import numpy as np
import pytest

import pandas.util._test_decorators as td

import pandas as pd
from pandas import (
    DataFrame,
    Index,

            

Reported by Pylint.

                      # see gh-10553
        unpickled = tm.round_trip_pickle(df)
        tm.assert_frame_equal(df, unpickled)
        assert df._metadata == unpickled._metadata
        assert df.testattr == unpickled.testattr

    def test_indexing_sliced(self):
        # GH 11559
        df = tm.SubclassedDataFrame(

            

Reported by Pylint.

                      # see gh-10553
        unpickled = tm.round_trip_pickle(df)
        tm.assert_frame_equal(df, unpickled)
        assert df._metadata == unpickled._metadata
        assert df.testattr == unpickled.testattr

    def test_indexing_sliced(self):
        # GH 11559
        df = tm.SubclassedDataFrame(

            

Reported by Pylint.

                              return self.i_dont_exist

        with pytest.raises(AttributeError, match=".*i_dont_exist.*"):
            A().bar

    def test_subclass_align(self):
        # GH 12983
        df1 = tm.SubclassedDataFrame(
            {"a": [1, 3, 5], "b": [1, 3, 5]}, index=list("ACE")

            

Reported by Pylint.

                          columns=["first", "last", "variable", "value"],
        )

        df.apply(lambda x: check_row_subclass(x))
        df.apply(lambda x: check_row_subclass(x), axis=1)

        expected = tm.SubclassedDataFrame(
            [
                ["John", "Doe", "height", 6.0],

            

Reported by Pylint.

                      )

        df.apply(lambda x: check_row_subclass(x))
        df.apply(lambda x: check_row_subclass(x), axis=1)

        expected = tm.SubclassedDataFrame(
            [
                ["John", "Doe", "height", 6.0],
                ["Mary", "Bo", "height", 6.5],

            

Reported by Pylint.

                          columns=["first", "last", "variable", "value"],
        )

        result = df.apply(lambda x: stretch(x), axis=1)
        assert isinstance(result, tm.SubclassedDataFrame)
        tm.assert_frame_equal(result, expected)

        expected = tm.SubclassedDataFrame([[1, 2, 3], [1, 2, 3], [1, 2, 3], [1, 2, 3]])


            

Reported by Pylint.

              import numpy as np
import pytest

import pandas.util._test_decorators as td

import pandas as pd
from pandas import (
    DataFrame,
    Index,

            

Reported by Pylint.

              import pandas._testing as tm


class TestDataFrameSubclassing:
    def test_frame_subclassing_and_slicing(self):
        # Subclass frame and ensure it returns the right class on slicing it
        # In reference to PR 9632

        class CustomSeries(Series):

            

Reported by Pylint.

              import pandas._testing as tm


class TestDataFrameSubclassing:
    def test_frame_subclassing_and_slicing(self):
        # Subclass frame and ensure it returns the right class on slicing it
        # In reference to PR 9632

        class CustomSeries(Series):

            

Reported by Pylint.

              
import numpy as np

from pandas._libs import (
    lib,
    reduction as libreduction,
)
from pandas._typing import (
    ArrayLike,

            

Reported by Pylint.

              
import numpy as np

from pandas._libs import (
    lib,
    reduction as libreduction,
)
from pandas._typing import (
    ArrayLike,

            

Reported by Pylint.

              from pandas.plotting import boxplot_frame_groupby

NamedAgg = namedtuple("NamedAgg", ["column", "aggfunc"])
# TODO(typing) the return value on this callable should be any *scalar*.
AggScalar = Union[str, Callable[..., Any]]
# TODO: validate types on ScalarResult and move to _typing
# Blocked from using by https://github.com/python/mypy/issues/1484
# See note at _mangle_lambda_list
ScalarResult = TypeVar("ScalarResult")

            

Reported by Pylint.

              NamedAgg = namedtuple("NamedAgg", ["column", "aggfunc"])
# TODO(typing) the return value on this callable should be any *scalar*.
AggScalar = Union[str, Callable[..., Any]]
# TODO: validate types on ScalarResult and move to _typing
# Blocked from using by https://github.com/python/mypy/issues/1484
# See note at _mangle_lambda_list
ScalarResult = TypeVar("ScalarResult")



            

Reported by Pylint.

                  """

    def prop(self):
        return self._make_wrapper(name)

    parent_method = getattr(klass, name)
    prop.__doc__ = parent_method.__doc__ or ""
    prop.__name__ = name
    return property(prop)

            

Reported by Pylint.

                      return super().apply(func, *args, **kwargs)

    @doc(_agg_template, examples=_agg_examples_doc, klass="Series")
    def aggregate(self, func=None, *args, engine=None, engine_kwargs=None, **kwargs):

        if maybe_use_numba(engine):
            with group_selection_context(self):
                data = self._selected_obj
            result, index = self._aggregate_with_numba(

            

Reported by Pylint.

                      return super().apply(func, *args, **kwargs)

    @doc(_agg_template, examples=_agg_examples_doc, klass="Series")
    def aggregate(self, func=None, *args, engine=None, engine_kwargs=None, **kwargs):

        if maybe_use_numba(engine):
            with group_selection_context(self):
                data = self._selected_obj
            result, index = self._aggregate_with_numba(

            

Reported by Pylint.

                          result, index = self._aggregate_with_numba(
                data.to_frame(), func, *args, engine_kwargs=engine_kwargs, **kwargs
            )
            return self.obj._constructor(result.ravel(), index=index, name=data.name)

        relabeling = func is None
        columns = None
        if relabeling:
            columns, func = validate_func_kwargs(kwargs)

            

Reported by Pylint.

                          try:
                return self._python_agg_general(func, *args, **kwargs)
            except KeyError:
                # TODO: KeyError is raised in _python_agg_general,
                #  see test_groupby.test_basic
                result = self._aggregate_named(func, *args, **kwargs)

                index = Index(sorted(result), name=self.grouper.names[0])
                return create_series_with_explicit_dtype(

            

Reported by Pylint.

                          return res_df  # type: ignore[return-value]

        indexed_output = {key.position: val for key, val in results.items()}
        output = self.obj._constructor_expanddim(indexed_output, index=None)
        output.columns = Index(key.label for key in results)

        output = self._reindex_output(output)
        return output


            

Reported by Pylint.

              from string import ascii_letters as letters

import numpy as np
import pytest

import pandas.util._test_decorators as td

import pandas as pd
from pandas import (

            

Reported by Pylint.

              
def random_text(nobs=100):
    df = []
    for i in range(nobs):
        idx = np.random.randint(len(letters), size=2)
        idx.sort()

        df.append([letters[idx[0] : idx[1]]])


            

Reported by Pylint.

                          df["cc"] = 0.0

            # caches a reference to the 'bb' series
            df["bb"]

            # repr machinery triggers consolidation
            repr(df)

            # Assignment to wrong series

            

Reported by Pylint.

              
            # Assignment to wrong series
            df["bb"].iloc[0] = 0.17
            df._clear_item_cache()
            tm.assert_almost_equal(df["bb"][0], 0.17)

    @pytest.mark.parametrize("do_ref", [True, False])
    def test_setitem_cache_updating(self, do_ref):
        # GH 5424

            

Reported by Pylint.

              
        # ref the cache
        if do_ref:
            df.loc[0, "c"]

        # set it
        df.loc[7, "c"] = 1

        assert df.loc[0, "c"] == 0.0

            

Reported by Pylint.

                      # loop through df to update out
        six = Timestamp("5/7/2014")
        eix = Timestamp("5/9/2014")
        for ix, row in df.iterrows():
            out.loc[six:eix, row["C"]] = out.loc[six:eix, row["C"]] + row["D"]

        tm.assert_frame_equal(out, expected)
        tm.assert_series_equal(out["A"], expected["A"])


            

Reported by Pylint.

                      df = DataFrame([[1, 2], [3, 4]], index=["a", "b"], columns=["A", "B"])
        ser = df["A"]

        assert "A" in df._item_cache

        # Adding a new entry to ser swaps in a new array, so "A" needs to
        #  be removed from df._item_cache
        ser["c"] = 5
        assert len(ser) == 3

            

Reported by Pylint.

                      #  be removed from df._item_cache
        ser["c"] = 5
        assert len(ser) == 3
        assert "A" not in df._item_cache
        assert df["A"] is not ser
        assert len(df["A"]) == 2


class TestChaining:

            

Reported by Pylint.

                      # work with the chain
        expected = DataFrame([[-5, 1], [-6, 3]], columns=list("AB"))
        df = DataFrame(np.arange(4).reshape(2, 2), columns=list("AB"), dtype="int64")
        assert df._is_copy is None

        df["A"][0] = -5
        df["A"][1] = -6
        tm.assert_frame_equal(df, expected)


            

Reported by Pylint.

                              "B": np.array(np.arange(2, 4), dtype=np.float64),
            }
        )
        assert df._is_copy is None

        if not using_array_manager:
            with pytest.raises(com.SettingWithCopyError, match=msg):
                df["A"][0] = -5


            

Reported by Pylint.

              
import numpy as np

from pandas._libs import (
    Timestamp,
    algos as libalgos,
    internals as libinternals,
    lib,
    writers,

            

Reported by Pylint.

              
import numpy as np

from pandas._libs import (
    Timestamp,
    algos as libalgos,
    internals as libinternals,
    lib,
    writers,

            

Reported by Pylint.

              
import numpy as np

from pandas._libs import (
    Timestamp,
    algos as libalgos,
    internals as libinternals,
    lib,
    writers,

            

Reported by Pylint.

              
import numpy as np

from pandas._libs import (
    Timestamp,
    algos as libalgos,
    internals as libinternals,
    lib,
    writers,

            

Reported by Pylint.

                  lib,
    writers,
)
from pandas._libs.internals import BlockPlacement
from pandas._typing import (
    ArrayLike,
    DtypeObj,
    F,
    Shape,

            

Reported by Pylint.

                  lib,
    writers,
)
from pandas._libs.internals import BlockPlacement
from pandas._typing import (
    ArrayLike,
    DtypeObj,
    F,
    Shape,

            

Reported by Pylint.

                  @final
    @cache_readonly
    def _consolidate_key(self):
        return self._can_consolidate, self.dtype.name

    @property
    def is_view(self) -> bool:
        """return a boolean if I am possibly a view"""
        values = self.values

            

Reported by Pylint.

                      """
        dtype = self.dtype
        if isinstance(dtype, np.dtype):
            return dtype.kind not in ["b", "i", "u"]
        return dtype._can_hold_na

    @final
    @cache_readonly
    def is_categorical(self) -> bool:

            

Reported by Pylint.

                      dtype = self.dtype
        if isinstance(dtype, np.dtype):
            return dtype.kind not in ["b", "i", "u"]
        return dtype._can_hold_na

    @final
    @cache_readonly
    def is_categorical(self) -> bool:
        warnings.warn(

            

Reported by Pylint.

              
        # no need to downcast our float
        # unless indicated
        if downcast is None and self.dtype.kind in ["f", "m", "M"]:
            # TODO: complex?  more generally, self._can_hold_na?
            return blocks

        return extend_blocks([b.downcast(downcast) for b in blocks])


            

Reported by Pylint.

                  def copy_osx_pyobjc(text):
        """Copy string argument to clipboard"""
        text = _stringifyText(text)  # Converts non-str values to str.
        newStr = Foundation.NSString.stringWithString_(text).nsstring()
        newData = newStr.dataUsingEncoding_(Foundation.NSUTF8StringEncoding)
        board = AppKit.NSPasteboard.generalPasteboard()
        board.declareTypes_owner_([AppKit.NSStringPboardType], None)
        board.setData_forType_(newData, AppKit.NSStringPboardType)


            

Reported by Pylint.

                      """Copy string argument to clipboard"""
        text = _stringifyText(text)  # Converts non-str values to str.
        newStr = Foundation.NSString.stringWithString_(text).nsstring()
        newData = newStr.dataUsingEncoding_(Foundation.NSUTF8StringEncoding)
        board = AppKit.NSPasteboard.generalPasteboard()
        board.declareTypes_owner_([AppKit.NSStringPboardType], None)
        board.setData_forType_(newData, AppKit.NSStringPboardType)

    def paste_osx_pyobjc():

            

Reported by Pylint.

                      text = _stringifyText(text)  # Converts non-str values to str.
        newStr = Foundation.NSString.stringWithString_(text).nsstring()
        newData = newStr.dataUsingEncoding_(Foundation.NSUTF8StringEncoding)
        board = AppKit.NSPasteboard.generalPasteboard()
        board.declareTypes_owner_([AppKit.NSStringPboardType], None)
        board.setData_forType_(newData, AppKit.NSStringPboardType)

    def paste_osx_pyobjc():
        """Returns contents of clipboard"""

            

Reported by Pylint.

                      newStr = Foundation.NSString.stringWithString_(text).nsstring()
        newData = newStr.dataUsingEncoding_(Foundation.NSUTF8StringEncoding)
        board = AppKit.NSPasteboard.generalPasteboard()
        board.declareTypes_owner_([AppKit.NSStringPboardType], None)
        board.setData_forType_(newData, AppKit.NSStringPboardType)

    def paste_osx_pyobjc():
        """Returns contents of clipboard"""
        board = AppKit.NSPasteboard.generalPasteboard()

            

Reported by Pylint.

                      newData = newStr.dataUsingEncoding_(Foundation.NSUTF8StringEncoding)
        board = AppKit.NSPasteboard.generalPasteboard()
        board.declareTypes_owner_([AppKit.NSStringPboardType], None)
        board.setData_forType_(newData, AppKit.NSStringPboardType)

    def paste_osx_pyobjc():
        """Returns contents of clipboard"""
        board = AppKit.NSPasteboard.generalPasteboard()
        content = board.stringForType_(AppKit.NSStringPboardType)

            

Reported by Pylint.

              
    def paste_osx_pyobjc():
        """Returns contents of clipboard"""
        board = AppKit.NSPasteboard.generalPasteboard()
        content = board.stringForType_(AppKit.NSStringPboardType)
        return content

    return copy_osx_pyobjc, paste_osx_pyobjc


            

Reported by Pylint.

                  def paste_osx_pyobjc():
        """Returns contents of clipboard"""
        board = AppKit.NSPasteboard.generalPasteboard()
        content = board.stringForType_(AppKit.NSStringPboardType)
        return content

    return copy_osx_pyobjc, paste_osx_pyobjc



            

Reported by Pylint.

                      super().__setattr__("f", f)

    def __call__(self, *args):
        ret = self.f(*args)
        if not ret and get_errno():
            raise PyperclipWindowsException("Error calling " + self.f.__name__)
        return ret

    def __setattr__(self, key, value):

            

Reported by Pylint.

                  def __call__(self, *args):
        ret = self.f(*args)
        if not ret and get_errno():
            raise PyperclipWindowsException("Error calling " + self.f.__name__)
        return ret

    def __setattr__(self, key, value):
        setattr(self.f, key, value)


            

Reported by Pylint.

                      return ret

    def __setattr__(self, key, value):
        setattr(self.f, key, value)


def init_windows_clipboard():
    global HGLOBAL, LPVOID, DWORD, LPCSTR, INT
    global HWND, HINSTANCE, HMENU, BOOL, UINT, HANDLE

            

Reported by Pylint.

              import dateutil.tz
from dateutil.tz import tzutc
import numpy as np
import pytest
import pytz

from pandas.compat import PY310
from pandas.errors import OutOfBoundsDatetime


            

Reported by Pylint.

              from dateutil.tz import tzutc
import numpy as np
import pytest
import pytz

from pandas.compat import PY310
from pandas.errors import OutOfBoundsDatetime

from pandas import (

            

Reported by Pylint.

                              assert result.value == expected

            # with timezone
            for tz, offset in timezones:
                result = Timestamp(date_str, tz=tz)
                expected_tz = expected
                assert result.value == expected_tz

                # should preserve tz

            

Reported by Pylint.

                      assert result.value == Timestamp("2013-11-01 05:00").value
        expected = "Timestamp('2013-11-01 00:00:00-0500', tz='America/Chicago')"
        assert repr(result) == expected
        assert result == eval(repr(result))

        # This should be 2013-11-01 05:00 in UTC
        # converted to Tokyo tz (+09:00)
        result = Timestamp("2013-11-01 00:00:00-0500", tz="Asia/Tokyo")
        assert result.value == Timestamp("2013-11-01 05:00").value

            

Reported by Pylint.

                      assert result.value == Timestamp("2013-11-01 05:00").value
        expected = "Timestamp('2013-11-01 00:00:00-0500', tz='America/Chicago')"
        assert repr(result) == expected
        assert result == eval(repr(result))

        # This should be 2013-11-01 05:00 in UTC
        # converted to Tokyo tz (+09:00)
        result = Timestamp("2013-11-01 00:00:00-0500", tz="Asia/Tokyo")
        assert result.value == Timestamp("2013-11-01 05:00").value

            

Reported by Bandit.

                      assert result.value == Timestamp("2013-11-01 05:00").value
        expected = "Timestamp('2013-11-01 14:00:00+0900', tz='Asia/Tokyo')"
        assert repr(result) == expected
        assert result == eval(repr(result))

        # GH11708
        # This should be 2015-11-18 10:00 in UTC
        # converted to Asia/Katmandu
        result = Timestamp("2015-11-18 15:45:00+05:45", tz="Asia/Katmandu")

            

Reported by Pylint.

                      assert result.value == Timestamp("2013-11-01 05:00").value
        expected = "Timestamp('2013-11-01 14:00:00+0900', tz='Asia/Tokyo')"
        assert repr(result) == expected
        assert result == eval(repr(result))

        # GH11708
        # This should be 2015-11-18 10:00 in UTC
        # converted to Asia/Katmandu
        result = Timestamp("2015-11-18 15:45:00+05:45", tz="Asia/Katmandu")

            

Reported by Bandit.

                      assert result.value == Timestamp("2015-11-18 10:00").value
        expected = "Timestamp('2015-11-18 15:45:00+0545', tz='Asia/Katmandu')"
        assert repr(result) == expected
        assert result == eval(repr(result))

        # This should be 2015-11-18 10:00 in UTC
        # converted to Asia/Kolkata
        result = Timestamp("2015-11-18 15:30:00+05:30", tz="Asia/Kolkata")
        assert result.value == Timestamp("2015-11-18 10:00").value

            

Reported by Pylint.

                      assert result.value == Timestamp("2015-11-18 10:00").value
        expected = "Timestamp('2015-11-18 15:45:00+0545', tz='Asia/Katmandu')"
        assert repr(result) == expected
        assert result == eval(repr(result))

        # This should be 2015-11-18 10:00 in UTC
        # converted to Asia/Kolkata
        result = Timestamp("2015-11-18 15:30:00+05:30", tz="Asia/Kolkata")
        assert result.value == Timestamp("2015-11-18 10:00").value

            

Reported by Bandit.

                      assert result.value == Timestamp("2015-11-18 10:00").value
        expected = "Timestamp('2015-11-18 15:30:00+0530', tz='Asia/Kolkata')"
        assert repr(result) == expected
        assert result == eval(repr(result))

    def test_constructor_invalid(self):
        msg = "Cannot convert input"
        with pytest.raises(TypeError, match=msg):
            Timestamp(slice(2))

            

Reported by Pylint.

              import pydoc

import numpy as np
import pytest

import pandas.util._test_decorators as td
from pandas.util._test_decorators import (
    async_mark,
    skip_if_no,

            

Reported by Pylint.

                  async def test_tab_complete_warning(self, ip, frame_or_series):
        # GH 16409
        pytest.importorskip("IPython", minversion="6.0.0")
        from IPython.core.completer import provisionalcompleter

        if frame_or_series is DataFrame:
            code = "from pandas import DataFrame; obj = DataFrame()"
        else:
            code = "from pandas import Series; obj = Series(dtype=object)"

            

Reported by Pylint.

              
    def test_get_axis(self, float_frame):
        f = float_frame
        assert f._get_axis_number(0) == 0
        assert f._get_axis_number(1) == 1
        assert f._get_axis_number("index") == 0
        assert f._get_axis_number("rows") == 0
        assert f._get_axis_number("columns") == 1


            

Reported by Pylint.

                  def test_get_axis(self, float_frame):
        f = float_frame
        assert f._get_axis_number(0) == 0
        assert f._get_axis_number(1) == 1
        assert f._get_axis_number("index") == 0
        assert f._get_axis_number("rows") == 0
        assert f._get_axis_number("columns") == 1

        assert f._get_axis_name(0) == "index"

            

Reported by Pylint.

                      f = float_frame
        assert f._get_axis_number(0) == 0
        assert f._get_axis_number(1) == 1
        assert f._get_axis_number("index") == 0
        assert f._get_axis_number("rows") == 0
        assert f._get_axis_number("columns") == 1

        assert f._get_axis_name(0) == "index"
        assert f._get_axis_name(1) == "columns"

            

Reported by Pylint.

                      assert f._get_axis_number(0) == 0
        assert f._get_axis_number(1) == 1
        assert f._get_axis_number("index") == 0
        assert f._get_axis_number("rows") == 0
        assert f._get_axis_number("columns") == 1

        assert f._get_axis_name(0) == "index"
        assert f._get_axis_name(1) == "columns"
        assert f._get_axis_name("index") == "index"

            

Reported by Pylint.

                      assert f._get_axis_number(1) == 1
        assert f._get_axis_number("index") == 0
        assert f._get_axis_number("rows") == 0
        assert f._get_axis_number("columns") == 1

        assert f._get_axis_name(0) == "index"
        assert f._get_axis_name(1) == "columns"
        assert f._get_axis_name("index") == "index"
        assert f._get_axis_name("rows") == "index"

            

Reported by Pylint.

                      assert f._get_axis_number("rows") == 0
        assert f._get_axis_number("columns") == 1

        assert f._get_axis_name(0) == "index"
        assert f._get_axis_name(1) == "columns"
        assert f._get_axis_name("index") == "index"
        assert f._get_axis_name("rows") == "index"
        assert f._get_axis_name("columns") == "columns"


            

Reported by Pylint.

                      assert f._get_axis_number("columns") == 1

        assert f._get_axis_name(0) == "index"
        assert f._get_axis_name(1) == "columns"
        assert f._get_axis_name("index") == "index"
        assert f._get_axis_name("rows") == "index"
        assert f._get_axis_name("columns") == "columns"

        assert f._get_axis(0) is f.index

            

Reported by Pylint.

              
        assert f._get_axis_name(0) == "index"
        assert f._get_axis_name(1) == "columns"
        assert f._get_axis_name("index") == "index"
        assert f._get_axis_name("rows") == "index"
        assert f._get_axis_name("columns") == "columns"

        assert f._get_axis(0) is f.index
        assert f._get_axis(1) is f.columns

            

Reported by Pylint.

              import itertools

import numpy as np
import pytest

from pandas.compat import (
    IS64,
    is_platform_windows,
)

            

Reported by Pylint.

              
    def test_where_index_period(self):
        dti = pd.date_range("2016-01-01", periods=3, freq="QS")
        pi = dti.to_period("Q")

        cond = np.array([False, True, False])

        # Passinga  valid scalar
        value = pi[-1] + pi.freq * 10

            

Reported by Pylint.

              
    def test_where_index_period(self):
        dti = pd.date_range("2016-01-01", periods=3, freq="QS")
        pi = dti.to_period("Q")

        cond = np.array([False, True, False])

        # Passinga  valid scalar
        value = pi[-1] + pi.freq * 10

            

Reported by Pylint.

                      # check dtype explicitly for sure
        assert temp.dtype == expected_dtype

        # FIXME: dont leave commented-out
        # .loc works different rule, temporary disable
        # temp = original_series.copy()
        # temp.loc[1] = loc_value
        # tm.assert_series_equal(temp, expected_series)


            

Reported by Pylint.

                  )
    def test_insert_index_object(self, insert, coerced_val, coerced_dtype):
        obj = pd.Index(list("abcd"))
        assert obj.dtype == object

        exp = pd.Index(["a", coerced_val, "b", "c", "d"])
        self._assert_insert_conversion(obj, insert, exp, coerced_dtype)

    @pytest.mark.parametrize(

            

Reported by Pylint.

                      "insert_value",
        [pd.Timestamp("2012-01-01"), pd.Timestamp("2012-01-01", tz="Asia/Tokyo"), 1],
    )
    def test_insert_index_datetimes(self, request, fill_val, exp_dtype, insert_value):

        obj = pd.DatetimeIndex(
            ["2011-01-01", "2011-01-02", "2011-01-03", "2011-01-04"], tz=fill_val.tz
        )
        assert obj.dtype == exp_dtype

            

Reported by Pylint.

                      "insert_value",
        [pd.Timestamp("2012-01-01"), pd.Timestamp("2012-01-01", tz="Asia/Tokyo"), 1],
    )
    def test_insert_index_datetimes(self, request, fill_val, exp_dtype, insert_value):

        obj = pd.DatetimeIndex(
            ["2011-01-01", "2011-01-02", "2011-01-03", "2011-01-04"], tz=fill_val.tz
        )
        assert obj.dtype == exp_dtype

            

Reported by Pylint.

                          expected = obj.astype(object).insert(0, insert)
            tm.assert_index_equal(result, expected)

            # TODO: ATM inserting '2012-01-01 00:00:00' when we have obj.freq=="M"
            #  casts that string to Period[M], not clear that is desirable
            if not isinstance(insert, pd.Timestamp):
                # non-castable string
                result = obj.insert(0, str(insert))
                expected = obj.astype(object).insert(0, str(insert))

            

Reported by Pylint.

                              pd.Timestamp("2011-01-04"),
            ]
        )
        assert obj.dtype == "datetime64[ns]"
        cond = pd.Index([True, False, True, False])

        result = obj.where(cond, fill_val)
        expected = pd.DatetimeIndex([obj[0], fill_val, obj[2], fill_val])
        tm.assert_index_equal(result, expected)

            

Reported by Pylint.

                              pd.Timestamp("2011-01-04"),
            ]
        )
        assert obj.dtype == "datetime64[ns]"
        cond = pd.Index([True, False, True, False])

        msg = "Index\\(\\.\\.\\.\\) must be called with a collection of some kind"
        with pytest.raises(TypeError, match=msg):
            obj.where(cond, fill_val)

            

Reported by Pylint.

              from io import StringIO

import numpy as np
import pytest

import pandas as pd
from pandas import (
    DataFrame,
    Index,

            

Reported by Pylint.

                  grouped = df.groupby(["A", "B"], as_index=False)
    result = grouped.apply(len)
    expected = grouped.count().rename(columns={"C": np.nan}).drop(columns="D")
    # TODO: Use assert_frame_equal when column name is not np.nan (GH 36306)
    tm.assert_index_equal(result.index, expected.index)
    tm.assert_numpy_array_equal(result.values, expected.values)


def test_apply_frame_concat_series():

            

Reported by Pylint.

              
    df = DataFrame({"a": 1, "b": [datetime.now() for nn in range(10)]})

    def func_with_no_date(batch):
        return Series({"c": 2})

    def func_with_date(batch):
        return Series({"b": datetime(2015, 1, 1), "c": 2})


            

Reported by Pylint.

                  def func_with_no_date(batch):
        return Series({"c": 2})

    def func_with_date(batch):
        return Series({"b": datetime(2015, 1, 1), "c": 2})

    dfg_no_conversion = df.groupby(by=["a"]).apply(func_with_no_date)
    dfg_no_conversion_expected = DataFrame({"c": 2}, index=[1])
    dfg_no_conversion_expected.index.name = "a"

            

Reported by Pylint.

                  # values. Issue 9684.
    test_df = DataFrame({"groups": [0, 0, 1, 1], "random_vars": [8, 7, 4, 5]})

    def test_func(x):
        pass

    result = test_df.groupby("groups").apply(test_func)
    expected = DataFrame()
    tm.assert_frame_equal(result, expected)

            

Reported by Pylint.

              
def test_doctest_example2():
    # GH#42702 this fails if we cache_readonly Block.shape
    # TODO: more informative name
    df = DataFrame({"A": ["a", "a", "b"], "B": [1, 2, 3], "C": [4, 6, 5]})
    gb = df.groupby("A")
    result = gb[["B", "C"]].apply(lambda x: x.astype(float).max() - x.min())

    expected = DataFrame(

            

Reported by Pylint.

              from datetime import (
    date,
    datetime,
)
from io import StringIO

import numpy as np
import pytest


            

Reported by Pylint.

              from datetime import (
    date,
    datetime,
)
from io import StringIO

import numpy as np
import pytest


            

Reported by Pylint.

              import pandas._testing as tm


def test_apply_issues():
    # GH 5788

    s = """2011.05.16,00:00,1.40893
2011.05.16,01:00,1.40760
2011.05.16,02:00,1.40750

            

Reported by Pylint.

              def test_apply_issues():
    # GH 5788

    s = """2011.05.16,00:00,1.40893
2011.05.16,01:00,1.40760
2011.05.16,02:00,1.40750
2011.05.16,03:00,1.40649
2011.05.17,02:00,1.40893
2011.05.17,03:00,1.40760

            

Reported by Pylint.

              
import numpy as np

from pandas import (
    Categorical,
    DataFrame,
    Series,
)


            

Reported by Pylint.

                  Series,
)

from .pandas_vb_common import tm


class Dtypes:
    params = ["str", "string[python]", "string[pyarrow]"]
    param_names = ["dtype"]

            

Reported by Pylint.

              
    def setup(self, dtype):
        try:
            self.s = Series(tm.makeStringIndex(10 ** 5), dtype=dtype)
        except ImportError:
            raise NotImplementedError


class Construction:

            

Reported by Pylint.

                      try:
            self.s = Series(tm.makeStringIndex(10 ** 5), dtype=dtype)
        except ImportError:
            raise NotImplementedError


class Construction:

    params = ["str", "string"]

            

Reported by Pylint.

                  params = ["str", "string"]
    param_names = ["dtype"]

    def setup(self, dtype):
        self.series_arr = tm.rands_array(nchars=10, size=10 ** 5)
        self.frame_arr = self.series_arr.reshape((50_000, 2)).copy()

        # GH37371. Testing construction of string series/frames from ExtensionArrays
        self.series_cat_arr = Categorical(self.series_arr)

            

Reported by Pylint.

                  param_names = ["dtype"]

    def setup(self, dtype):
        self.series_arr = tm.rands_array(nchars=10, size=10 ** 5)
        self.frame_arr = self.series_arr.reshape((50_000, 2)).copy()

        # GH37371. Testing construction of string series/frames from ExtensionArrays
        self.series_cat_arr = Categorical(self.series_arr)
        self.frame_cat_arr = Categorical(self.frame_arr)

            

Reported by Pylint.

              
    def setup(self, dtype):
        self.series_arr = tm.rands_array(nchars=10, size=10 ** 5)
        self.frame_arr = self.series_arr.reshape((50_000, 2)).copy()

        # GH37371. Testing construction of string series/frames from ExtensionArrays
        self.series_cat_arr = Categorical(self.series_arr)
        self.frame_cat_arr = Categorical(self.frame_arr)


            

Reported by Pylint.

                      self.frame_arr = self.series_arr.reshape((50_000, 2)).copy()

        # GH37371. Testing construction of string series/frames from ExtensionArrays
        self.series_cat_arr = Categorical(self.series_arr)
        self.frame_cat_arr = Categorical(self.frame_arr)

    def time_series_construction(self, dtype):
        Series(self.series_arr, dtype=dtype)


            

Reported by Pylint.

              
        # GH37371. Testing construction of string series/frames from ExtensionArrays
        self.series_cat_arr = Categorical(self.series_arr)
        self.frame_cat_arr = Categorical(self.frame_arr)

    def time_series_construction(self, dtype):
        Series(self.series_arr, dtype=dtype)

    def peakmem_series_construction(self, dtype):

            

Reported by Pylint.

              

class Methods(Dtypes):
    def time_center(self, dtype):
        self.s.str.center(100)

    def time_count(self, dtype):
        self.s.str.count("A")


            

Reported by Pylint.