

def slice_indexer(self, start=None, end=None, step=None, kind=None):
    '\n        For an ordered Index, compute the slice indexer for input labels and\n        step\n\n        Parameters\n        ----------\n        start : label, default None\n            If None, defaults to the beginning\n        end : label, default None\n            If None, defaults to the end\n        step : int, default None\n        kind : string, default None\n\n        Returns\n        -------\n        indexer : ndarray or slice\n\n        Notes\n        -----\n        This function assumes that the data is sorted, so use at your own peril\n        '
    (start_slice, end_slice) = self.slice_locs(start, end, step=kind, kind=kind)
    if (not lib.isscalar(start_slice)):
        raise AssertionError('Start slice bound is non-scalar')
    if (not lib.isscalar(end_slice)):
        raise AssertionError('End slice bound is non-scalar')
    return slice(start_slice, end_slice, step)

dataset/ETHPy150Open pydata/pandas/pandas/indexes/base.py Index.slice_indexer/VarMisuse@44/243 `step`->`kind`