def match(to_match, values, na_sentinel=-1):
    """
    Compute locations of to_match into values

    Parameters
    ----------
    to_match : array-like
        values to find positions of
    values : array-like
        Unique set of values
    na_sentinel : int, default -1
        Value to mark "not found"

    Examples
    --------

    Returns
    -------
    match : ndarray of integers
    """
    values = com.asarray_tuplesafe(values)
    htable, _, values, dtype, ndtype = _get_hashtable_algo(values)
    to_match, _, _ = _ensure_data(to_match, dtype)
    table = htable(min(len(to_match), 1000000))
    table.map_locations(values)
    result = table.lookup(to_match)

    if na_sentinel != -1:

        # replace but return a numpy array
        # use a Series because it handles dtype conversions properly
        from pandas import Series
        result = Series(result.ravel()).replace(-1, na_sentinel)
        result = result.values.reshape(result.shape)

    return result
Compute locations of to_match into values

    Parameters
    ----------
    to_match : array-like
        values to find positions of
    values : array-like
        Unique set of values
    na_sentinel : int, default -1
        Value to mark "not found"

    Examples
    --------

    Returns
    -------
    match : ndarray of integers