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STYLE fix: pylint "consider-using-from" (#49335)
* use from import * delete empty file Co-authored-by: carlotta <c.fabian@turbit.de> Co-authored-by: cfabian <cfabian@student.42wolfsburg.de>
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+109
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‎pandas/_libs/parsers.pyx

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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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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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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
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@@ -685,7 +685,7 @@ def __init__(
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# 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)
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elif isinstance(data, ma.MaskedArray):
688-
import numpy.ma.mrecords as mrecords
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from numpy.ma import mrecords
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# masked recarray
691691
if isinstance(data, mrecords.MaskedRecords):
@@ -8036,7 +8036,7 @@ def combine_first(self, other: DataFrame) -> DataFrame:
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1 0.0 3.0 1.0
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2 NaN 3.0 1.0
80388038
"""
8039-
import pandas.core.computation.expressions as expressions
8039+
from pandas.core.computation import expressions
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def combiner(x, y):
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mask = extract_array(isna(x))
@@ -8179,7 +8179,7 @@ def update(
81798179
1 2 500.0
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2 3 6.0
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"""
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import pandas.core.computation.expressions as expressions
8182+
from pandas.core.computation import expressions
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# TODO: Support other joins
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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.
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notna,
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)
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from pandas.core import nanops
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from pandas.core import (
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algorithms,
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nanops,
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sample,
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)
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from pandas.core._numba import executor
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import pandas.core.algorithms as algorithms
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from pandas.core.arrays import (
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BaseMaskedArray,
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BooleanArray,
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RangeIndex,
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)
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from pandas.core.internals.blocks import ensure_block_shape
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import pandas.core.sample as sample
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from pandas.core.series import Series
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from pandas.core.sorting import get_group_index_sorter
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from pandas.core.util.numba_ import (

‎pandas/core/groupby/grouper.py

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is_scalar,
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)
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import pandas.core.algorithms as algorithms
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from pandas.core import algorithms
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from pandas.core.arrays import (
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Categorical,
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ExtensionArray,

‎pandas/core/internals/blocks.py

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na_value_for_dtype,
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)
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from pandas.core import missing
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import pandas.core.algorithms as algos
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from pandas.core.array_algos.putmask import (
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extract_bool_array,
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from pandas.core.arrays.sparse import SparseDtype
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from pandas.core.base import PandasObject
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import pandas.core.common as com
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import pandas.core.computation.expressions as expressions
107+
from pandas.core.computation import expressions
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from pandas.core.construction import (
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ensure_wrapped_if_datetimelike,
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extract_array,
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)
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from pandas.core.indexers import check_setitem_lengths
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import pandas.core.missing as missing
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if TYPE_CHECKING:
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from pandas import (

‎pandas/core/internals/construction.py

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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._typing import (

‎pandas/core/nanops.py

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@@ -519,12 +519,12 @@ def nanany(
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Examples
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--------
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>>> import pandas.core.nanops as nanops
522+
>>> from pandas.core import nanops
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>>> s = pd.Series([1, 2])
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>>> nanops.nanany(s)
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True
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>>> import pandas.core.nanops as nanops
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>>> from pandas.core import nanops
528528
>>> s = pd.Series([np.nan])
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>>> nanops.nanany(s)
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False
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>>> import pandas.core.nanops as nanops
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>>> from pandas.core import nanops
569569
>>> s = pd.Series([1, 2, np.nan])
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>>> nanops.nanall(s)
571571
True
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>>> import pandas.core.nanops as nanops
573+
>>> from pandas.core import nanops
574574
>>> s = pd.Series([1, 0])
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>>> nanops.nanall(s)
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False
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>>> import pandas.core.nanops as nanops
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>>> from pandas.core import nanops
620620
>>> s = pd.Series([1, 2, np.nan])
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>>> nanops.nansum(s)
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3.0
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Examples
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>>> import pandas.core.nanops as nanops
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>>> from pandas.core import nanops
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>>> s = pd.Series([1, 2, np.nan])
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>>> nanops.nanmean(s)
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Examples
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>>> import pandas.core.nanops as nanops
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>>> from pandas.core import nanops
744744
>>> s = pd.Series([1, np.nan, 2, 2])
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>>> nanops.nanmedian(s)
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Examples
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>>> import pandas.core.nanops as nanops
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>>> from pandas.core import nanops
905905
>>> s = pd.Series([1, np.nan, 2, 3])
906906
>>> nanops.nanstd(s)
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Examples
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>>> import pandas.core.nanops as nanops
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>>> from pandas.core import nanops
952952
>>> s = pd.Series([1, np.nan, 2, 3])
953953
>>> nanops.nanvar(s)
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Examples
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--------
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)
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0.5773502691896258
@@ -1100,7 +1100,7 @@ def nanargmax(
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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)
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4
@@ -1146,7 +1146,7 @@ def nanargmin(
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Examples
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>>> 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)
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Examples
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--------
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)
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12881288
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Examples
12901290
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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)
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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)
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6.0

‎pandas/core/ops/array_ops.py

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notna,
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)
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import pandas.core.computation.expressions as expressions
50+
from pandas.core.computation import expressions
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from pandas.core.construction import ensure_wrapped_if_datetimelike
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from pandas.core.ops import (
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missing,

‎pandas/core/reshape/tile.py

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to_datetime,
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to_timedelta,
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)
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from pandas.core import nanops
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import pandas.core.algorithms as algos
47-
import pandas.core.nanops as nanops
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def cut(

‎pandas/core/strings/accessor.py

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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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AlignJoin,
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DtypeObj,

‎pandas/core/strings/object_array.py

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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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import pandas._libs.missing as libmissing
1616
import pandas._libs.ops as libops
1717
from pandas._typing import (

‎pandas/core/window/ewm.py

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)
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from pandas.core.dtypes.missing import isna
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import pandas.core.common as common # noqa: PDF018
30+
from pandas.core import common # noqa: PDF018
3131
from pandas.core.indexers.objects import (
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BaseIndexer,
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ExponentialMovingWindowIndexer,

‎pandas/io/excel/_odswriter.py

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cast,
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)
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import pandas._libs.json as json
13+
from pandas._libs import json
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from pandas._typing import (
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FilePath,
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StorageOptions,

‎pandas/io/excel/_xlsxwriter.py

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Any,
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)
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import pandas._libs.json as json
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from pandas._libs import json
99
from pandas._typing import (
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FilePath,
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StorageOptions,

‎pandas/io/json/_json.py

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

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