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fabincacarlottacfabian
authored and
noatamir
committed
STYLE fix: pylint "consider-using-from" (pandas-dev#49335)
* use from import * delete empty file Co-authored-by: carlotta <[email protected]> Co-authored-by: cfabian <[email protected]>
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+109
-99
lines changed

‎pandas/_libs/parsers.pyx

+1-1
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@@ -74,7 +74,7 @@ from pandas._libs.util cimport (
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UINT64_MAX,
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)
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77-
import pandas._libs.lib as lib
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from pandas._libs import lib
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from pandas._libs.khash cimport (
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kh_destroy_float64,

‎pandas/conftest.py

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@@ -1727,7 +1727,7 @@ def any_skipna_inferred_dtype(request):
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17281728
Examples
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--------
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>>> import pandas._libs.lib as lib
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>>> from pandas._libs import lib
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>>>
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>>> def test_something(any_skipna_inferred_dtype):
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... inferred_dtype, values = any_skipna_inferred_dtype

‎pandas/core/arrays/categorical.py

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@@ -87,14 +87,14 @@
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)
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from pandas.core import (
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algorithms,
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arraylike,
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ops,
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)
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from pandas.core.accessor import (
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PandasDelegate,
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delegate_names,
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)
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import pandas.core.algorithms as algorithms
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from pandas.core.algorithms import (
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factorize,
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take_nd,

‎pandas/core/arrays/sparse/array.py

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@@ -78,7 +78,10 @@
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notna,
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)
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from pandas.core import arraylike
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from pandas.core import (
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arraylike,
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ops,
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)
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import pandas.core.algorithms as algos
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from pandas.core.array_algos.quantile import quantile_with_mask
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from pandas.core.arraylike import OpsMixin
@@ -96,9 +99,8 @@
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)
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from pandas.core.missing import interpolate_2d
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from pandas.core.nanops import check_below_min_count
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import pandas.core.ops as ops
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import pandas.io.formats.printing as printing
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from pandas.io.formats import printing
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# See https://github.com/python/typing/issues/684
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if TYPE_CHECKING:

‎pandas/core/base.py

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@@ -21,7 +21,7 @@
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import numpy as np
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import pandas._libs.lib as lib
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from pandas._libs import lib
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from pandas._typing import (
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Axis,
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AxisInt,

‎pandas/core/computation/engines.py

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@@ -17,7 +17,7 @@
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REDUCTIONS,
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)
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import pandas.io.formats.printing as printing
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from pandas.io.formats import printing
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if TYPE_CHECKING:
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from pandas.core.computation.expr import Expr

‎pandas/core/computation/expr.py

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@@ -44,7 +44,7 @@
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)
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from pandas.core.computation.scope import Scope
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import pandas.io.formats.printing as printing
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from pandas.io.formats import printing
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def _rewrite_assign(tok: tuple[int, str]) -> tuple[int, str]:

‎pandas/core/construction.py

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@@ -18,7 +18,7 @@
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import warnings
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import numpy as np
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import numpy.ma as ma
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from numpy import ma
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from pandas._libs import lib
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from pandas._libs.tslibs.period import Period

‎pandas/core/frame.py

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@@ -33,7 +33,7 @@
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import warnings
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import numpy as np
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import numpy.ma as ma
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from numpy import ma
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from pandas._config import get_option
3939

@@ -685,7 +685,7 @@ def __init__(
685685
# GH#38939 de facto copy defaults to False only in non-dict cases
686686
mgr = dict_to_mgr(data, index, columns, dtype=dtype, copy=copy, typ=manager)
687687
elif isinstance(data, ma.MaskedArray):
688-
import numpy.ma.mrecords as mrecords
688+
from numpy.ma import mrecords
689689

690690
# masked recarray
691691
if isinstance(data, mrecords.MaskedRecords):
@@ -8036,7 +8036,7 @@ def combine_first(self, other: DataFrame) -> DataFrame:
80368036
1 0.0 3.0 1.0
80378037
2 NaN 3.0 1.0
80388038
"""
8039-
import pandas.core.computation.expressions as expressions
8039+
from pandas.core.computation import expressions
80408040

80418041
def combiner(x, y):
80428042
mask = extract_array(isna(x))
@@ -8179,7 +8179,7 @@ def update(
81798179
1 2 500.0
81808180
2 3 6.0
81818181
"""
8182-
import pandas.core.computation.expressions as expressions
8182+
from pandas.core.computation import expressions
81838183

81848184
# TODO: Support other joins
81858185
if join != "left": # pragma: no cover

‎pandas/core/groupby/groupby.py

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@@ -88,9 +88,12 @@ class providing the base-class of operations.
8888
notna,
8989
)
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91-
from pandas.core import nanops
91+
from pandas.core import (
92+
algorithms,
93+
nanops,
94+
sample,
95+
)
9296
from pandas.core._numba import executor
93-
import pandas.core.algorithms as algorithms
9497
from pandas.core.arrays import (
9598
BaseMaskedArray,
9699
BooleanArray,
@@ -121,7 +124,6 @@ class providing the base-class of operations.
121124
RangeIndex,
122125
)
123126
from pandas.core.internals.blocks import ensure_block_shape
124-
import pandas.core.sample as sample
125127
from pandas.core.series import Series
126128
from pandas.core.sorting import get_group_index_sorter
127129
from pandas.core.util.numba_ import (

‎pandas/core/groupby/grouper.py

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@@ -31,7 +31,7 @@
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is_scalar,
3232
)
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34-
import pandas.core.algorithms as algorithms
34+
from pandas.core import algorithms
3535
from pandas.core.arrays import (
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Categorical,
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ExtensionArray,

‎pandas/core/internals/blocks.py

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@@ -76,6 +76,7 @@
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na_value_for_dtype,
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)
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79+
from pandas.core import missing
7980
import pandas.core.algorithms as algos
8081
from pandas.core.array_algos.putmask import (
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extract_bool_array,
@@ -103,13 +104,12 @@
103104
from pandas.core.arrays.sparse import SparseDtype
104105
from pandas.core.base import PandasObject
105106
import pandas.core.common as com
106-
import pandas.core.computation.expressions as expressions
107+
from pandas.core.computation import expressions
107108
from pandas.core.construction import (
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ensure_wrapped_if_datetimelike,
109110
extract_array,
110111
)
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from pandas.core.indexers import check_setitem_lengths
112-
import pandas.core.missing as missing
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114114
if TYPE_CHECKING:
115115
from pandas import (

‎pandas/core/internals/construction.py

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@@ -15,7 +15,7 @@
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import warnings
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import numpy as np
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import numpy.ma as ma
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from numpy import ma
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2020
from pandas._libs import lib
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from pandas._typing import (

‎pandas/core/nanops.py

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@@ -519,12 +519,12 @@ def nanany(
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520520
Examples
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--------
522-
>>> import pandas.core.nanops as nanops
522+
>>> from pandas.core import nanops
523523
>>> s = pd.Series([1, 2])
524524
>>> nanops.nanany(s)
525525
True
526526
527-
>>> import pandas.core.nanops as nanops
527+
>>> from pandas.core import nanops
528528
>>> s = pd.Series([np.nan])
529529
>>> nanops.nanany(s)
530530
False
@@ -565,12 +565,12 @@ def nanall(
565565
566566
Examples
567567
--------
568-
>>> import pandas.core.nanops as nanops
568+
>>> from pandas.core import nanops
569569
>>> s = pd.Series([1, 2, np.nan])
570570
>>> nanops.nanall(s)
571571
True
572572
573-
>>> import pandas.core.nanops as nanops
573+
>>> from pandas.core import nanops
574574
>>> s = pd.Series([1, 0])
575575
>>> nanops.nanall(s)
576576
False
@@ -616,7 +616,7 @@ def nansum(
616616
617617
Examples
618618
--------
619-
>>> import pandas.core.nanops as nanops
619+
>>> from pandas.core import nanops
620620
>>> s = pd.Series([1, 2, np.nan])
621621
>>> nanops.nansum(s)
622622
3.0
@@ -684,7 +684,7 @@ def nanmean(
684684
685685
Examples
686686
--------
687-
>>> import pandas.core.nanops as nanops
687+
>>> from pandas.core import nanops
688688
>>> s = pd.Series([1, 2, np.nan])
689689
>>> nanops.nanmean(s)
690690
1.5
@@ -740,7 +740,7 @@ def nanmedian(values, *, axis: AxisInt | None = None, skipna: bool = True, mask=
740740
741741
Examples
742742
--------
743-
>>> import pandas.core.nanops as nanops
743+
>>> from pandas.core import nanops
744744
>>> s = pd.Series([1, np.nan, 2, 2])
745745
>>> nanops.nanmedian(s)
746746
2.0
@@ -901,7 +901,7 @@ def nanstd(
901901
902902
Examples
903903
--------
904-
>>> import pandas.core.nanops as nanops
904+
>>> from pandas.core import nanops
905905
>>> s = pd.Series([1, np.nan, 2, 3])
906906
>>> nanops.nanstd(s)
907907
1.0
@@ -948,7 +948,7 @@ def nanvar(
948948
949949
Examples
950950
--------
951-
>>> import pandas.core.nanops as nanops
951+
>>> from pandas.core import nanops
952952
>>> s = pd.Series([1, np.nan, 2, 3])
953953
>>> nanops.nanvar(s)
954954
1.0
@@ -1023,7 +1023,7 @@ def nansem(
10231023
10241024
Examples
10251025
--------
1026-
>>> import pandas.core.nanops as nanops
1026+
>>> from pandas.core import nanops
10271027
>>> s = pd.Series([1, np.nan, 2, 3])
10281028
>>> nanops.nansem(s)
10291029
0.5773502691896258
@@ -1100,7 +1100,7 @@ def nanargmax(
11001100
11011101
Examples
11021102
--------
1103-
>>> import pandas.core.nanops as nanops
1103+
>>> from pandas.core import nanops
11041104
>>> arr = np.array([1, 2, 3, np.nan, 4])
11051105
>>> nanops.nanargmax(arr)
11061106
4
@@ -1146,7 +1146,7 @@ def nanargmin(
11461146
11471147
Examples
11481148
--------
1149-
>>> import pandas.core.nanops as nanops
1149+
>>> from pandas.core import nanops
11501150
>>> arr = np.array([1, 2, 3, np.nan, 4])
11511151
>>> nanops.nanargmin(arr)
11521152
0
@@ -1200,7 +1200,7 @@ def nanskew(
12001200
12011201
Examples
12021202
--------
1203-
>>> import pandas.core.nanops as nanops
1203+
>>> from pandas.core import nanops
12041204
>>> s = pd.Series([1, np.nan, 1, 2])
12051205
>>> nanops.nanskew(s)
12061206
1.7320508075688787
@@ -1288,7 +1288,7 @@ def nankurt(
12881288
12891289
Examples
12901290
--------
1291-
>>> import pandas.core.nanops as nanops
1291+
>>> from pandas.core import nanops
12921292
>>> s = pd.Series([1, np.nan, 1, 3, 2])
12931293
>>> nanops.nankurt(s)
12941294
-1.2892561983471076
@@ -1380,7 +1380,7 @@ def nanprod(
13801380
13811381
Examples
13821382
--------
1383-
>>> import pandas.core.nanops as nanops
1383+
>>> from pandas.core import nanops
13841384
>>> s = pd.Series([1, 2, 3, np.nan])
13851385
>>> nanops.nanprod(s)
13861386
6.0

‎pandas/core/ops/array_ops.py

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notna,
4848
)
4949

50-
import pandas.core.computation.expressions as expressions
50+
from pandas.core.computation import expressions
5151
from pandas.core.construction import ensure_wrapped_if_datetimelike
5252
from pandas.core.ops import (
5353
missing,

‎pandas/core/reshape/tile.py

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@@ -43,8 +43,8 @@
4343
to_datetime,
4444
to_timedelta,
4545
)
46+
from pandas.core import nanops
4647
import pandas.core.algorithms as algos
47-
import pandas.core.nanops as nanops
4848

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5050
def cut(

‎pandas/core/strings/accessor.py

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1515
import numpy as np
1616

17-
import pandas._libs.lib as lib
17+
from pandas._libs import lib
1818
from pandas._typing import (
1919
AlignJoin,
2020
DtypeObj,

‎pandas/core/strings/object_array.py

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@@ -11,7 +11,7 @@
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1212
import numpy as np
1313

14-
import pandas._libs.lib as lib
14+
from pandas._libs import lib
1515
import pandas._libs.missing as libmissing
1616
import pandas._libs.ops as libops
1717
from pandas._typing import (

‎pandas/core/window/ewm.py

+1-1
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@@ -27,7 +27,7 @@
2727
)
2828
from pandas.core.dtypes.missing import isna
2929

30-
import pandas.core.common as common # noqa: PDF018
30+
from pandas.core import common # noqa: PDF018
3131
from pandas.core.indexers.objects import (
3232
BaseIndexer,
3333
ExponentialMovingWindowIndexer,

‎pandas/io/excel/_odswriter.py

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cast,
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)
1212

13-
import pandas._libs.json as json
13+
from pandas._libs import json
1414
from pandas._typing import (
1515
FilePath,
1616
StorageOptions,

‎pandas/io/excel/_xlsxwriter.py

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@@ -5,7 +5,7 @@
55
Any,
66
)
77

8-
import pandas._libs.json as json
8+
from pandas._libs import json
99
from pandas._typing import (
1010
FilePath,
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StorageOptions,

‎pandas/io/json/_json.py

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2222
import numpy as np
2323

24-
import pandas._libs.json as json
24+
from pandas._libs import json
2525
from pandas._libs.tslibs import iNaT
2626
from pandas._typing import (
2727
CompressionOptions,

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