Why does I get type error while importing dataprep?

Question

I try to importing clean_lat_long from dataprep. But I get TypeError instead

here's my code:

from dataprep.clean import clean_lat_long

But I get

TypeError                                 Traceback (most recent call last)
Cell In[32], line 1
----> 1 from dataprep.clean import clean_lat_long
      3 cleanedDF = clean_lat_long(data, "Coordinate", split=True)

File ~\anaconda3\lib\site-packages\dataprep\clean\__init__.py:6
      1 """
      2 dataprep.clean
      3 ==============
      4 """
----> 6 from .clean_lat_long import clean_lat_long, validate_lat_long
      8 from .clean_email import clean_email, validate_email
     10 from .clean_country import clean_country, validate_country

File ~\anaconda3\lib\site-packages\dataprep\clean\clean_lat_long.py:9
      6 from typing import Any, Optional, Tuple, Union
      8 import dask
----> 9 import dask.dataframe as dd
     10 import numpy as np
     11 import pandas as pd

File ~\anaconda3\lib\site-packages\dask\dataframe\__init__.py:6
      4 import dask.dataframe._pyarrow_compat
      5 from dask.base import compute
----> 6 from dask.dataframe import backends, dispatch, rolling
      7 from dask.dataframe.core import (
      8     DataFrame,
      9     Index,
   (...)
     15     to_timedelta,
     16 )
     17 from dask.dataframe.groupby import Aggregation

File ~\anaconda3\lib\site-packages\dask\dataframe\backends.py:10
      7 import pandas as pd
      8 from pandas.api.types import is_scalar, union_categoricals
---> 10 from dask.array.core import Array
     11 from dask.array.dispatch import percentile_lookup
     12 from dask.array.percentile import _percentile

File ~\anaconda3\lib\site-packages\dask\array\__init__.py:4
      1 from __future__ import annotations
      3 try:
----> 4     from dask.array import backends, fft, lib, linalg, ma, overlap, random
      5     from dask.array.blockwise import atop, blockwise
      6     from dask.array.chunk_types import register_chunk_type

File ~\anaconda3\lib\site-packages\dask\array\backends.py:8
      5 import numpy as np
      7 from dask.array import chunk
----> 8 from dask.array.core import Array
      9 from dask.array.dispatch import (
     10     concatenate_lookup,
     11     divide_lookup,
   (...)
     19     to_numpy_dispatch,
     20 )
     21 from dask.array.numpy_compat import divide as np_divide

File ~\anaconda3\lib\site-packages\dask\array\core.py:30
     27 from typing import Any, TypeVar, Union, cast
     29 import numpy as np
---> 30 from numpy.typing import ArrayLike
     31 from tlz import accumulate, concat, first, frequencies, groupby, partition
     32 from tlz.curried import pluck

File ~\anaconda3\lib\site-packages\numpy\typing\__init__.py:158
      1 """
      2 ============================
      3 Typing (:mod:`numpy.typing`)
   (...)
    153 
    154 """
    155 # NOTE: The API section will be appended with additional entries
    156 # further down in this file
--> 158 from numpy._typing import (
    159     ArrayLike,
    160     DTypeLike,
    161     NBitBase,
    162     NDArray,
    163 )
    165 __all__ = ["ArrayLike", "DTypeLike", "NBitBase", "NDArray"]
    167 if __doc__ is not None:

File ~\anaconda3\lib\site-packages\numpy\_typing\__init__.py:148
     95 from ._nbit import (
     96     _NBitByte as _NBitByte,
     97     _NBitShort as _NBitShort,
   (...)
    105     _NBitLongDouble as _NBitLongDouble,
    106 )
    107 from ._char_codes import (
    108     _BoolCodes as _BoolCodes,
    109     _UInt8Codes as _UInt8Codes,
   (...)
    146     _ObjectCodes as _ObjectCodes,
    147 )
--> 148 from ._scalars import (
    149     _CharLike_co as _CharLike_co,
    150     _BoolLike_co as _BoolLike_co,
    151     _UIntLike_co as _UIntLike_co,
    152     _IntLike_co as _IntLike_co,
    153     _FloatLike_co as _FloatLike_co,
    154     _ComplexLike_co as _ComplexLike_co,
    155     _TD64Like_co as _TD64Like_co,
    156     _NumberLike_co as _NumberLike_co,
    157     _ScalarLike_co as _ScalarLike_co,
    158     _VoidLike_co as _VoidLike_co,
    159 )
    160 from ._shape import (
    161     _Shape as _Shape,
    162     _ShapeLike as _ShapeLike,
    163 )
    164 from ._dtype_like import (
    165     DTypeLike as DTypeLike,
    166     _DTypeLike as _DTypeLike,
   (...)
    180     _DTypeLikeComplex_co as _DTypeLikeComplex_co,
    181 )

File ~\anaconda3\lib\site-packages\numpy\_typing\_scalars.py:13
     10 # The 6 `<X>Like_co` type-aliases below represent all scalars that can be
     11 # coerced into `<X>` (with the casting rule `same_kind`)
     12 _BoolLike_co = Union[bool, np.bool_]
---> 13 _UIntLike_co = Union[_BoolLike_co, np.unsignedinteger[Any]]
     14 _IntLike_co = Union[_BoolLike_co, int, np.integer[Any]]
     15 _FloatLike_co = Union[_IntLike_co, float, np.floating[Any]]

TypeError: 'type' object is not subscriptable

What should I do to fix it?