points.
        If value is scalar, a single integer.

    See Also
    --------
    numpy.searchsorted : Similar method from NumPy.
    """
    if sorter is not None:
        sorter = ensure_platform_int(sorter)

    if (
        isinstance(arr, np.ndarray)
        and arr.dtype.kind in "iu"
        and (is_integer(value) or is_integer_dtype(value))
    ):
        # if `arr` and `value` have different dtypes, `arr` would be
        # recast by numpy, causing a slow search.