dtype = JSONDtype()
    __array_priority__ = 1000

    def __init__(self, values, dtype=None, copy=False):
        for val in values:
            if not isinstance(val, self.dtype.type):
                raise TypeError("All values must be of type " + str(self.dtype.type))
        self.data = values


            

Reported by Pylint.

                  dtype = JSONDtype()
    __array_priority__ = 1000

    def __init__(self, values, dtype=None, copy=False):
        for val in values:
            if not isinstance(val, self.dtype.type):
                raise TypeError("All values must be of type " + str(self.dtype.type))
        self.data = values


            

Reported by Pylint.

                      # self._values = self.values = self.data

    @classmethod
    def _from_sequence(cls, scalars, dtype=None, copy=False):
        return cls(scalars)

    @classmethod
    def _from_factorized(cls, values, original):
        return cls([UserDict(x) for x in values if x != ()])

            

Reported by Pylint.

                      # self._values = self.values = self.data

    @classmethod
    def _from_sequence(cls, scalars, dtype=None, copy=False):
        return cls(scalars)

    @classmethod
    def _from_factorized(cls, values, original):
        return cls([UserDict(x) for x in values if x != ()])

            

Reported by Pylint.

                      # self._values = self.values = self.data

    @classmethod
    def _from_sequence(cls, scalars, dtype=None, copy=False):
        return cls(scalars)

    @classmethod
    def _from_factorized(cls, values, original):
        return cls([UserDict(x) for x in values if x != ()])

            

Reported by Pylint.

                  def isna(self):
        return np.array([x == self.dtype.na_value for x in self.data], dtype=bool)

    def take(self, indexer, allow_fill=False, fill_value=None):
        # re-implement here, since NumPy has trouble setting
        # sized objects like UserDicts into scalar slots of
        # an ndarary.
        indexer = np.asarray(indexer)
        msg = (

            

Reported by Pylint.

                          return self
        elif isinstance(dtype, StringDtype):
            value = self.astype(str)  # numpy doesn'y like nested dicts
            return dtype.construct_array_type()._from_sequence(value, copy=False)

        return np.array([dict(x) for x in self], dtype=dtype, copy=copy)

    def unique(self):
        # Parent method doesn't work since np.array will try to infer

            

Reported by Pylint.

              

def make_data():
    # TODO: Use a regular dict. See _NDFrameIndexer._setitem_with_indexer
    return [
        UserDict(
            [
                (random.choice(string.ascii_letters), random.randint(0, 100))
                for _ in range(random.randint(0, 10))

            

Reported by Pylint.

              from pandas.api.types import is_bool_dtype


class JSONDtype(ExtensionDtype):
    type = abc.Mapping
    name = "json"
    na_value: Mapping[str, Any] = UserDict()

    @classmethod

            

Reported by Pylint.

                      return JSONArray


class JSONArray(ExtensionArray):
    dtype = JSONDtype()
    __array_priority__ = 1000

    def __init__(self, values, dtype=None, copy=False):
        for val in values:

            

Reported by Pylint.

              __setitem__.
"""
import numpy as np
import pytest

from pandas.errors import PerformanceWarning

from pandas import (
    DataFrame,

            

Reported by Pylint.

              import pandas._testing as tm


class TestDataFrameInsert:
    def test_insert(self):
        df = DataFrame(
            np.random.randn(5, 3), index=np.arange(5), columns=["c", "b", "a"]
        )


            

Reported by Pylint.

              

class TestDataFrameInsert:
    def test_insert(self):
        df = DataFrame(
            np.random.randn(5, 3), index=np.arange(5), columns=["c", "b", "a"]
        )

        df.insert(0, "foo", df["a"])

            

Reported by Pylint.

              

class TestDataFrameInsert:
    def test_insert(self):
        df = DataFrame(
            np.random.randn(5, 3), index=np.arange(5), columns=["c", "b", "a"]
        )

        df.insert(0, "foo", df["a"])

            

Reported by Pylint.

              
class TestDataFrameInsert:
    def test_insert(self):
        df = DataFrame(
            np.random.randn(5, 3), index=np.arange(5), columns=["c", "b", "a"]
        )

        df.insert(0, "foo", df["a"])
        tm.assert_index_equal(df.columns, Index(["foo", "c", "b", "a"]))

            

Reported by Pylint.

                      df.columns.name = "some_name"
        # preserve columns name field
        df.insert(0, "baz", df["c"])
        assert df.columns.name == "some_name"

    def test_insert_column_bug_4032(self):

        # GH#4032, inserting a column and renaming causing errors
        df = DataFrame({"b": [1.1, 2.2]})

            

Reported by Bandit.

                      df.insert(0, "baz", df["c"])
        assert df.columns.name == "some_name"

    def test_insert_column_bug_4032(self):

        # GH#4032, inserting a column and renaming causing errors
        df = DataFrame({"b": [1.1, 2.2]})

        df = df.rename(columns={})

            

Reported by Pylint.

                      df.insert(0, "baz", df["c"])
        assert df.columns.name == "some_name"

    def test_insert_column_bug_4032(self):

        # GH#4032, inserting a column and renaming causing errors
        df = DataFrame({"b": [1.1, 2.2]})

        df = df.rename(columns={})

            

Reported by Pylint.

                  def test_insert_column_bug_4032(self):

        # GH#4032, inserting a column and renaming causing errors
        df = DataFrame({"b": [1.1, 2.2]})

        df = df.rename(columns={})
        df.insert(0, "a", [1, 2])
        result = df.rename(columns={})


            

Reported by Pylint.

                      # GH#4032, inserting a column and renaming causing errors
        df = DataFrame({"b": [1.1, 2.2]})

        df = df.rename(columns={})
        df.insert(0, "a", [1, 2])
        result = df.rename(columns={})

        str(result)
        expected = DataFrame([[1, 1.1], [2, 2.2]], columns=["a", "b"])

            

Reported by Pylint.

              from io import StringIO

import numpy as np
import pytest

from pandas.errors import DtypeWarning

from pandas import (
    DataFrame,

            

Reported by Pylint.

              

@pytest.mark.parametrize("index_col", [0, "index"])
def test_read_chunksize_with_index(all_parsers, index_col):
    parser = all_parsers
    data = """index,A,B,C,D
foo,2,3,4,5
bar,7,8,9,10
baz,12,13,14,15

            

Reported by Pylint.

              

@pytest.mark.parametrize("index_col", [0, "index"])
def test_read_chunksize_with_index(all_parsers, index_col):
    parser = all_parsers
    data = """index,A,B,C,D
foo,2,3,4,5
bar,7,8,9,10
baz,12,13,14,15

            

Reported by Pylint.

              

@pytest.mark.parametrize("chunksize", [1.3, "foo", 0])
def test_read_chunksize_bad(all_parsers, chunksize):
    data = """index,A,B,C,D
foo,2,3,4,5
bar,7,8,9,10
baz,12,13,14,15
qux,12,13,14,15

            

Reported by Pylint.

              

@pytest.mark.parametrize("chunksize", [2, 8])
def test_read_chunksize_and_nrows(all_parsers, chunksize):
    # see gh-15755
    data = """index,A,B,C,D
foo,2,3,4,5
bar,7,8,9,10
baz,12,13,14,15

            

Reported by Pylint.

                      tm.assert_frame_equal(concat(reader), expected)


def test_read_chunksize_and_nrows_changing_size(all_parsers):
    data = """index,A,B,C,D
foo,2,3,4,5
bar,7,8,9,10
baz,12,13,14,15
qux,12,13,14,15

            

Reported by Pylint.

                          reader.get_chunk(size=3)


def test_get_chunk_passed_chunksize(all_parsers):
    parser = all_parsers
    data = """A,B,C
1,2,3
4,5,6
7,8,9

            

Reported by Pylint.

              

@pytest.mark.parametrize("kwargs", [{}, {"index_col": 0}])
def test_read_chunksize_compat(all_parsers, kwargs):
    # see gh-12185
    data = """index,A,B,C,D
foo,2,3,4,5
bar,7,8,9,10
baz,12,13,14,15

            

Reported by Pylint.

                      tm.assert_frame_equal(concat(reader), result)


def test_read_chunksize_jagged_names(all_parsers):
    # see gh-23509
    parser = all_parsers
    data = "\n".join(["0"] * 7 + [",".join(["0"] * 10)])

    expected = DataFrame([[0] + [np.nan] * 9] * 7 + [[0] * 10])

            

Reported by Pylint.

                  tm.assert_frame_equal(result, expected)


def test_chunk_begins_with_newline_whitespace(all_parsers):
    # see gh-10022
    parser = all_parsers
    data = "\n hello\nworld\n"

    result = parser.read_csv(StringIO(data), header=None)

            

Reported by Pylint.

              import numpy as np
import pytest

from pandas import (
    Series,
    Timestamp,
)
import pandas._testing as tm


            

Reported by Pylint.

              import numpy as np
import pytest

from pandas import (
    Series,
    Timestamp,
)
import pandas._testing as tm


            

Reported by Pylint.

              import pandas._testing as tm


class TestCopy:
    @pytest.mark.parametrize("deep", [None, False, True])
    def test_copy(self, deep):

        ser = Series(np.arange(10), dtype="float64")


            

Reported by Pylint.

              
class TestCopy:
    @pytest.mark.parametrize("deep", [None, False, True])
    def test_copy(self, deep):

        ser = Series(np.arange(10), dtype="float64")

        # default deep is True
        if deep is None:

            

Reported by Pylint.

              
class TestCopy:
    @pytest.mark.parametrize("deep", [None, False, True])
    def test_copy(self, deep):

        ser = Series(np.arange(10), dtype="float64")

        # default deep is True
        if deep is None:

            

Reported by Pylint.

              
        if deep is None or deep is True:
            # Did not modify original Series
            assert np.isnan(ser2[0])
            assert not np.isnan(ser[0])
        else:
            # we DID modify the original Series
            assert np.isnan(ser2[0])
            assert np.isnan(ser[0])

            

Reported by Bandit.

                      if deep is None or deep is True:
            # Did not modify original Series
            assert np.isnan(ser2[0])
            assert not np.isnan(ser[0])
        else:
            # we DID modify the original Series
            assert np.isnan(ser2[0])
            assert np.isnan(ser[0])


            

Reported by Bandit.

                          assert not np.isnan(ser[0])
        else:
            # we DID modify the original Series
            assert np.isnan(ser2[0])
            assert np.isnan(ser[0])

    @pytest.mark.parametrize("deep", [None, False, True])
    def test_copy_tzaware(self, deep):
        # GH#11794

            

Reported by Bandit.

                      else:
            # we DID modify the original Series
            assert np.isnan(ser2[0])
            assert np.isnan(ser[0])

    @pytest.mark.parametrize("deep", [None, False, True])
    def test_copy_tzaware(self, deep):
        # GH#11794
        # copy of tz-aware

            

Reported by Bandit.

                          assert np.isnan(ser[0])

    @pytest.mark.parametrize("deep", [None, False, True])
    def test_copy_tzaware(self, deep):
        # GH#11794
        # copy of tz-aware
        expected = Series([Timestamp("2012/01/01", tz="UTC")])
        expected2 = Series([Timestamp("1999/01/01", tz="UTC")])


            

Reported by Pylint.

                  deepcopy,
)

import pytest

from pandas import MultiIndex
import pandas._testing as tm



            

Reported by Pylint.

              import pandas._testing as tm


def assert_multiindex_copied(copy, original):
    # Levels should be (at least, shallow copied)
    tm.assert_copy(copy.levels, original.levels)
    tm.assert_almost_equal(copy.codes, original.codes)

    # Labels doesn't matter which way copied

            

Reported by Pylint.

              

def test_shallow_copy(idx):
    i_copy = idx._view()

    assert_multiindex_copied(i_copy, idx)


def test_view(idx):

            

Reported by Pylint.

              from copy import (
    copy,
    deepcopy,
)

import pytest

from pandas import MultiIndex
import pandas._testing as tm

            

Reported by Pylint.

              import pandas._testing as tm


def assert_multiindex_copied(copy, original):
    # Levels should be (at least, shallow copied)
    tm.assert_copy(copy.levels, original.levels)
    tm.assert_almost_equal(copy.codes, original.codes)

    # Labels doesn't matter which way copied

            

Reported by Pylint.

              
    # Labels doesn't matter which way copied
    tm.assert_almost_equal(copy.codes, original.codes)
    assert copy.codes is not original.codes

    # Names doesn't matter which way copied
    assert copy.names == original.names
    assert copy.names is not original.names


            

Reported by Bandit.

                  assert copy.codes is not original.codes

    # Names doesn't matter which way copied
    assert copy.names == original.names
    assert copy.names is not original.names

    # Sort order should be copied
    assert copy.sortorder == original.sortorder


            

Reported by Bandit.

              
    # Names doesn't matter which way copied
    assert copy.names == original.names
    assert copy.names is not original.names

    # Sort order should be copied
    assert copy.sortorder == original.sortorder



            

Reported by Bandit.

                  assert copy.names is not original.names

    # Sort order should be copied
    assert copy.sortorder == original.sortorder


def test_copy(idx):
    i_copy = idx.copy()


            

Reported by Bandit.

                  assert copy.sortorder == original.sortorder


def test_copy(idx):
    i_copy = idx.copy()

    assert_multiindex_copied(i_copy, idx)



            

Reported by Pylint.

                  StringIO,
)

import pytest

from pandas.errors import ParserError

from pandas import (
    DataFrame,

            

Reported by Pylint.

              import pandas._testing as tm


def test_default_separator(python_parser_only):
    # see gh-17333
    #
    # csv.Sniffer in Python treats "o" as separator.
    data = "aob\n1o2\n3o4"
    parser = python_parser_only

            

Reported by Pylint.

              

@pytest.mark.parametrize("skipfooter", ["foo", 1.5, True])
def test_invalid_skipfooter_non_int(python_parser_only, skipfooter):
    # see gh-15925 (comment)
    data = "a\n1\n2"
    parser = python_parser_only
    msg = "skipfooter must be an integer"


            

Reported by Pylint.

                      parser.read_csv(StringIO(data), skipfooter=skipfooter)


def test_invalid_skipfooter_negative(python_parser_only):
    # see gh-15925 (comment)
    data = "a\n1\n2"
    parser = python_parser_only
    msg = "skipfooter cannot be negative"


            

Reported by Pylint.

              

@pytest.mark.parametrize("kwargs", [{"sep": None}, {"delimiter": "|"}])
def test_sniff_delimiter(python_parser_only, kwargs):
    data = """index|A|B|C
foo|1|2|3
bar|4|5|6
baz|7|8|9
"""

            

Reported by Pylint.

                  tm.assert_frame_equal(result, expected)


def test_sniff_delimiter_comment(python_parser_only):
    data = """# comment line
index|A|B|C
# comment line
foo|1|2|3 # ignore | this
bar|4|5|6

            

Reported by Pylint.

              

@pytest.mark.parametrize("encoding", [None, "utf-8"])
def test_sniff_delimiter_encoding(python_parser_only, encoding):
    parser = python_parser_only
    data = """ignore this
ignore this too
index|A|B|C
foo|1|2|3

            

Reported by Pylint.

              """

    if encoding is not None:
        from io import TextIOWrapper

        data = data.encode(encoding)
        data = BytesIO(data)
        data = TextIOWrapper(data, encoding=encoding)
    else:

            

Reported by Pylint.

                  tm.assert_frame_equal(result, expected)


def test_single_line(python_parser_only):
    # see gh-6607: sniff separator
    parser = python_parser_only
    result = parser.read_csv(StringIO("1,2"), names=["a", "b"], header=None, sep=None)

    expected = DataFrame({"a": [1], "b": [2]})

            

Reported by Pylint.

              

@pytest.mark.parametrize("kwargs", [{"skipfooter": 2}, {"nrows": 3}])
def test_skipfooter(python_parser_only, kwargs):
    # see gh-6607
    data = """A,B,C
1,2,3
4,5,6
7,8,9

            

Reported by Pylint.

              import re

import pytest

from pandas._libs.tslibs import (
    Timedelta,
    offsets,
    to_offset,
)

            

Reported by Pylint.

              
import pytest

from pandas._libs.tslibs import (
    Timedelta,
    offsets,
    to_offset,
)


            

Reported by Pylint.

              import re

import pytest

from pandas._libs.tslibs import (
    Timedelta,
    offsets,
    to_offset,
)

            

Reported by Pylint.

                      ("2SM-16", offsets.SemiMonthEnd(2, day_of_month=16)),
        ("2SMS-14", offsets.SemiMonthBegin(2, day_of_month=14)),
        ("2SMS-15", offsets.SemiMonthBegin(2)),
    ],
)
def test_to_offset(freq_input, expected):
    result = to_offset(freq_input)
    assert result == expected


            

Reported by Pylint.

              )
def test_to_offset(freq_input, expected):
    result = to_offset(freq_input)
    assert result == expected


@pytest.mark.parametrize(
    "freqstr,expected", [("-1S", -1), ("-2SM", -2), ("-1SMS", -1), ("-5min10s", -310)]
)

            

Reported by Bandit.

              
@pytest.mark.parametrize(
    "freqstr,expected", [("-1S", -1), ("-2SM", -2), ("-1SMS", -1), ("-5min10s", -310)]
)
def test_to_offset_negative(freqstr, expected):
    result = to_offset(freqstr)
    assert result.n == expected



            

Reported by Pylint.

              )
def test_to_offset_negative(freqstr, expected):
    result = to_offset(freqstr)
    assert result.n == expected


@pytest.mark.parametrize(
    "freqstr",
    [

            

Reported by Bandit.

                      "SMS-BYR",
        "BSMS",
        "SMS--2",
    ],
)
def test_to_offset_invalid(freqstr):
    # see gh-13930

    # We escape string because some of our

            

Reported by Pylint.

                      to_offset(freqstr)


def test_to_offset_no_evaluate():
    msg = str(("", ""))
    with pytest.raises(TypeError, match=msg):
        to_offset(("", ""))



            

Reported by Pylint.

                      to_offset(("", ""))


def test_to_offset_tuple_unsupported():
    with pytest.raises(TypeError, match="pass as a string instead"):
        to_offset((5, "T"))


@pytest.mark.parametrize(

            

Reported by Pylint.

              import numpy as np
import pytest

from pandas._libs.tslibs import IncompatibleFrequency

from pandas import (
    Index,
    PeriodIndex,
    period_range,

            

Reported by Pylint.

                  def test_join_outer_indexer(self):
        pi = period_range("1/1/2000", "1/20/2000", freq="D")

        result = pi._outer_indexer(pi)
        tm.assert_extension_array_equal(result[0], pi._values)
        tm.assert_numpy_array_equal(result[1], np.arange(len(pi), dtype=np.intp))
        tm.assert_numpy_array_equal(result[2], np.arange(len(pi), dtype=np.intp))

    def test_joins(self, join_type):

            

Reported by Pylint.

                      pi = period_range("1/1/2000", "1/20/2000", freq="D")

        result = pi._outer_indexer(pi)
        tm.assert_extension_array_equal(result[0], pi._values)
        tm.assert_numpy_array_equal(result[1], np.arange(len(pi), dtype=np.intp))
        tm.assert_numpy_array_equal(result[2], np.arange(len(pi), dtype=np.intp))

    def test_joins(self, join_type):
        index = period_range("1/1/2000", "1/20/2000", freq="D")

            

Reported by Pylint.

              import numpy as np
import pytest

from pandas._libs.tslibs import IncompatibleFrequency

from pandas import (
    Index,
    PeriodIndex,
    period_range,

            

Reported by Pylint.

              import pandas._testing as tm


class TestJoin:
    def test_join_outer_indexer(self):
        pi = period_range("1/1/2000", "1/20/2000", freq="D")

        result = pi._outer_indexer(pi)
        tm.assert_extension_array_equal(result[0], pi._values)

            

Reported by Pylint.

              

class TestJoin:
    def test_join_outer_indexer(self):
        pi = period_range("1/1/2000", "1/20/2000", freq="D")

        result = pi._outer_indexer(pi)
        tm.assert_extension_array_equal(result[0], pi._values)
        tm.assert_numpy_array_equal(result[1], np.arange(len(pi), dtype=np.intp))

            

Reported by Pylint.

              

class TestJoin:
    def test_join_outer_indexer(self):
        pi = period_range("1/1/2000", "1/20/2000", freq="D")

        result = pi._outer_indexer(pi)
        tm.assert_extension_array_equal(result[0], pi._values)
        tm.assert_numpy_array_equal(result[1], np.arange(len(pi), dtype=np.intp))

            

Reported by Pylint.

              
class TestJoin:
    def test_join_outer_indexer(self):
        pi = period_range("1/1/2000", "1/20/2000", freq="D")

        result = pi._outer_indexer(pi)
        tm.assert_extension_array_equal(result[0], pi._values)
        tm.assert_numpy_array_equal(result[1], np.arange(len(pi), dtype=np.intp))
        tm.assert_numpy_array_equal(result[2], np.arange(len(pi), dtype=np.intp))

            

Reported by Pylint.

                      tm.assert_numpy_array_equal(result[1], np.arange(len(pi), dtype=np.intp))
        tm.assert_numpy_array_equal(result[2], np.arange(len(pi), dtype=np.intp))

    def test_joins(self, join_type):
        index = period_range("1/1/2000", "1/20/2000", freq="D")

        joined = index.join(index[:-5], how=join_type)

        assert isinstance(joined, PeriodIndex)

            

Reported by Pylint.

                      tm.assert_numpy_array_equal(result[1], np.arange(len(pi), dtype=np.intp))
        tm.assert_numpy_array_equal(result[2], np.arange(len(pi), dtype=np.intp))

    def test_joins(self, join_type):
        index = period_range("1/1/2000", "1/20/2000", freq="D")

        joined = index.join(index[:-5], how=join_type)

        assert isinstance(joined, PeriodIndex)

            

Reported by Pylint.

              import pytest

from pandas import (
    Index,
    Series,
    date_range,
)
import pandas._testing as tm


            

Reported by Pylint.

                      tm.assert_series_equal(ser, expected)

        # PeriodDtype
        pi = dti.tz_localize(None).to_period("D")
        ser = Series(pi)

        expected = ser[:2]
        del ser[2]
        assert ser.dtype == pi.dtype

            

Reported by Pylint.

                      tm.assert_series_equal(ser, expected)

        # PeriodDtype
        pi = dti.tz_localize(None).to_period("D")
        ser = Series(pi)

        expected = ser[:2]
        del ser[2]
        assert ser.dtype == pi.dtype

            

Reported by Pylint.

              
        expected = ser[[0, 2]]
        del ser[1]
        assert ser.dtype == dti.dtype
        tm.assert_series_equal(ser, expected)

        # PeriodDtype
        pi = dti.tz_localize(None).to_period("D")
        ser = Series(pi)

            

Reported by Pylint.

              import pytest

from pandas import (
    Index,
    Series,
    date_range,
)
import pandas._testing as tm


            

Reported by Pylint.

              import pandas._testing as tm


class TestSeriesDelItem:
    def test_delitem(self):
        # GH#5542
        # should delete the item inplace
        s = Series(range(5))
        del s[0]

            

Reported by Pylint.

              

class TestSeriesDelItem:
    def test_delitem(self):
        # GH#5542
        # should delete the item inplace
        s = Series(range(5))
        del s[0]


            

Reported by Pylint.

              

class TestSeriesDelItem:
    def test_delitem(self):
        # GH#5542
        # should delete the item inplace
        s = Series(range(5))
        del s[0]


            

Reported by Pylint.

                  def test_delitem(self):
        # GH#5542
        # should delete the item inplace
        s = Series(range(5))
        del s[0]

        expected = Series(range(1, 5), index=range(1, 5))
        tm.assert_series_equal(s, expected)


            

Reported by Pylint.

                      tm.assert_series_equal(s, expected)

        # only 1 left, del, add, del
        s = Series(1)
        del s[0]
        tm.assert_series_equal(s, Series(dtype="int64", index=Index([], dtype="int64")))
        s[0] = 1
        tm.assert_series_equal(s, Series(1))
        del s[0]

            

Reported by Pylint.

              import pytest

import pandas as pd
import pandas._testing as tm
from pandas.tests.io.pytables.common import ensure_clean_path

tables = pytest.importorskip("tables")



            

Reported by Pylint.

                  Was introduced for regression-testing issue 11188.
    """

    def test_read_complete(self, pytables_hdf5_file):
        path, objname, df = pytables_hdf5_file
        result = pd.read_hdf(path, key=objname)
        expected = df
        tm.assert_frame_equal(result, expected)


            

Reported by Pylint.

                      expected = df
        tm.assert_frame_equal(result, expected)

    def test_read_with_start(self, pytables_hdf5_file):
        path, objname, df = pytables_hdf5_file
        # This is a regression test for pandas-dev/pandas/issues/11188
        result = pd.read_hdf(path, key=objname, start=1)
        expected = df[1:].reset_index(drop=True)
        tm.assert_frame_equal(result, expected)

            

Reported by Pylint.

                      expected = df[1:].reset_index(drop=True)
        tm.assert_frame_equal(result, expected)

    def test_read_with_stop(self, pytables_hdf5_file):
        path, objname, df = pytables_hdf5_file
        # This is a regression test for pandas-dev/pandas/issues/11188
        result = pd.read_hdf(path, key=objname, stop=1)
        expected = df[:1].reset_index(drop=True)
        tm.assert_frame_equal(result, expected)

            

Reported by Pylint.

                      expected = df[:1].reset_index(drop=True)
        tm.assert_frame_equal(result, expected)

    def test_read_with_startstop(self, pytables_hdf5_file):
        path, objname, df = pytables_hdf5_file
        # This is a regression test for pandas-dev/pandas/issues/11188
        result = pd.read_hdf(path, key=objname, start=1, stop=2)
        expected = df[1:2].reset_index(drop=True)
        tm.assert_frame_equal(result, expected)

            

Reported by Pylint.

              import pytest

import pandas as pd
import pandas._testing as tm
from pandas.tests.io.pytables.common import ensure_clean_path

tables = pytest.importorskip("tables")



            

Reported by Pylint.

                      "c2": tables.Int64Col(pos=2),
    }

    t0 = 1_561_105_000.0

    testsamples = [
        {"c0": t0, "c1": "aaaaa", "c2": 1},
        {"c0": t0 + 1, "c1": "bbbbb", "c2": 2},
        {"c0": t0 + 2, "c1": "ccccc", "c2": 10 ** 5},

            

Reported by Pylint.

              
    with ensure_clean_path("written_with_pytables.h5") as path:
        # The `ensure_clean_path` context mgr removes the temp file upon exit.
        with tables.open_file(path, mode="w") as f:
            t = f.create_table("/", name=objname, description=table_schema)
            for sample in testsamples:
                for key, value in sample.items():
                    t.row[key] = value
                t.row.append()

            

Reported by Pylint.

                  with ensure_clean_path("written_with_pytables.h5") as path:
        # The `ensure_clean_path` context mgr removes the temp file upon exit.
        with tables.open_file(path, mode="w") as f:
            t = f.create_table("/", name=objname, description=table_schema)
            for sample in testsamples:
                for key, value in sample.items():
                    t.row[key] = value
                t.row.append()


            

Reported by Pylint.

                  Was introduced for regression-testing issue 11188.
    """

    def test_read_complete(self, pytables_hdf5_file):
        path, objname, df = pytables_hdf5_file
        result = pd.read_hdf(path, key=objname)
        expected = df
        tm.assert_frame_equal(result, expected)


            

Reported by Pylint.