text: # -*- coding: utf-8 -*-
  
  import pytest
  
  from datetime import datetime, timedelta
  from decimal import Decimal
  from collections import defaultdict
  
  import pandas.util.testing as tm
  from pandas.core.dtypes.generic import ABCIndex
  from pandas.core.dtypes.common import is_unsigned_integer_dtype
  from pandas.core.indexes.api import Index, MultiIndex
  from pandas.tests.indexes.common import Base
  
  from pandas.compat import (range, lrange, lzip, u,
                             text_type, zip, PY3, PY35, PY36, StringIO)
  import math
  import operator
  import numpy as np
  
  from pandas import (period_range, date_range, Series,
                      DataFrame, Float64Index, Int64Index, UInt64Index,
                      CategoricalIndex, DatetimeIndex, TimedeltaIndex,
                      PeriodIndex, RangeIndex, isna)
  from pandas.core.index import _get_combined_index, ensure_index_from_sequences
  from pandas.util.testing import assert_almost_equal
  from pandas.compat.numpy import np_datetime64_compat
  
  import pandas.core.config as cf
  
  from pandas.core.indexes.datetimes import _to_m8
  
  import pandas as pd
  from pandas._libs.tslib import Timestamp
  
  
  class TestIndex(Base):
      _holder = Index
  
      def setup_method(self, method):
          self.indices = dict(unicodeIndex=tm.makeUnicodeIndex(100),
                              strIndex=tm.makeStringIndex(100),
                              dateIndex=tm.makeDateIndex(100),
                              periodIndex=tm.makePeriodIndex(100),
                              tdIndex=tm.makeTimedeltaIndex(100),
                              intIndex=tm.makeIntIndex(100),
                              uintIndex=tm.makeUIntIndex(100),
                              rangeIndex=tm.makeRangeIndex(100),
                              floatIndex=tm.makeFloatIndex(100),
                              boolIndex=Index([True, False]),
                              catIndex=tm.makeCategoricalIndex(100),
                              empty=Index([]),
                              tuples=MultiIndex.from_tuples(lzip(
                                  ['foo', 'bar', 'baz'], [1, 2, 3])),
                              repeats=Index([0, 0, 1, 1, 2, 2]))
          self.setup_indices()
  
      def create_index(self):
          return Index(list('abcde'))
  
      def generate_index_types(self, skip_index_keys=[]):
          """
          Return a generator of the various index types, leaving
          out the ones with a key in skip_index_keys
          """
          for key, index in self.indices.items():
              if key not in skip_index_keys:
                  yield key, index
  
      def test_can_hold_identifiers(self):
          index = self.create_index()
          key = index[0]
          assert index._can_hold_identifiers_and_holds_name(key) is True
  
      def test_new_axis(self):
          new_index = self.dateIndex[None, :]
          assert new_index.ndim == 2
          assert isinstance(new_index, np.ndarray)
  
      def test_copy_and_deepcopy(self, indices):
          super(TestIndex, self).test_copy_and_deepcopy(indices)
  
          new_copy2 = self.intIndex.copy(dtype=int)
          assert new_copy2.dtype.kind == 'i'
  
      @pytest.mark.parametrize("attr", ['strIndex', 'dateIndex'])
      def test_constructor_regular(self, attr):
          # regular instance creation
          index = getattr(self, attr)
          tm.assert_contains_all(index, index)
  
      def test_constructor_casting(self):
          # casting
          arr = np.array(self.strIndex)
          index = Index(arr)
          tm.assert_contains_all(arr, index)
          tm.assert_index_equal(self.strIndex, index)
  
      def test_constructor_copy(self):
          # copy
          arr = np.array(self.strIndex)
          index = Index(arr, copy=True, name='name')
          assert isinstance(index, Index)
          assert index.name == 'name'
          tm.assert_numpy_array_equal(arr, index.values)
          arr[0] = "SOMEBIGLONGSTRING"
          assert index[0] != "SOMEBIGLONGSTRING"
  
          # what to do here?
          # arr = np.array(5.)
          # pytest.raises(Exception, arr.view, Index)
  
      def test_constructor_corner(self):
          # corner case
          pytest.raises(TypeError, Index, 0)
  
      @pytest.mark.parametrize("index_vals", [
          [('A', 1), 'B'], ['B', ('A', 1)]])
      def test_construction_list_mixed_tuples(self, index_vals):
          # see gh-10697: if we are constructing from a mixed list of tuples,
          # make sure that we are independent of the sorting order.
          index = Index(index_vals)
          assert isinstance(index, Index)
          assert not isinstance(index, MultiIndex)
  
      @pytest.mark.parametrize('na_value', [None, np.nan])
      @pytest.mark.parametrize('vtype', [list, tuple, iter])
      def test_construction_list_tuples_nan(self, na_value, vtype):
          # GH 18505 : valid tuples containing NaN
          values = [(1, 'two'), (3., na_value)]
          result = Index(vtype(values))
          expected = MultiIndex.from_tuples(values)
          tm.assert_index_equal(result, expected)
  
      @pytest.mark.parametrize("cast_as_obj", [True, False])
      @pytest.mark.parametrize("index", [
          pd.date_range('2015-01-01 10:00', freq='D', periods=3,
                        tz='US/Eastern'),  # DTI with tz
          pd.date_range('2015-01-01 10:00', freq='D', periods=3),  # DTI no tz
          pd.timedelta_range('1 days', freq='D', periods=3),  # td
          pd.period_range('2015-01-01', freq='D', periods=3)  # period
      ])
      def test_constructor_from_index_dtlike(self, cast_as_obj, index):
          if cast_as_obj:
              result = pd.Index(index.astype(object))
          else:
              result = pd.Index(index)
  
          tm.assert_index_equal(result, index)
  
          if isinstance(index, pd.DatetimeIndex) and hasattr(index, 'tz'):
              assert result.tz == index.tz
  
      @pytest.mark.parametrize("index,has_tz", [
          (pd.date_range('2015-01-01 10:00', freq='D', periods=3,
                         tz='US/Eastern'), True),  # datetimetz
          (pd.timedelta_range('1 days', freq='D', periods=3), False),  # td
          (pd.period_range('2015-01-01', freq='D', periods=3), False)  # period
      ])
      def test_constructor_from_series_dtlike(self, index, has_tz):
          result = pd.Index(pd.Series(index))
          tm.assert_index_equal(result, index)
  
          if has_tz:
              assert result.tz == index.tz
  
      @pytest.mark.parametrize("klass", [Index, DatetimeIndex])
      def test_constructor_from_series(self, klass):
          expected = DatetimeIndex([Timestamp('20110101'), Timestamp('20120101'),
                                    Timestamp('20130101')])
          s = Series([Timestamp('20110101'), Timestamp('20120101'),
                      Timestamp('20130101')])
          result = klass(s)
          tm.assert_index_equal(result, expected)
  
      def test_constructor_from_series_freq(self):
          # GH 6273
          # create from a series, passing a freq
          dts = ['1-1-1990', '2-1-1990', '3-1-1990', '4-1-1990', '5-1-1990']
          expected = DatetimeIndex(dts, freq='MS')
  
          s = Series(pd.to_datetime(dts))
          result = DatetimeIndex(s, freq='MS')
  
          tm.assert_index_equal(result, expected)
  
      def test_constructor_from_frame_series_freq(self):
          # GH 6273
          # create from a series, passing a freq
          dts = ['1-1-1990', '2-1-1990', '3-1-1990', '4-1-1990', '5-1-1990']
          expected = DatetimeIndex(dts, freq='MS')
  
          df = pd.DataFrame(np.random.rand(5, 3))
          df['date'] = dts
          result = DatetimeIndex(df['date'], freq='MS')
  
          assert df['date'].dtype == object
          expected.name = 'date'
          tm.assert_index_equal(result, expected)
  
          expected = pd.Series(dts, name='date')
          tm.assert_series_equal(df['date'], expected)
  
          # GH 6274
          # infer freq of same
          freq = pd.infer_freq(df['date'])
          assert freq == 'MS'
  
      @pytest.mark.parametrize("array", [
          np.arange(5), np.array(['a', 'b', 'c']), date_range(
              '2000-01-01', periods=3).values
      ])
      def test_constructor_ndarray_like(self, array):
          # GH 5460#issuecomment-44474502
          # it should be possible to convert any object that satisfies the numpy
          # ndarray interface directly into an Index
          class ArrayLike(object):
              def __init__(self, array):
                  self.array = array
  
              def __array__(self, dtype=None):
                  return self.array
  
          expected = pd.Index(array)
          result = pd.Index(ArrayLike(array))
          tm.assert_index_equal(result, expected)
  
      @pytest.mark.parametrize('dtype', [
          int, 'int64', 'int32', 'int16', 'int8', 'uint64', 'uint32',
          'uint16', 'uint8'])
      def test_constructor_int_dtype_float(self, dtype):
          # GH 18400
          if is_unsigned_integer_dtype(dtype):
              index_type = UInt64Index
          else:
              index_type = Int64Index
  
          expected = index_type([0, 1, 2, 3])
          result = Index([0., 1., 2., 3.], dtype=dtype)
          tm.assert_index_equal(result, expected)
  
      def test_constructor_int_dtype_nan(self):
          # see gh-15187
          data = [np.nan]
          expected = Float64Index(data)
          result = Index(data, dtype='float')
          tm.assert_index_equal(result, expected)
  
      def test_droplevel(self, indices):
          # GH 21115
          if isinstance(indices, MultiIndex):
              # Tested separately in test_multi.py
              return
  
          assert indices.droplevel([]).equals(indices)
  
          for level in indices.name, [indices.name]:
              if isinstance(indices.name, tuple) and level is indices.name:
                  # GH 21121 : droplevel with tuple name
                  continue
              with pytest.raises(ValueError):
                  indices.droplevel(level)
  
          for level in 'wrong', ['wrong']:
              with pytest.raises(KeyError):
                  indices.droplevel(level)
  
      @pytest.mark.parametrize("dtype", ['int64', 'uint64'])
      def test_constructor_int_dtype_nan_raises(self, dtype):
          # see gh-15187
          data = [np.nan]
          msg = "cannot convert"
          with tm.assert_raises_regex(ValueError, msg):
              Index(data, dtype=dtype)
  
      @pytest.mark.parametrize("klass,dtype,na_val", [
          (pd.Float64Index, np.float64, np.nan),
          (pd.DatetimeIndex, 'datetime64[ns]', pd.NaT)
      ])
      def test_index_ctor_infer_nan_nat(self, klass, dtype, na_val):
          # GH 13467
          na_list = [na_val, na_val]
          expected = klass(na_list)
          assert expected.dtype == dtype
  
          result = Index(na_list)
          tm.assert_index_equal(result, expected)
  
          result = Index(np.array(na_list))
          tm.assert_index_equal(result, expected)
  
      @pytest.mark.parametrize("pos", [0, 1])
      @pytest.mark.parametrize("klass,dtype,ctor", [
          (pd.DatetimeIndex, 'datetime64[ns]', np.datetime64('nat')),
          (pd.TimedeltaIndex, 'timedelta64[ns]', np.timedelta64('nat'))
      ])
      def test_index_ctor_infer_nat_dt_like(self, pos, klass, dtype, ctor,
                                            nulls_fixture):
          expected = klass([pd.NaT, pd.NaT])
          assert expected.dtype == dtype
          data = [ctor]
          data.insert(pos, nulls_fixture)
  
          result = Index(data)
          tm.assert_index_equal(result, expected)
  
          result = Index(np.array(data, dtype=object))
          tm.assert_index_equal(result, expected)
  
      @pytest.mark.parametrize("swap_objs", [True, False])
      def test_index_ctor_nat_result(self, swap_objs):
          # mixed np.datetime64/timedelta64 nat results in object
          data = [np.datetime64('nat'), np.timedelta64('nat')]
          if swap_objs:
              data = data[::-1]
  
          expected = pd.Index(data, dtype=object)
          tm.assert_index_equal(Index(data), expected)
          tm.assert_index_equal(Index(np.array(data, dtype=object)), expected)
  
      def test_index_ctor_infer_periodindex(self):
          xp = period_range('2012-1-1', freq='M', periods=3)
          rs = Index(xp)
          tm.assert_index_equal(rs, xp)
          assert isinstance(rs, PeriodIndex)
  
      @pytest.mark.parametrize("vals,dtype", [
          ([1, 2, 3, 4, 5], 'int'), ([1.1, np.nan, 2.2, 3.0], 'float'),
          (['A', 'B', 'C', np.nan], 'obj')
      ])
      def test_constructor_simple_new(self, vals, dtype):
          index = Index(vals, name=dtype)
          result = index._simple_new(index.values, dtype)
          tm.assert_index_equal(result, index)
  
      @pytest.mark.parametrize("vals", [
          [1, 2, 3], np.array([1, 2, 3]), np.array([1, 2, 3], dtype=int),
          # below should coerce
          [1., 2., 3.], np.array([1., 2., 3.], dtype=float)
      ])
      def test_constructor_dtypes_to_int64(self, vals):
          index = Index(vals, dtype=int)
          assert isinstance(index, Int64Index)
  
      @pytest.mark.parametrize("vals", [
          [1, 2, 3], [1., 2., 3.], np.array([1., 2., 3.]),
          np.array([1, 2, 3], dtype=int), np.array([1., 2., 3.], dtype=float)
      ])
      def test_constructor_dtypes_to_float64(self, vals):
          index = Index(vals, dtype=float)
          assert isinstance(index, Float64Index)
  
      @pytest.mark.parametrize("cast_index", [True, False])
      @pytest.mark.parametrize("vals", [
          [True, False, True], np.array([True, False, True], dtype=bool)
      ])
      def test_constructor_dtypes_to_object(self, cast_index, vals):
          if cast_index:
              index = Index(vals, dtype=bool)
          else:
              index = Index(vals)
  
          assert isinstance(index, Index)
          assert index.dtype == object
  
      @pytest.mark.parametrize("vals", [
          [1, 2, 3], np.array([1, 2, 3], dtype=int),
          np.array([np_datetime64_compat('2011-01-01'),
                    np_datetime64_compat('2011-01-02')]),
          [datetime(2011, 1, 1), datetime(2011, 1, 2)]
      ])
      def test_constructor_dtypes_to_categorical(self, vals):
          index = Index(vals, dtype='category')
          assert isinstance(index, CategoricalIndex)
  
      @pytest.mark.parametrize("cast_index", [True, False])
      @pytest.mark.parametrize("vals", [
          Index(np.array([np_datetime64_compat('2011-01-01'),
                          np_datetime64_compat('2011-01-02')])),
          Index([datetime(2011, 1, 1), datetime(2011, 1, 2)])
  
      ])
      def test_constructor_dtypes_to_datetime(self, cast_index, vals):
          if cast_index:
              index = Index(vals, dtype=object)
              assert isinstance(index, Index)
              assert index.dtype == object
          else:
              index = Index(vals)
              assert isinstance(index, DatetimeIndex)
  
      @pytest.mark.parametrize("cast_index", [True, False])
      @pytest.mark.parametrize("vals", [
          np.array([np.timedelta64(1, 'D'), np.timedelta64(1, 'D')]),
          [timedelta(1), timedelta(1)]
      ])
      def test_constructor_dtypes_to_timedelta(self, cast_index, vals):
          if cast_index:
              index = Index(vals, dtype=object)
              assert isinstance(index, Index)
              assert index.dtype == object
          else:
              index = Index(vals)
              assert isinstance(index, TimedeltaIndex)
  
      @pytest.mark.parametrize("attr, utc", [
          ['values', False],
          ['asi8', True]])
      @pytest.mark.parametrize("klass", [pd.Index, pd.DatetimeIndex])
      def test_constructor_dtypes_datetime(self, tz_naive_fixture, attr, utc,
                                           klass):
          # Test constructing with a datetimetz dtype
          # .values produces numpy datetimes, so these are considered naive
          # .asi8 produces integers, so these are considered epoch timestamps
          index = pd.date_range('2011-01-01', periods=5)
          arg = getattr(index, attr)
          if utc:
              index = index.tz_localize('UTC').tz_convert(tz_naive_fixture)
          else:
              index = index.tz_localize(tz_naive_fixture)
          dtype = index.dtype
  
          result = klass(arg, tz=tz_naive_fixture)
          tm.assert_index_equal(result, index)
  
          result = klass(arg, dtype=dtype)
          tm.assert_index_equal(result, index)
  
          result = klass(list(arg), tz=tz_naive_fixture)
          tm.assert_index_equal(result, index)
  
          result = klass(list(arg), dtype=dtype)
          tm.assert_index_equal(result, index)
  
      @pytest.mark.parametrize("attr", ['values', 'asi8'])
      @pytest.mark.parametrize("klass", [pd.Index, pd.TimedeltaIndex])
      def test_constructor_dtypes_timedelta(self, attr, klass):
          index = pd.timedelta_range('1 days', periods=5)
          dtype = index.dtype
  
          values = getattr(index, attr)
  
          result = klass(values, dtype=dtype)
          tm.assert_index_equal(result, index)
  
          result = klass(list(values), dtype=dtype)
          tm.assert_index_equal(result, index)
  
      @pytest.mark.parametrize("value", [[], iter([]), (x for x in [])])
      @pytest.mark.parametrize("klass",
                               [Index, Float64Index, Int64Index, UInt64Index,
                                CategoricalIndex, DatetimeIndex, TimedeltaIndex])
      def test_constructor_empty(self, value, klass):
          empty = klass(value)
          assert isinstance(empty, klass)
          assert not len(empty)
  
      @pytest.mark.parametrize("empty,klass", [
          (PeriodIndex([], freq='B'), PeriodIndex),
          (PeriodIndex(iter([]), freq='B'), PeriodIndex),
          (PeriodIndex((x for x in []), freq='B'), PeriodIndex),
          (RangeIndex(step=1), pd.RangeIndex),
          (MultiIndex(levels=[[1, 2], ['blue', 'red']],
                      labels=[[], []]), MultiIndex)
      ])
      def test_constructor_empty_special(self, empty, klass):
          assert isinstance(empty, klass)
          assert not len(empty)
  
      def test_constructor_nonhashable_name(self, indices):
          # GH 20527
  
          if isinstance(indices, MultiIndex):
              pytest.skip("multiindex handled in test_multi.py")
  
          name = ['0']
          message = "Index.name must be a hashable type"
          tm.assert_raises_regex(TypeError, message, name=name)
  
          # With .rename()
          renamed = [['1']]
          tm.assert_raises_regex(TypeError, message,
                                 indices.rename, name=renamed)
          # With .set_names()
          tm.assert_raises_regex(TypeError, message,
                                 indices.set_names, names=renamed)
  
      def test_constructor_overflow_int64(self):
          # see gh-15832
          msg = ("The elements provided in the data cannot "
                 "all be casted to the dtype int64")
          with tm.assert_raises_regex(OverflowError, msg):
              Index([np.iinfo(np.uint64).max - 1], dtype="int64")
  
      @pytest.mark.xfail(reason="see GH#21311: Index "
                                "doesn't enforce dtype argument",
                         strict=True)
      def test_constructor_cast(self):
          msg = "could not convert string to float"
          with tm.assert_raises_regex(ValueError, msg):
              Index(["a", "b", "c"], dtype=float)
  
      def test_view_with_args(self):
  
          restricted = ['unicodeIndex', 'strIndex', 'catIndex', 'boolIndex',
                        'empty']
  
          for i in restricted:
              ind = self.indices[i]
  
              # with arguments
              pytest.raises(TypeError, lambda: ind.view('i8'))
  
          # these are ok
          for i in list(set(self.indices.keys()) - set(restricted)):
              ind = self.indices[i]
  
              # with arguments
              ind.view('i8')
  
      def test_astype(self):
          casted = self.intIndex.astype('i8')
  
          # it works!
          casted.get_loc(5)
  
          # pass on name
          self.intIndex.name = 'foobar'
          casted = self.intIndex.astype('i8')
          assert casted.name == 'foobar'
  
      def test_equals_object(self):
          # same
          assert Index(['a', 'b', 'c']).equals(Index(['a', 'b', 'c']))
  
      @pytest.mark.parametrize("comp", [
          Index(['a', 'b']), Index(['a', 'b', 'd']), ['a', 'b', 'c']])
      def test_not_equals_object(self, comp):
          assert not Index(['a', 'b', 'c']).equals(comp)
  
      def test_insert(self):
  
          # GH 7256
          # validate neg/pos inserts
          result = Index(['b', 'c', 'd'])
  
          # test 0th element
          tm.assert_index_equal(Index(['a', 'b', 'c', 'd']),
                                result.insert(0, 'a'))
  
          # test Nth element that follows Python list behavior
          tm.assert_index_equal(Index(['b', 'c', 'e', 'd']),
                                result.insert(-1, 'e'))
  
          # test loc +/- neq (0, -1)
          tm.assert_index_equal(result.insert(1, 'z'), result.insert(-2, 'z'))
  
          # test empty
          null_index = Index([])
          tm.assert_index_equal(Index(['a']), null_index.insert(0, 'a'))
  
      def test_insert_missing(self, nulls_fixture):
          # GH 22295
          # test there is no mangling of NA values
          expected = Index(['a', nulls_fixture, 'b', 'c'])
          result = Index(list('abc')).insert(1, nulls_fixture)
          tm.assert_index_equal(result, expected)
  
      @pytest.mark.parametrize("pos,expected", [
          (0, Index(['b', 'c', 'd'], name='index')),
          (-1, Index(['a', 'b', 'c'], name='index'))
      ])
      def test_delete(self, pos, expected):
          index = Index(['a', 'b', 'c', 'd'], name='index')
          result = index.delete(pos)
          tm.assert_index_equal(result, expected)
          assert result.name == expected.name
  
      def test_delete_raises(self):
          index = Index(['a', 'b', 'c', 'd'], name='index')
          with pytest.raises((IndexError, ValueError)):
              # either depending on numpy version
              index.delete(5)
  
      def test_identical(self):
  
          # index
          i1 = Index(['a', 'b', 'c'])
          i2 = Index(['a', 'b', 'c'])
  
          assert i1.identical(i2)
  
          i1 = i1.rename('foo')
          assert i1.equals(i2)
          assert not i1.identical(i2)
  
          i2 = i2.rename('foo')
          assert i1.identical(i2)
  
          i3 = Index([('a', 'a'), ('a', 'b'), ('b', 'a')])
          i4 = Index([('a', 'a'), ('a', 'b'), ('b', 'a')], tupleize_cols=False)
          assert not i3.identical(i4)
  
      def test_is_(self):
          ind = Index(range(10))
          assert ind.is_(ind)
          assert ind.is_(ind.view().view().view().view())
          assert not ind.is_(Index(range(10)))
          assert not ind.is_(ind.copy())
          assert not ind.is_(ind.copy(deep=False))
          assert not ind.is_(ind[:])
          assert not ind.is_(np.array(range(10)))
  
          # quasi-implementation dependent
          assert ind.is_(ind.view())
          ind2 = ind.view()
          ind2.name = 'bob'
          assert ind.is_(ind2)
          assert ind2.is_(ind)
          # doesn't matter if Indices are *actually* views of underlying data,
          assert not ind.is_(Index(ind.values))
          arr = np.array(range(1, 11))
          ind1 = Index(arr, copy=False)
          ind2 = Index(arr, copy=False)
          assert not ind1.is_(ind2)
  
      def test_asof(self):
          d = self.dateIndex[0]
          assert self.dateIndex.asof(d) == d
          assert isna(self.dateIndex.asof(d - timedelta(1)))
  
          d = self.dateIndex[-1]
          assert self.dateIndex.asof(d + timedelta(1)) == d
  
          d = self.dateIndex[0].to_pydatetime()
          assert isinstance(self.dateIndex.asof(d), Timestamp)
  
      def test_asof_datetime_partial(self):
          index = pd.date_range('2010-01-01', periods=2, freq='m')
          expected = Timestamp('2010-02-28')
          result = index.asof('2010-02')
          assert result == expected
          assert not isinstance(result, Index)
  
      def test_nanosecond_index_access(self):
          s = Series([Timestamp('20130101')]).values.view('i8')[0]
          r = DatetimeIndex([s + 50 + i for i in range(100)])
          x = Series(np.random.randn(100), index=r)
  
          first_value = x.asof(x.index[0])
  
          # this does not yet work, as parsing strings is done via dateutil
          # assert first_value == x['2013-01-01 00:00:00.000000050+0000']
  
          expected_ts = np_datetime64_compat('2013-01-01 00:00:00.000000050+'
                                             '0000', 'ns')
          assert first_value == x[Timestamp(expected_ts)]
  
      @pytest.mark.parametrize("op", [
          operator.eq, operator.ne, operator.gt, operator.lt,
          operator.ge, operator.le
      ])
      def test_comparators(self, op):
          index = self.dateIndex
          element = index[len(index) // 2]
          element = _to_m8(element)
  
          arr = np.array(index)
          arr_result = op(arr, element)
          index_result = op(index, element)
  
          assert isinstance(index_result, np.ndarray)
          tm.assert_numpy_array_equal(arr_result, index_result)
  
      def test_booleanindex(self):
          boolIndex = np.repeat(True, len(self.strIndex)).astype(bool)
          boolIndex[5:30:2] = False
  
          subIndex = self.strIndex[boolIndex]
  
          for i, val in enumerate(subIndex):
              assert subIndex.get_loc(val) == i
  
          subIndex = self.strIndex[list(boolIndex)]
          for i, val in enumerate(subIndex):
              assert subIndex.get_loc(val) == i
  
      def test_fancy(self):
          sl = self.strIndex[[1, 2, 3]]
          for i in sl:
              assert i == sl[sl.get_loc(i)]
  
      @pytest.mark.parametrize("attr", [
          'strIndex', 'intIndex', 'floatIndex'])
      @pytest.mark.parametrize("dtype", [np.int_, np.bool_])
      def test_empty_fancy(self, attr, dtype):
          empty_arr = np.array([], dtype=dtype)
          index = getattr(self, attr)
          empty_index = index.__class__([])
  
          assert index[[]].identical(empty_index)
          assert index[empty_arr].identical(empty_index)
  
      @pytest.mark.parametrize("attr", [
          'strIndex', 'intIndex', 'floatIndex'])
      def test_empty_fancy_raises(self, attr):
          # pd.DatetimeIndex is excluded, because it overrides getitem and should
          # be tested separately.
          empty_farr = np.array([], dtype=np.float_)
          index = getattr(self, attr)
          empty_index = index.__class__([])
  
          assert index[[]].identical(empty_index)
          # np.ndarray only accepts ndarray of int & bool dtypes, so should Index
          pytest.raises(IndexError, index.__getitem__, empty_farr)
  
      @pytest.mark.parametrize("itm", [101, 'no_int'])
      # FutureWarning from non-tuple sequence of nd indexing
      @pytest.mark.filterwarnings("ignore::FutureWarning")
      def test_getitem_error(self, indices, itm):
          with pytest.raises(IndexError):
              indices[itm]
  
      def test_intersection(self):
          first = self.strIndex[:20]
          second = self.strIndex[:10]
          intersect = first.intersection(second)
          assert tm.equalContents(intersect, second)
  
          # Corner cases
          inter = first.intersection(first)
          assert inter is first
  
      @pytest.mark.parametrize("index2,keeps_name", [
          (Index([3, 4, 5, 6, 7], name="index"), True),  # preserve same name
          (Index([3, 4, 5, 6, 7], name="other"), False),  # drop diff names
          (Index([3, 4, 5, 6, 7]), False)])
      def test_intersection_name_preservation(self, index2, keeps_name):
          index1 = Index([1, 2, 3, 4, 5], name='index')
          expected = Index([3, 4, 5])
          result = index1.intersection(index2)
  
          if keeps_name:
              expected.name = 'index'
  
          assert result.name == expected.name
          tm.assert_index_equal(result, expected)
  
      @pytest.mark.parametrize("first_name,second_name,expected_name", [
          ('A', 'A', 'A'), ('A', 'B', None), (None, 'B', None)])
      def test_intersection_name_preservation2(self, first_name, second_name,
                                               expected_name):
          first = self.strIndex[5:20]
          second = self.strIndex[:10]
          first.name = first_name
          second.name = second_name
          intersect = first.intersection(second)
          assert intersect.name == expected_name
  
      @pytest.mark.parametrize("index2,keeps_name", [
          (Index([4, 7, 6, 5, 3], name='index'), True),
          (Index([4, 7, 6, 5, 3], name='other'), False)])
      def test_intersection_monotonic(self, index2, keeps_name):
          index1 = Index([5, 3, 2, 4, 1], name='index')
          expected = Index([5, 3, 4])
  
          if keeps_name:
              expected.name = "index"
  
          result = index1.intersection(index2)
          tm.assert_index_equal(result, expected)
  
      @pytest.mark.parametrize("index2,expected_arr", [
          (Index(['B', 'D']), ['B']),
          (Index(['B', 'D', 'A']), ['A', 'B', 'A'])])
      def test_intersection_non_monotonic_non_unique(self, index2, expected_arr):
          # non-monotonic non-unique
          index1 = Index(['A', 'B', 'A', 'C'])
          expected = Index(expected_arr, dtype='object')
          result = index1.intersection(index2)
          tm.assert_index_equal(result, expected)
  
      def test_intersect_str_dates(self):
          dt_dates = [datetime(2012, 2, 9), datetime(2012, 2, 22)]
  
          i1 = Index(dt_dates, dtype=object)
          i2 = Index(['aa'], dtype=object)
          result = i2.intersection(i1)
  
          assert len(result) == 0
  
      def test_union(self):
          # TODO: Replace with fixturesult
          first = self.strIndex[5:20]
          second = self.strIndex[:10]
          everything = self.strIndex[:20]
  
          union = first.union(second)
          assert tm.equalContents(union, everything)
  
      @pytest.mark.parametrize("klass", [
          np.array, Series, list])
      def test_union_from_iterables(self, klass):
          # GH 10149
          # TODO: Replace with fixturesult
          first = self.strIndex[5:20]
          second = self.strIndex[:10]
          everything = self.strIndex[:20]
  
          case = klass(second.values)
          result = first.union(case)
          assert tm.equalContents(result, everything)
  
      def test_union_identity(self):
          # TODO: replace with fixturesult
          first = self.strIndex[5:20]
  
          union = first.union(first)
          assert union is first
  
          union = first.union([])
          assert union is first
  
          union = Index([]).union(first)
          assert union is first
  
      @pytest.mark.parametrize("first_list", [list('ab'), list()])
      @pytest.mark.parametrize("second_list", [list('ab'), list()])
      @pytest.mark.parametrize("first_name, second_name, expected_name", [
          ('A', 'B', None), (None, 'B', 'B'), ('A', None, 'A')])
      def test_union_name_preservation(self, first_list, second_list, first_name,
                                       second_name, expected_name):
          first = Index(first_list, name=first_name)
          second = Index(second_list, name=second_name)
          union = first.union(second)
  
          vals = sorted(set(first_list).union(second_list))
          expected = Index(vals, name=expected_name)
          tm.assert_index_equal(union, expected)
  
      def test_union_dt_as_obj(self):
          # TODO: Replace with fixturesult
          with tm.assert_produces_warning(RuntimeWarning):
              firstCat = self.strIndex.union(self.dateIndex)
          secondCat = self.strIndex.union(self.strIndex)
  
          if self.dateIndex.dtype == np.object_:
              appended = np.append(self.strIndex, self.dateIndex)
          else:
              appended = np.append(self.strIndex, self.dateIndex.astype('O'))
  
          assert tm.equalContents(firstCat, appended)
          assert tm.equalContents(secondCat, self.strIndex)
          tm.assert_contains_all(self.strIndex, firstCat)
          tm.assert_contains_all(self.strIndex, secondCat)
          tm.assert_contains_all(self.dateIndex, firstCat)
  
      def test_add(self):
          index = self.strIndex
          expected = Index(self.strIndex.values * 2)
          tm.assert_index_equal(index + index, expected)
          tm.assert_index_equal(index + index.tolist(), expected)
          tm.assert_index_equal(index.tolist() + index, expected)
  
          # test add and radd
          index = Index(list('abc'))
          expected = Index(['a1', 'b1', 'c1'])
          tm.assert_index_equal(index + '1', expected)
          expected = Index(['1a', '1b', '1c'])
          tm.assert_index_equal('1' + index, expected)
  
      def test_sub_fail(self):
          index = self.strIndex
          pytest.raises(TypeError, lambda: index - 'a')
          pytest.raises(TypeError, lambda: index - index)
          pytest.raises(TypeError, lambda: index - index.tolist())
          pytest.raises(TypeError, lambda: index.tolist() - index)
  
      def test_sub_object(self):
          # GH#19369
          index = pd.Index([Decimal(1), Decimal(2)])
          expected = pd.Index([Decimal(0), Decimal(1)])
  
          result = index - Decimal(1)
          tm.assert_index_equal(result, expected)
  
          result = index - pd.Index([Decimal(1), Decimal(1)])
          tm.assert_index_equal(result, expected)
  
          with pytest.raises(TypeError):
              index - 'foo'
  
          with pytest.raises(TypeError):
              index - np.array([2, 'foo'])
  
      def test_rsub_object(self):
          # GH#19369
          index = pd.Index([Decimal(1), Decimal(2)])
          expected = pd.Index([Decimal(1), Decimal(0)])
  
          result = Decimal(2) - index
          tm.assert_index_equal(result, expected)
  
          result = np.array([Decimal(2), Decimal(2)]) - index
          tm.assert_index_equal(result, expected)
  
          with pytest.raises(TypeError):
              'foo' - index
  
          with pytest.raises(TypeError):
              np.array([True, pd.Timestamp.now()]) - index
  
      def test_map_identity_mapping(self):
          # GH 12766
          # TODO: replace with fixture
          for name, cur_index in self.indices.items():
              tm.assert_index_equal(cur_index, cur_index.map(lambda x: x))
  
      def test_map_with_tuples(self):
          # GH 12766
  
          # Test that returning a single tuple from an Index
          #   returns an Index.
          index = tm.makeIntIndex(3)
          result = tm.makeIntIndex(3).map(lambda x: (x,))
          expected = Index([(i,) for i in index])
          tm.assert_index_equal(result, expected)
  
          # Test that returning a tuple from a map of a single index
          #   returns a MultiIndex object.
          result = index.map(lambda x: (x, x == 1))
          expected = MultiIndex.from_tuples([(i, i == 1) for i in index])
          tm.assert_index_equal(result, expected)
  
      def test_map_with_tuples_mi(self):
          # Test that returning a single object from a MultiIndex
          #   returns an Index.
          first_level = ['foo', 'bar', 'baz']
          multi_index = MultiIndex.from_tuples(lzip(first_level, [1, 2, 3]))
          reduced_index = multi_index.map(lambda x: x[0])
          tm.assert_index_equal(reduced_index, Index(first_level))
  
      @pytest.mark.parametrize("attr", [
          'makeDateIndex', 'makePeriodIndex', 'makeTimedeltaIndex'])
      def test_map_tseries_indices_return_index(self, attr):
          index = getattr(tm, attr)(10)
          expected = Index([1] * 10)
          result = index.map(lambda x: 1)
          tm.assert_index_equal(expected, result)
  
      def test_map_tseries_indices_accsr_return_index(self):
          date_index = tm.makeDateIndex(24, freq='h', name='hourly')
          expected = Index(range(24), name='hourly')
          tm.assert_index_equal(expected, date_index.map(lambda x: x.hour))
  
      @pytest.mark.parametrize(
          "mapper",
          [
              lambda values, index: {i: e for e, i in zip(values, index)},
              lambda values, index: pd.Series(values, index)])
      def test_map_dictlike(self, mapper):
          # GH 12756
          expected = Index(['foo', 'bar', 'baz'])
          index = tm.makeIntIndex(3)
          result = index.map(mapper(expected.values, index))
          tm.assert_index_equal(result, expected)
  
          # TODO: replace with fixture
          for name in self.indices.keys():
              if name == 'catIndex':
                  # Tested in test_categorical
                  continue
              elif name == 'repeats':
                  # Cannot map duplicated index
                  continue
  
              index = self.indices[name]
              expected = Index(np.arange(len(index), 0, -1))
  
              # to match proper result coercion for uints
              if name == 'empty':
                  expected = Index([])
  
              result = index.map(mapper(expected, index))
              tm.assert_index_equal(result, expected)
  
      @pytest.mark.parametrize("mapper", [
          Series(['foo', 2., 'baz'], index=[0, 2, -1]),
          {0: 'foo', 2: 2.0, -1: 'baz'}])
      def test_map_with_non_function_missing_values(self, mapper):
          # GH 12756
          expected = Index([2., np.nan, 'foo'])
          result = Index([2, 1, 0]).map(mapper)
  
          tm.assert_index_equal(expected, result)
  
      def test_map_na_exclusion(self):
          index = Index([1.5, np.nan, 3, np.nan, 5])
  
          result = index.map(lambda x: x * 2, na_action='ignore')
          expected = index * 2
          tm.assert_index_equal(result, expected)
  
      def test_map_defaultdict(self):
          index = Index([1, 2, 3])
          default_dict = defaultdict(lambda: 'blank')
          default_dict[1] = 'stuff'
          result = index.map(default_dict)
          expected = Index(['stuff', 'blank', 'blank'])
          tm.assert_index_equal(result, expected)
  
      def test_append_multiple(self):
          index = Index(['a', 'b', 'c', 'd', 'e', 'f'])
  
          foos = [index[:2], index[2:4], index[4:]]
          result = foos[0].append(foos[1:])
          tm.assert_index_equal(result, index)
  
          # empty
          result = index.append([])
          tm.assert_index_equal(result, index)
  
      @pytest.mark.parametrize("name,expected", [
          ('foo', 'foo'), ('bar', None)])
      def test_append_empty_preserve_name(self, name, expected):
          left = Index([], name='foo')
          right = Index([1, 2, 3], name=name)
  
          result = left.append(right)
          assert result.name == expected
  
      def test_add_string(self):
          # from bug report
          index = Index(['a', 'b', 'c'])
          index2 = index + 'foo'
  
          assert 'a' not in index2
          assert 'afoo' in index2
  
      def test_iadd_string(self):
          index = pd.Index(['a', 'b', 'c'])
          # doesn't fail test unless there is a check before `+=`
          assert 'a' in index
  
          index += '_x'
          assert 'a_x' in index
  
      @pytest.mark.parametrize("second_name,expected", [
          (None, None), ('name', 'name')])
      def test_difference_name_preservation(self, second_name, expected):
          # TODO: replace with fixturesult
          first = self.strIndex[5:20]
          second = self.strIndex[:10]
          answer = self.strIndex[10:20]
  
          first.name = 'name'
          second.name = second_name
          result = first.difference(second)
  
          assert tm.equalContents(result, answer)
  
          if expected is None:
              assert result.name is None
          else:
              assert result.name == expected
  
      def test_difference_empty_arg(self):
          first = self.strIndex[5:20]
          first.name == 'name'
          result = first.difference([])
  
          assert tm.equalContents(result, first)
          assert result.name == first.name
  
      def test_difference_identity(self):
          first = self.strIndex[5:20]
          first.name == 'name'
          result = first.difference(first)
  
          assert len(result) == 0
          assert result.name == first.name
  
      def test_symmetric_difference(self):
          # smoke
          index1 = Index([1, 2, 3, 4], name='index1')
          index2 = Index([2, 3, 4, 5])
          result = index1.symmetric_difference(index2)
          expected = Index([1, 5])
          assert tm.equalContents(result, expected)
          assert result.name is None
  
          # __xor__ syntax
          expected = index1 ^ index2
          assert tm.equalContents(result, expected)
          assert result.name is None
  
      def test_symmetric_difference_mi(self):
          index1 = MultiIndex.from_tuples(self.tuples)
          index2 = MultiIndex.from_tuples([('foo', 1), ('bar', 3)])
          result = index1.symmetric_difference(index2)
          expected = MultiIndex.from_tuples([('bar', 2), ('baz', 3), ('bar', 3)])
          assert tm.equalContents(result, expected)
  
      @pytest.mark.parametrize("index2,expected", [
          (Index([0, 1, np.nan]), Index([0.0, 2.0, 3.0])),
          (Index([0, 1]), Index([0.0, 2.0, 3.0, np.nan]))])
      def test_symmetric_difference_missing(self, index2, expected):
          # GH 13514 change: {nan} - {nan} == {}
          # (GH 6444, sorting of nans, is no longer an issue)
          index1 = Index([1, np.nan, 2, 3])
  
          result = index1.symmetric_difference(index2)
          tm.assert_index_equal(result, expected)
  
      def test_symmetric_difference_non_index(self):
          index1 = Index([1, 2, 3, 4], name='index1')
          index2 = np.array([2, 3, 4, 5])
          expected = Index([1, 5])
          result = index1.symmetric_difference(index2)
          assert tm.equalContents(result, expected)
          assert result.name == 'index1'
  
          result = index1.symmetric_difference(index2, result_name='new_name')
          assert tm.equalContents(result, expected)
          assert result.name == 'new_name'
  
      def test_difference_type(self):
          # GH 20040
          # If taking difference of a set and itself, it
          # needs to preserve the type of the index
          skip_index_keys = ['repeats']
          for key, index in self.generate_index_types(skip_index_keys):
              result = index.difference(index)
              expected = index.drop(index)
              tm.assert_index_equal(result, expected)
  
      def test_intersection_difference(self):
          # GH 20040
          # Test that the intersection of an index with an
          # empty index produces the same index as the difference
          # of an index with itself.  Test for all types
          skip_index_keys = ['repeats']
          for key, index in self.generate_index_types(skip_index_keys):
              inter = index.intersection(index.drop(index))
              diff = index.difference(index)
              tm.assert_index_equal(inter, diff)
  
      @pytest.mark.parametrize("attr,expected", [
          ('strIndex', False), ('boolIndex', False), ('catIndex', False),
          ('intIndex', True), ('dateIndex', False), ('floatIndex', True)])
      def test_is_numeric(self, attr, expected):
          assert getattr(self, attr).is_numeric() == expected
  
      @pytest.mark.parametrize("attr,expected", [
          ('strIndex', True), ('boolIndex', True), ('catIndex', False),
          ('intIndex', False), ('dateIndex', False), ('floatIndex', False)])
      def test_is_object(self, attr, expected):
          assert getattr(self, attr).is_object() == expected
  
      @pytest.mark.parametrize("attr,expected", [
          ('strIndex', False), ('boolIndex', False), ('catIndex', False),
          ('intIndex', False), ('dateIndex', True), ('floatIndex', False)])
      def test_is_all_dates(self, attr, expected):
          assert getattr(self, attr).is_all_dates == expected
  
      def test_summary(self):
          self._check_method_works(Index._summary)
          # GH3869
          ind = Index(['{other}%s', "~:{range}:0"], name='A')
          result = ind._summary()
          # shouldn't be formatted accidentally.
          assert '~:{range}:0' in result
          assert '{other}%s' in result
  
      # GH18217
      def test_summary_deprecated(self):
          ind = Index(['{other}%s', "~:{range}:0"], name='A')
  
          with tm.assert_produces_warning(FutureWarning):
              ind.summary()
  
      def test_format(self):
          self._check_method_works(Index.format)
  
          # GH 14626
          # windows has different precision on datetime.datetime.now (it doesn't
          # include us since the default for Timestamp shows these but Index
          # formatting does not we are skipping)
          now = datetime.now()
          if not str(now).endswith("000"):
              index = Index([now])
              formatted = index.format()
              expected = [str(index[0])]
              assert formatted == expected
  
          self.strIndex[:0].format()
  
      @pytest.mark.parametrize("vals", [
          [1, 2.0 + 3.0j, 4.], ['a', 'b', 'c']])
      def test_format_missing(self, vals, nulls_fixture):
          # 2845
          vals = list(vals)  # Copy for each iteration
          vals.append(nulls_fixture)
          index = Index(vals)
  
          formatted = index.format()
          expected = [str(index[0]), str(index[1]), str(index[2]), u('NaN')]
  
          assert formatted == expected
          assert index[3] is nulls_fixture
  
      def test_format_with_name_time_info(self):
          # bug I fixed 12/20/2011
          inc = timedelta(hours=4)
          dates = Index([dt + inc for dt in self.dateIndex], name='something')
  
          formatted = dates.format(name=True)
          assert formatted[0] == 'something'
  
      def test_format_datetime_with_time(self):
          t = Index([datetime(2012, 2, 7), datetime(2012, 2, 7, 23)])
  
          result = t.format()
          expected = ['2012-02-07 00:00:00', '2012-02-07 23:00:00']
          assert len(result) == 2
          assert result == expected
  
      @pytest.mark.parametrize("op", ['any', 'all'])
      def test_logical_compat(self, op):
          index = self.create_index()
          assert getattr(index, op)() == getattr(index.values, op)()
  
      def _check_method_works(self, method):
          # TODO: make this a dedicated test with parametrized methods
          method(self.empty)
          method(self.dateIndex)
          method(self.unicodeIndex)
          method(self.strIndex)
          method(self.intIndex)
          method(self.tuples)
          method(self.catIndex)
  
      def test_get_indexer(self):
          index1 = Index([1, 2, 3, 4, 5])
          index2 = Index([2, 4, 6])
  
          r1 = index1.get_indexer(index2)
          e1 = np.array([1, 3, -1], dtype=np.intp)
          assert_almost_equal(r1, e1)
  
      @pytest.mark.parametrize("reverse", [True, False])
      @pytest.mark.parametrize("expected,method", [
          (np.array([-1, 0, 0, 1, 1], dtype=np.intp), 'pad'),
          (np.array([-1, 0, 0, 1, 1], dtype=np.intp), 'ffill'),
          (np.array([0, 0, 1, 1, 2], dtype=np.intp), 'backfill'),
          (np.array([0, 0, 1, 1, 2], dtype=np.intp), 'bfill')])
      def test_get_indexer_methods(self, reverse, expected, method):
          index1 = Index([1, 2, 3, 4, 5])
          index2 = Index([2, 4, 6])
  
          if reverse:
              index1 = index1[::-1]
              expected = expected[::-1]
  
          result = index2.get_indexer(index1, method=method)
          assert_almost_equal(result, expected)
  
      def test_get_indexer_invalid(self):
          # GH10411
          index = Index(np.arange(10))
  
          with tm.assert_raises_regex(ValueError, 'tolerance argument'):
              index.get_indexer([1, 0], tolerance=1)
  
          with tm.assert_raises_regex(ValueError, 'limit argument'):
              index.get_indexer([1, 0], limit=1)
  
      @pytest.mark.parametrize(
          'method, tolerance, indexer, expected',
          [
              ('pad', None, [0, 5, 9], [0, 5, 9]),
              ('backfill', None, [0, 5, 9], [0, 5, 9]),
              ('nearest', None, [0, 5, 9], [0, 5, 9]),
              ('pad', 0, [0, 5, 9], [0, 5, 9]),
              ('backfill', 0, [0, 5, 9], [0, 5, 9]),
              ('nearest', 0, [0, 5, 9], [0, 5, 9]),
  
              ('pad', None, [0.2, 1.8, 8.5], [0, 1, 8]),
              ('backfill', None, [0.2, 1.8, 8.5], [1, 2, 9]),
              ('nearest', None, [0.2, 1.8, 8.5], [0, 2, 9]),
              ('pad', 1, [0.2, 1.8, 8.5], [0, 1, 8]),
              ('backfill', 1, [0.2, 1.8, 8.5], [1, 2, 9]),
              ('nearest', 1, [0.2, 1.8, 8.5], [0, 2, 9]),
  
              ('pad', 0.2, [0.2, 1.8, 8.5], [0, -1, -1]),
              ('backfill', 0.2, [0.2, 1.8, 8.5], [-1, 2, -1]),
              ('nearest', 0.2, [0.2, 1.8, 8.5], [0, 2, -1])])
      def test_get_indexer_nearest(self, method, tolerance, indexer, expected):
          index = Index(np.arange(10))
  
          actual = index.get_indexer(indexer, method=method, tolerance=tolerance)
          tm.assert_numpy_array_equal(actual, np.array(expected,
                                                       dtype=np.intp))
  
      @pytest.mark.parametrize('listtype', [list, tuple, Series, np.array])
      @pytest.mark.parametrize(
          'tolerance, expected',
          list(zip([[0.3, 0.3, 0.1], [0.2, 0.1, 0.1],
                    [0.1, 0.5, 0.5]],
                   [[0, 2, -1], [0, -1, -1],
                    [-1, 2, 9]])))
      def test_get_indexer_nearest_listlike_tolerance(self, tolerance,
                                                      expected, listtype):
          index = Index(np.arange(10))
  
          actual = index.get_indexer([0.2, 1.8, 8.5], method='nearest',
                                     tolerance=listtype(tolerance))
          tm.assert_numpy_array_equal(actual, np.array(expected,
                                                       dtype=np.intp))
  
      def test_get_indexer_nearest_error(self):
          index = Index(np.arange(10))
          with tm.assert_raises_regex(ValueError, 'limit argument'):
              index.get_indexer([1, 0], method='nearest', limit=1)
  
          with pytest.raises(ValueError, match='tolerance size must match'):
              index.get_indexer([1, 0], method='nearest',
                                tolerance=[1, 2, 3])
  
      @pytest.mark.parametrize("method,expected", [
          ('pad', [8, 7, 0]), ('backfill', [9, 8, 1]), ('nearest', [9, 7, 0])])
      def test_get_indexer_nearest_decreasing(self, method, expected):
          index = Index(np.arange(10))[::-1]
  
          actual = index.get_indexer([0, 5, 9], method=method)
          tm.assert_numpy_array_equal(actual, np.array([9, 4, 0], dtype=np.intp))
  
          actual = index.get_indexer([0.2, 1.8, 8.5], method=method)
          tm.assert_numpy_array_equal(actual, np.array(expected, dtype=np.intp))
  
      @pytest.mark.parametrize("method,expected", [
          ('pad', np.array([-1, 0, 1, 1], dtype=np.intp)),
          ('backfill', np.array([0, 0, 1, -1], dtype=np.intp))])
      def test_get_indexer_strings(self, method, expected):
          index = pd.Index(['b', 'c'])
          actual = index.get_indexer(['a', 'b', 'c', 'd'], method=method)
  
          tm.assert_numpy_array_equal(actual, expected)
  
      def test_get_indexer_strings_raises(self):
          index = pd.Index(['b', 'c'])
  
          with pytest.raises(TypeError):
              index.get_indexer(['a', 'b', 'c', 'd'], method='nearest')
  
          with pytest.raises(TypeError):
              index.get_indexer(['a', 'b', 'c', 'd'], method='pad', tolerance=2)
  
          with pytest.raises(TypeError):
              index.get_indexer(['a', 'b', 'c', 'd'], method='pad',
                                tolerance=[2, 2, 2, 2])
  
      def test_get_indexer_numeric_index_boolean_target(self):
          # GH 16877
          numeric_index = pd.Index(range(4))
          result = numeric_index.get_indexer([True, False, True])
          expected = np.array([-1, -1, -1], dtype=np.intp)
          tm.assert_numpy_array_equal(result, expected)
  
      def test_get_indexer_with_NA_values(self, unique_nulls_fixture,
                                          unique_nulls_fixture2):
          # GH 22332
          # check pairwise, that no pair of na values
          # is mangled
          if unique_nulls_fixture is unique_nulls_fixture2:
              return  # skip it, values are not unique
          arr = np.array([unique_nulls_fixture,
                          unique_nulls_fixture2], dtype=np.object)
          index = pd.Index(arr, dtype=np.object)
          result = index.get_indexer([unique_nulls_fixture,
                                      unique_nulls_fixture2, 'Unknown'])
          expected = np.array([0, 1, -1], dtype=np.int64)
          tm.assert_numpy_array_equal(result, expected)
  
      @pytest.mark.parametrize("method", [None, 'pad', 'backfill', 'nearest'])
      def test_get_loc(self, method):
          index = pd.Index([0, 1, 2])
          assert index.get_loc(1, method=method) == 1
  
          if method:
              assert index.get_loc(1, method=method, tolerance=0) == 1
  
      @pytest.mark.parametrize("method", [None, 'pad', 'backfill', 'nearest'])
      def test_get_loc_raises_bad_label(self, method):
          index = pd.Index([0, 1, 2])
          if method:
              # Messages vary across versions
              if PY36:
                  msg = 'not supported between'
              elif PY35:
                  msg = 'unorderable types'
              else:
                  if method == 'nearest':
                      msg = 'unsupported operand'
                  else:
                      msg = 'requires scalar valued input'
          else:
              msg = 'invalid key'
  
          with tm.assert_raises_regex(TypeError, msg):
              index.get_loc([1, 2], method=method)
  
      @pytest.mark.parametrize("method,loc", [
          ('pad', 1), ('backfill', 2), ('nearest', 1)])
      def test_get_loc_tolerance(self, method, loc):
          index = pd.Index([0, 1, 2])
          assert index.get_loc(1.1, method) == loc
          assert index.get_loc(1.1, method, tolerance=1) == loc
  
      @pytest.mark.parametrize("method", ['pad', 'backfill', 'nearest'])
      def test_get_loc_outside_tolerance_raises(self, method):
          index = pd.Index([0, 1, 2])
          with tm.assert_raises_regex(KeyError, '1.1'):
              index.get_loc(1.1, method, tolerance=0.05)
  
      def test_get_loc_bad_tolerance_raises(self):
          index = pd.Index([0, 1, 2])
          with tm.assert_raises_regex(ValueError, 'must be numeric'):
              index.get_loc(1.1, 'nearest', tolerance='invalid')
  
      def test_get_loc_tolerance_no_method_raises(self):
          index = pd.Index([0, 1, 2])
          with tm.assert_raises_regex(ValueError, 'tolerance .* valid if'):
              index.get_loc(1.1, tolerance=1)
  
      def test_get_loc_raises_missized_tolerance(self):
          index = pd.Index([0, 1, 2])
          with tm.assert_raises_regex(ValueError, 'tolerance size must match'):
              index.get_loc(1.1, 'nearest', tolerance=[1, 1])
  
      def test_get_loc_raises_object_nearest(self):
          index = pd.Index(['a', 'c'])
          with tm.assert_raises_regex(TypeError, 'unsupported operand type'):
              index.get_loc('a', method='nearest')
  
      def test_get_loc_raises_object_tolerance(self):
          index = pd.Index(['a', 'c'])
          with tm.assert_raises_regex(TypeError, 'unsupported operand type'):
              index.get_loc('a', method='pad', tolerance='invalid')
  
      @pytest.mark.parametrize("dtype", [int, float])
      def test_slice_locs(self, dtype):
          index = Index(np.array([0, 1, 2, 5, 6, 7, 9, 10], dtype=dtype))
          n = len(index)
  
          assert index.slice_locs(start=2) == (2, n)
          assert index.slice_locs(start=3) == (3, n)
          assert index.slice_locs(3, 8) == (3, 6)
          assert index.slice_locs(5, 10) == (3, n)
          assert index.slice_locs(end=8) == (0, 6)
          assert index.slice_locs(end=9) == (0, 7)
  
          # reversed
          index2 = index[::-1]
          assert index2.slice_locs(8, 2) == (2, 6)
          assert index2.slice_locs(7, 3) == (2, 5)
  
      def test_slice_float_locs(self):
          index = Index(np.array([0, 1, 2, 5, 6, 7, 9, 10], dtype=float))
          n = len(index)
          assert index.slice_locs(5.0, 10.0) == (3, n)
          assert index.slice_locs(4.5, 10.5) == (3, 8)
  
          index2 = index[::-1]
          assert index2.slice_locs(8.5, 1.5) == (2, 6)
          assert index2.slice_locs(10.5, -1) == (0, n)
  
      @pytest.mark.xfail(reason="Assertions were not correct - see GH#20915",
                         strict=True)
      def test_slice_ints_with_floats_raises(self):
          # int slicing with floats
          # GH 4892, these are all TypeErrors
          index = Index(np.array([0, 1, 2, 5, 6, 7, 9, 10], dtype=int))
          n = len(index)
  
          pytest.raises(TypeError,
                        lambda: index.slice_locs(5.0, 10.0))
          pytest.raises(TypeError,
                        lambda: index.slice_locs(4.5, 10.5))
  
          index2 = index[::-1]
          pytest.raises(TypeError,
                        lambda: index2.slice_locs(8.5, 1.5), (2, 6))
          pytest.raises(TypeError,
                        lambda: index2.slice_locs(10.5, -1), (0, n))
  
      def test_slice_locs_dup(self):
          index = Index(['a', 'a', 'b', 'c', 'd', 'd'])
          assert index.slice_locs('a', 'd') == (0, 6)
          assert index.slice_locs(end='d') == (0, 6)
          assert index.slice_locs('a', 'c') == (0, 4)
          assert index.slice_locs('b', 'd') == (2, 6)
  
          index2 = index[::-1]
          assert index2.slice_locs('d', 'a') == (0, 6)
          assert index2.slice_locs(end='a') == (0, 6)
          assert index2.slice_locs('d', 'b') == (0, 4)
          assert index2.slice_locs('c', 'a') == (2, 6)
  
      @pytest.mark.parametrize("dtype", [int, float])
      def test_slice_locs_dup_numeric(self, dtype):
          index = Index(np.array([10, 12, 12, 14], dtype=dtype))
          assert index.slice_locs(12, 12) == (1, 3)
          assert index.slice_locs(11, 13) == (1, 3)
  
          index2 = index[::-1]
          assert index2.slice_locs(12, 12) == (1, 3)
          assert index2.slice_locs(13, 11) == (1, 3)
  
      def test_slice_locs_na(self):
          index = Index([np.nan, 1, 2])
          assert index.slice_locs(1) == (1, 3)
          assert index.slice_locs(np.nan) == (0, 3)
  
          index = Index([0, np.nan, np.nan, 1, 2])
          assert index.slice_locs(np.nan) == (1, 5)
  
      def test_slice_locs_na_raises(self):
          index = Index([np.nan, 1, 2])
          with tm.assert_raises_regex(KeyError, ''):
              index.slice_locs(start=1.5)
  
          with tm.assert_raises_regex(KeyError, ''):
              index.slice_locs(end=1.5)
  
      @pytest.mark.parametrize("in_slice,expected", [
          (pd.IndexSlice[::-1], 'yxdcb'), (pd.IndexSlice['b':'y':-1], ''),
          (pd.IndexSlice['b'::-1], 'b'), (pd.IndexSlice[:'b':-1], 'yxdcb'),
          (pd.IndexSlice[:'y':-1], 'y'), (pd.IndexSlice['y'::-1], 'yxdcb'),
          (pd.IndexSlice['y'::-4], 'yb'),
          # absent labels
          (pd.IndexSlice[:'a':-1], 'yxdcb'), (pd.IndexSlice[:'a':-2], 'ydb'),
          (pd.IndexSlice['z'::-1], 'yxdcb'), (pd.IndexSlice['z'::-3], 'yc'),
          (pd.IndexSlice['m'::-1], 'dcb'), (pd.IndexSlice[:'m':-1], 'yx'),
          (pd.IndexSlice['a':'a':-1], ''), (pd.IndexSlice['z':'z':-1], ''),
          (pd.IndexSlice['m':'m':-1], '')
      ])
      def test_slice_locs_negative_step(self, in_slice, expected):
          index = Index(list('bcdxy'))
  
          s_start, s_stop = index.slice_locs(in_slice.start, in_slice.stop,
                                             in_slice.step)
          result = index[s_start:s_stop:in_slice.step]
          expected = pd.Index(list(expected))
          tm.assert_index_equal(result, expected)
  
      def test_drop_by_str_label(self):
          # TODO: Parametrize these after replacing self.strIndex with fixture
          n = len(self.strIndex)
          drop = self.strIndex[lrange(5, 10)]
          dropped = self.strIndex.drop(drop)
  
          expected = self.strIndex[lrange(5) + lrange(10, n)]
          tm.assert_index_equal(dropped, expected)
  
          dropped = self.strIndex.drop(self.strIndex[0])
          expected = self.strIndex[1:]
          tm.assert_index_equal(dropped, expected)
  
      @pytest.mark.parametrize("keys", [['foo', 'bar'], ['1', 'bar']])
      def test_drop_by_str_label_raises_missing_keys(self, keys):
          with tm.assert_raises_regex(KeyError, ''):
              self.strIndex.drop(keys)
  
      def test_drop_by_str_label_errors_ignore(self):
          # TODO: Parametrize these after replacing self.strIndex with fixture
  
          # errors='ignore'
          n = len(self.strIndex)
          drop = self.strIndex[lrange(5, 10)]
          mixed = drop.tolist() + ['foo']
          dropped = self.strIndex.drop(mixed, errors='ignore')
  
          expected = self.strIndex[lrange(5) + lrange(10, n)]
          tm.assert_index_equal(dropped, expected)
  
          dropped = self.strIndex.drop(['foo', 'bar'], errors='ignore')
          expected = self.strIndex[lrange(n)]
          tm.assert_index_equal(dropped, expected)
  
      def test_drop_by_numeric_label_loc(self):
          # TODO: Parametrize numeric and str tests after self.strIndex fixture
          index = Index([1, 2, 3])
          dropped = index.drop(1)
          expected = Index([2, 3])
  
          tm.assert_index_equal(dropped, expected)
  
      def test_drop_by_numeric_label_raises_missing_keys(self):
          index = Index([1, 2, 3])
          with tm.assert_raises_regex(KeyError, ''):
              index.drop([3, 4])
  
      @pytest.mark.parametrize("key,expected", [
          (4, Index([1, 2, 3])), ([3, 4, 5], Index([1, 2]))])
      def test_drop_by_numeric_label_errors_ignore(self, key, expected):
          index = Index([1, 2, 3])
          dropped = index.drop(key, errors='ignore')
  
          tm.assert_index_equal(dropped, expected)
  
      @pytest.mark.parametrize("values", [['a', 'b', ('c', 'd')],
                                          ['a', ('c', 'd'), 'b'],
                                          [('c', 'd'), 'a', 'b']])
      @pytest.mark.parametrize("to_drop", [[('c', 'd'), 'a'], ['a', ('c', 'd')]])
      def test_drop_tuple(self, values, to_drop):
          # GH 18304
          index = pd.Index(values)
          expected = pd.Index(['b'])
  
          result = index.drop(to_drop)
          tm.assert_index_equal(result, expected)
  
          removed = index.drop(to_drop[0])
          for drop_me in to_drop[1], [to_drop[1]]:
              result = removed.drop(drop_me)
              tm.assert_index_equal(result, expected)
  
          removed = index.drop(to_drop[1])
          for drop_me in to_drop[1], [to_drop[1]]:
              pytest.raises(KeyError, removed.drop, drop_me)
  
      @pytest.mark.parametrize("method,expected", [
          ('intersection', np.array([(1, 'A'), (2, 'A'), (1, 'B'), (2, 'B')],
                                    dtype=[('num', int), ('let', 'a1')])),
          ('union', np.array([(1, 'A'), (2, 'A'), (1, 'B'), (2, 'B'), (1, 'C'),
                              (2, 'C')], dtype=[('num', int), ('let', 'a1')]))
      ])
      def test_tuple_union_bug(self, method, expected):
          index1 = Index(np.array([(1, 'A'), (2, 'A'), (1, 'B'), (2, 'B')],
                                  dtype=[('num', int), ('let', 'a1')]))
          index2 = Index(np.array([(1, 'A'), (2, 'A'), (1, 'B'),
                                   (2, 'B'), (1, 'C'), (2, 'C')],
                                  dtype=[('num', int), ('let', 'a1')]))
  
          result = getattr(index1, method)(index2)
          assert result.ndim == 1
  
          expected = Index(expected)
          tm.assert_index_equal(result, expected)
  
      @pytest.mark.parametrize("attr", [
          'is_monotonic_increasing', 'is_monotonic_decreasing',
          '_is_strictly_monotonic_increasing',
          '_is_strictly_monotonic_decreasing'])
      def test_is_monotonic_incomparable(self, attr):
          index = Index([5, datetime.now(), 7])
          assert not getattr(index, attr)
  
      def test_get_set_value(self):
          # TODO: Remove function? GH 19728
          values = np.random.randn(100)
          date = self.dateIndex[67]
  
          assert_almost_equal(self.dateIndex.get_value(values, date), values[67])
  
          self.dateIndex.set_value(values, date, 10)
          assert values[67] == 10
  
      @pytest.mark.parametrize("values", [
          ['foo', 'bar', 'quux'], {'foo', 'bar', 'quux'}])
      @pytest.mark.parametrize("index,expected", [
          (Index(['qux', 'baz', 'foo', 'bar']),
           np.array([False, False, True, True])),
          (Index([]), np.array([], dtype=bool))  # empty
      ])
      def test_isin(self, values, index, expected):
          result = index.isin(values)
          tm.assert_numpy_array_equal(result, expected)
  
      def test_isin_nan_common_object(self, nulls_fixture, nulls_fixture2):
          # Test cartesian product of null fixtures and ensure that we don't
          # mangle the various types (save a corner case with PyPy)
  
          # all nans are the same
          if (isinstance(nulls_fixture, float) and
                  isinstance(nulls_fixture2, float) and
                  math.isnan(nulls_fixture) and
                  math.isnan(nulls_fixture2)):
              tm.assert_numpy_array_equal(Index(['a', nulls_fixture]).isin(
                  [nulls_fixture2]), np.array([False, True]))
  
          elif nulls_fixture is nulls_fixture2:  # should preserve NA type
              tm.assert_numpy_array_equal(Index(['a', nulls_fixture]).isin(
                  [nulls_fixture2]), np.array([False, True]))
  
          else:
              tm.assert_numpy_array_equal(Index(['a', nulls_fixture]).isin(
                  [nulls_fixture2]), np.array([False, False]))
  
      def test_isin_nan_common_float64(self, nulls_fixture):
          if nulls_fixture is pd.NaT:
              pytest.skip("pd.NaT not compatible with Float64Index")
  
          # Float64Index overrides isin, so must be checked separately
          tm.assert_numpy_array_equal(Float64Index([1.0, nulls_fixture]).isin(
              [np.nan]), np.array([False, True]))
  
          # we cannot compare NaT with NaN
          tm.assert_numpy_array_equal(Float64Index([1.0, nulls_fixture]).isin(
              [pd.NaT]), np.array([False, False]))
  
      @pytest.mark.parametrize("level", [0, -1])
      @pytest.mark.parametrize("index", [
          Index(['qux', 'baz', 'foo', 'bar']),
          # Float64Index overrides isin, so must be checked separately
          Float64Index([1.0, 2.0, 3.0, 4.0])])
      def test_isin_level_kwarg(self, level, index):
          values = index.tolist()[-2:] + ['nonexisting']
  
          expected = np.array([False, False, True, True])
          tm.assert_numpy_array_equal(expected, index.isin(values, level=level))
  
          index.name = 'foobar'
          tm.assert_numpy_array_equal(expected,
                                      index.isin(values, level='foobar'))
  
      @pytest.mark.parametrize("level", [1, 10, -2])
      @pytest.mark.parametrize("index", [
          Index(['qux', 'baz', 'foo', 'bar']),
          # Float64Index overrides isin, so must be checked separately
          Float64Index([1.0, 2.0, 3.0, 4.0])])
      def test_isin_level_kwarg_raises_bad_index(self, level, index):
          with tm.assert_raises_regex(IndexError, 'Too many levels'):
              index.isin([], level=level)
  
      @pytest.mark.parametrize("level", [1.0, 'foobar', 'xyzzy', np.nan])
      @pytest.mark.parametrize("index", [
          Index(['qux', 'baz', 'foo', 'bar']),
          Float64Index([1.0, 2.0, 3.0, 4.0])])
      def test_isin_level_kwarg_raises_key(self, level, index):
          with tm.assert_raises_regex(KeyError, 'must be same as name'):
              index.isin([], level=level)
  
      @pytest.mark.parametrize("empty", [[], Series(), np.array([])])
      def test_isin_empty(self, empty):
          # see gh-16991
          index = Index(["a", "b"])
          expected = np.array([False, False])
  
          result = index.isin(empty)
          tm.assert_numpy_array_equal(expected, result)
  
      @pytest.mark.parametrize("values", [
          [1, 2, 3, 4],
          [1., 2., 3., 4.],
          [True, True, True, True],
          ["foo", "bar", "baz", "qux"],
          pd.date_range('2018-01-01', freq='D', periods=4)])
      def test_boolean_cmp(self, values):
          index = Index(values)
          result = (index == values)
          expected = np.array([True, True, True, True], dtype=bool)
  
          tm.assert_numpy_array_equal(result, expected)
  
      @pytest.mark.parametrize("name,level", [
          (None, 0), ('a', 'a')])
      def test_get_level_values(self, name, level):
          expected = self.strIndex.copy()
          if name:
              expected.name = name
  
          result = expected.get_level_values(level)
          tm.assert_index_equal(result, expected)
  
      def test_slice_keep_name(self):
          index = Index(['a', 'b'], name='asdf')
          assert index.name == index[1:].name
  
      # instance attributes of the form self.<name>Index
      @pytest.mark.parametrize('index_kind',
                               ['unicode', 'str', 'date', 'int', 'float'])
      def test_join_self(self, join_type, index_kind):
  
          res = getattr(self, '{0}Index'.format(index_kind))
  
          joined = res.join(res, how=join_type)
          assert res is joined
  
      @pytest.mark.parametrize("method", ['strip', 'rstrip', 'lstrip'])
      def test_str_attribute(self, method):
          # GH9068
          index = Index([' jack', 'jill ', ' jesse ', 'frank'])
          expected = Index([getattr(str, method)(x) for x in index.values])
  
          result = getattr(index.str, method)()
          tm.assert_index_equal(result, expected)
  
      @pytest.mark.parametrize("index", [
          Index(range(5)), tm.makeDateIndex(10),
          MultiIndex.from_tuples([('foo', '1'), ('bar', '3')]),
          PeriodIndex(start='2000', end='2010', freq='A')])
      def test_str_attribute_raises(self, index):
          with tm.assert_raises_regex(AttributeError, 'only use .str accessor'):
              index.str.repeat(2)
  
      @pytest.mark.parametrize("expand,expected", [
          (None, Index([['a', 'b', 'c'], ['d', 'e'], ['f']])),
          (False, Index([['a', 'b', 'c'], ['d', 'e'], ['f']])),
          (True, MultiIndex.from_tuples([('a', 'b', 'c'), ('d', 'e', np.nan),
                                         ('f', np.nan, np.nan)]))])
      def test_str_split(self, expand, expected):
          index = Index(['a b c', 'd e', 'f'])
          if expand is not None:
              result = index.str.split(expand=expand)
          else:
              result = index.str.split()
  
          tm.assert_index_equal(result, expected)
  
      def test_str_bool_return(self):
          # test boolean case, should return np.array instead of boolean Index
          index = Index(['a1', 'a2', 'b1', 'b2'])
          result = index.str.startswith('a')
          expected = np.array([True, True, False, False])
  
          tm.assert_numpy_array_equal(result, expected)
          assert isinstance(result, np.ndarray)
  
      def test_str_bool_series_indexing(self):
          index = Index(['a1', 'a2', 'b1', 'b2'])
          s = Series(range(4), index=index)
  
          result = s[s.index.str.startswith('a')]
          expected = Series(range(2), index=['a1', 'a2'])
          tm.assert_series_equal(result, expected)
  
      @pytest.mark.parametrize("index,expected", [
          (Index(list('abcd')), True), (Index(range(4)), False)])
      def test_tab_completion(self, index, expected):
          # GH 9910
          result = 'str' in dir(index)
          assert result == expected
  
      def test_indexing_doesnt_change_class(self):
          index = Index([1, 2, 3, 'a', 'b', 'c'])
  
          assert index[1:3].identical(pd.Index([2, 3], dtype=np.object_))
          assert index[[0, 1]].identical(pd.Index([1, 2], dtype=np.object_))
  
      def test_outer_join_sort(self):
          left_index = Index(np.random.permutation(15))
          right_index = tm.makeDateIndex(10)
  
          with tm.assert_produces_warning(RuntimeWarning):
              result = left_index.join(right_index, how='outer')
  
          # right_index in this case because DatetimeIndex has join precedence
          # over Int64Index
          with tm.assert_produces_warning(RuntimeWarning):
              expected = right_index.astype(object).union(
                  left_index.astype(object))
  
          tm.assert_index_equal(result, expected)
  
      def test_nan_first_take_datetime(self):
          index = Index([pd.NaT, Timestamp('20130101'), Timestamp('20130102')])
          result = index.take([-1, 0, 1])
          expected = Index([index[-1], index[0], index[1]])
          tm.assert_index_equal(result, expected)
  
      def test_take_fill_value(self):
          # GH 12631
          index = pd.Index(list('ABC'), name='xxx')
          result = index.take(np.array([1, 0, -1]))
          expected = pd.Index(list('BAC'), name='xxx')
          tm.assert_index_equal(result, expected)
  
          # fill_value
          result = index.take(np.array([1, 0, -1]), fill_value=True)
          expected = pd.Index(['B', 'A', np.nan], name='xxx')
          tm.assert_index_equal(result, expected)
  
          # allow_fill=False
          result = index.take(np.array([1, 0, -1]), allow_fill=False,
                              fill_value=True)
          expected = pd.Index(['B', 'A', 'C'], name='xxx')
          tm.assert_index_equal(result, expected)
  
      def test_take_fill_value_none_raises(self):
          index = pd.Index(list('ABC'), name='xxx')
          msg = ('When allow_fill=True and fill_value is not None, '
                 'all indices must be >= -1')
  
          with tm.assert_raises_regex(ValueError, msg):
              index.take(np.array([1, 0, -2]), fill_value=True)
          with tm.assert_raises_regex(ValueError, msg):
              index.take(np.array([1, 0, -5]), fill_value=True)
  
      def test_take_bad_bounds_raises(self):
          index = pd.Index(list('ABC'), name='xxx')
          with tm.assert_raises_regex(IndexError, 'out of bounds'):
              index.take(np.array([1, -5]))
  
      @pytest.mark.parametrize("name", [None, 'foobar'])
      @pytest.mark.parametrize("labels", [
          [], np.array([]), ['A', 'B', 'C'], ['C', 'B', 'A'],
          np.array(['A', 'B', 'C']), np.array(['C', 'B', 'A']),
          # Must preserve name even if dtype changes
          pd.date_range('20130101', periods=3).values,
          pd.date_range('20130101', periods=3).tolist()])
      def test_reindex_preserves_name_if_target_is_list_or_ndarray(self, name,
                                                                   labels):
          # GH6552
          index = pd.Index([0, 1, 2])
          index.name = name
          assert index.reindex(labels)[0].name == name
  
      @pytest.mark.parametrize("labels", [
          [], np.array([]), np.array([], dtype=np.int64)])
      def test_reindex_preserves_type_if_target_is_empty_list_or_array(self,
                                                                       labels):
          # GH7774
          index = pd.Index(list('abc'))
          assert index.reindex(labels)[0].dtype.type == np.object_
  
      @pytest.mark.parametrize("labels,dtype", [
          (pd.Int64Index([]), np.int64),
          (pd.Float64Index([]), np.float64),
          (pd.DatetimeIndex([]), np.datetime64)])
      def test_reindex_doesnt_preserve_type_if_target_is_empty_index(self,
                                                                     labels,
                                                                     dtype):
          # GH7774
          index = pd.Index(list('abc'))
          assert index.reindex(labels)[0].dtype.type == dtype
  
      def test_reindex_no_type_preserve_target_empty_mi(self):
          index = pd.Index(list('abc'))
          result = index.reindex(pd.MultiIndex(
              [pd.Int64Index([]), pd.Float64Index([])], [[], []]))[0]
          assert result.levels[0].dtype.type == np.int64
          assert result.levels[1].dtype.type == np.float64
  
      def test_groupby(self):
          index = Index(range(5))
          result = index.groupby(np.array([1, 1, 2, 2, 2]))
          expected = {1: pd.Index([0, 1]), 2: pd.Index([2, 3, 4])}
  
          tm.assert_dict_equal(result, expected)
  
      @pytest.mark.parametrize("mi,expected", [
          (MultiIndex.from_tuples([(1, 2), (4, 5)]), np.array([True, True])),
          (MultiIndex.from_tuples([(1, 2), (4, 6)]), np.array([True, False]))])
      def test_equals_op_multiindex(self, mi, expected):
          # GH9785
          # test comparisons of multiindex
          df = pd.read_csv(StringIO('a,b,c\n1,2,3\n4,5,6'), index_col=[0, 1])
  
          result = df.index == mi
          tm.assert_numpy_array_equal(result, expected)
  
      def test_equals_op_multiindex_identify(self):
          df = pd.read_csv(StringIO('a,b,c\n1,2,3\n4,5,6'), index_col=[0, 1])
  
          result = df.index == df.index
          expected = np.array([True, True])
          tm.assert_numpy_array_equal(result, expected)
  
      @pytest.mark.parametrize("index", [
          MultiIndex.from_tuples([(1, 2), (4, 5), (8, 9)]),
          Index(['foo', 'bar', 'baz'])])
      def test_equals_op_mismatched_multiindex_raises(self, index):
          df = pd.read_csv(StringIO('a,b,c\n1,2,3\n4,5,6'), index_col=[0, 1])
  
          with tm.assert_raises_regex(ValueError, "Lengths must match"):
              df.index == index
  
      def test_equals_op_index_vs_mi_same_length(self):
          mi = MultiIndex.from_tuples([(1, 2), (4, 5), (8, 9)])
          index = Index(['foo', 'bar', 'baz'])
  
          result = mi == index
          expected = np.array([False, False, False])
          tm.assert_numpy_array_equal(result, expected)
  
      @pytest.mark.parametrize("dt_conv", [
          pd.to_datetime, pd.to_timedelta])
      def test_dt_conversion_preserves_name(self, dt_conv):
          # GH 10875
          index = pd.Index(['01:02:03', '01:02:04'], name='label')
          assert index.name == dt_conv(index).name
  
      @pytest.mark.skipif(not PY3, reason="compat test")
      @pytest.mark.parametrize("index,expected", [
          # ASCII
          # short
          (pd.Index(['a', 'bb', 'ccc']),
           u"""Index(['a', 'bb', 'ccc'], dtype='object')"""),
          # multiple lines
          (pd.Index(['a', 'bb', 'ccc'] * 10),
           u"""\
  Index(['a', 'bb', 'ccc', 'a', 'bb', 'ccc', 'a', 'bb', 'ccc', 'a', 'bb', 'ccc',
         'a', 'bb', 'ccc', 'a', 'bb', 'ccc', 'a', 'bb', 'ccc', 'a', 'bb', 'ccc',
         'a', 'bb', 'ccc', 'a', 'bb', 'ccc'],
        dtype='object')"""),
          # truncated
          (pd.Index(['a', 'bb', 'ccc'] * 100),
           u"""\
  Index(['a', 'bb', 'ccc', 'a', 'bb', 'ccc', 'a', 'bb', 'ccc', 'a',
         ...
         'ccc', 'a', 'bb', 'ccc', 'a', 'bb', 'ccc', 'a', 'bb', 'ccc'],
        dtype='object', length=300)"""),
  
          # Non-ASCII
          # short
          (pd.Index([u'あ', u'いい', u'ううう']),
           u"""Index(['あ', 'いい', 'ううう'], dtype='object')"""),
          # multiple lines
          (pd.Index([u'あ', u'いい', u'ううう'] * 10),
           (u"Index(['あ', 'いい', 'ううう', 'あ', 'いい', 'ううう', "
            u"'あ', 'いい', 'ううう', 'あ', 'いい', 'ううう',\n"
            u"       'あ', 'いい', 'ううう', 'あ', 'いい', 'ううう', "
            u"'あ', 'いい', 'ううう', 'あ', 'いい', 'ううう',\n"
            u"       'あ', 'いい', 'ううう', 'あ', 'いい', "
            u"'ううう'],\n"
            u"      dtype='object')")),
          # truncated
          (pd.Index([u'あ', u'いい', u'ううう'] * 100),
           (u"Index(['あ', 'いい', 'ううう', 'あ', 'いい', 'ううう', "
            u"'あ', 'いい', 'ううう', 'あ',\n"
            u"       ...\n"
            u"       'ううう', 'あ', 'いい', 'ううう', 'あ', 'いい', "
            u"'ううう', 'あ', 'いい', 'ううう'],\n"
            u"      dtype='object', length=300)"))])
      def test_string_index_repr(self, index, expected):
          result = repr(index)
          assert result == expected
  
      @pytest.mark.skipif(PY3, reason="compat test")
      @pytest.mark.parametrize("index,expected", [
          # ASCII
          # short
          (pd.Index(['a', 'bb', 'ccc']),
           u"""Index([u'a', u'bb', u'ccc'], dtype='object')"""),
          # multiple lines
          (pd.Index(['a', 'bb', 'ccc'] * 10),
           u"""\
  Index([u'a', u'bb', u'ccc', u'a', u'bb', u'ccc', u'a', u'bb', u'ccc', u'a',
         u'bb', u'ccc', u'a', u'bb', u'ccc', u'a', u'bb', u'ccc', u'a', u'bb',
         u'ccc', u'a', u'bb', u'ccc', u'a', u'bb', u'ccc', u'a', u'bb', u'ccc'],
        dtype='object')"""),
          # truncated
          (pd.Index(['a', 'bb', 'ccc'] * 100),
           u"""\
  Index([u'a', u'bb', u'ccc', u'a', u'bb', u'ccc', u'a', u'bb', u'ccc', u'a',
         ...
         u'ccc', u'a', u'bb', u'ccc', u'a', u'bb', u'ccc', u'a', u'bb', u'ccc'],
        dtype='object', length=300)"""),
  
          # Non-ASCII
          # short
          (pd.Index([u'あ', u'いい', u'ううう']),
           u"""Index([u'あ', u'いい', u'ううう'], dtype='object')"""),
          # multiple lines
          (pd.Index([u'あ', u'いい', u'ううう'] * 10),
           (u"Index([u'あ', u'いい', u'ううう', u'あ', u'いい', "
            u"u'ううう', u'あ', u'いい', u'ううう', u'あ',\n"
            u"       u'いい', u'ううう', u'あ', u'いい', u'ううう', "
            u"u'あ', u'いい', u'ううう', u'あ', u'いい',\n"
            u"       u'ううう', u'あ', u'いい', u'ううう', u'あ', "
            u"u'いい', u'ううう', u'あ', u'いい', u'ううう'],\n"
            u"      dtype='object')")),
          # truncated
          (pd.Index([u'あ', u'いい', u'ううう'] * 100),
           (u"Index([u'あ', u'いい', u'ううう', u'あ', u'いい', "
            u"u'ううう', u'あ', u'いい', u'ううう', u'あ',\n"
            u"       ...\n"
            u"       u'ううう', u'あ', u'いい', u'ううう', u'あ', "
            u"u'いい', u'ううう', u'あ', u'いい', u'ううう'],\n"
            u"      dtype='object', length=300)"))])
      def test_string_index_repr_compat(self, index, expected):
          result = unicode(index)  # noqa
          assert result == expected
  
      @pytest.mark.skipif(not PY3, reason="compat test")
      @pytest.mark.parametrize("index,expected", [
          # short
          (pd.Index([u'あ', u'いい', u'ううう']),
           (u"Index(['あ', 'いい', 'ううう'], "
            u"dtype='object')")),
          # multiple lines
          (pd.Index([u'あ', u'いい', u'ううう'] * 10),
           (u"Index(['あ', 'いい', 'ううう', 'あ', 'いい', "
            u"'ううう', 'あ', 'いい', 'ううう',\n"
            u"       'あ', 'いい', 'ううう', 'あ', 'いい', "
            u"'ううう', 'あ', 'いい', 'ううう',\n"
            u"       'あ', 'いい', 'ううう', 'あ', 'いい', "
            u"'ううう', 'あ', 'いい', 'ううう',\n"
            u"       'あ', 'いい', 'ううう'],\n"
            u"      dtype='object')""")),
          # truncated
          (pd.Index([u'あ', u'いい', u'ううう'] * 100),
           (u"Index(['あ', 'いい', 'ううう', 'あ', 'いい', "
            u"'ううう', 'あ', 'いい', 'ううう',\n"
            u"       'あ',\n"
            u"       ...\n"
            u"       'ううう', 'あ', 'いい', 'ううう', 'あ', "
            u"'いい', 'ううう', 'あ', 'いい',\n"
            u"       'ううう'],\n"
            u"      dtype='object', length=300)"))])
      def test_string_index_repr_with_unicode_option(self, index, expected):
          # Enable Unicode option -----------------------------------------
          with cf.option_context('display.unicode.east_asian_width', True):
              result = repr(index)
              assert result == expected
  
      @pytest.mark.skipif(PY3, reason="compat test")
      @pytest.mark.parametrize("index,expected", [
          # short
          (pd.Index([u'あ', u'いい', u'ううう']),
           (u"Index([u'あ', u'いい', u'ううう'], "
            u"dtype='object')")),
          # multiple lines
          (pd.Index([u'あ', u'いい', u'ううう'] * 10),
           (u"Index([u'あ', u'いい', u'ううう', u'あ', u'いい', "
            u"u'ううう', u'あ', u'いい',\n"
            u"       u'ううう', u'あ', u'いい', u'ううう', "
            u"u'あ', u'いい', u'ううう', u'あ',\n"
            u"       u'いい', u'ううう', u'あ', u'いい', "
            u"u'ううう', u'あ', u'いい',\n"
            u"       u'ううう', u'あ', u'いい', u'ううう', "
            u"u'あ', u'いい', u'ううう'],\n"
            u"      dtype='object')")),
          # truncated
          (pd.Index([u'あ', u'いい', u'ううう'] * 100),
           (u"Index([u'あ', u'いい', u'ううう', u'あ', u'いい', "
            u"u'ううう', u'あ', u'いい',\n"
            u"       u'ううう', u'あ',\n"
            u"       ...\n"
            u"       u'ううう', u'あ', u'いい', u'ううう', "
            u"u'あ', u'いい', u'ううう', u'あ',\n"
            u"       u'いい', u'ううう'],\n"
            u"      dtype='object', length=300)"))])
      def test_string_index_repr_with_unicode_option_compat(self, index,
                                                            expected):
          # Enable Unicode option -----------------------------------------
          with cf.option_context('display.unicode.east_asian_width', True):
              result = unicode(index)  # noqa
              assert result == expected
  
      @pytest.mark.parametrize('dtype', [np.int64, np.float64])
      @pytest.mark.parametrize('delta', [1, 0, -1])
      def test_addsub_arithmetic(self, dtype, delta):
          # GH 8142
          delta = dtype(delta)
          index = pd.Index([10, 11, 12], dtype=dtype)
          result = index + delta
          expected = pd.Index(index.values + delta, dtype=dtype)
          tm.assert_index_equal(result, expected)
  
          # this subtraction used to fail
          result = index - delta
          expected = pd.Index(index.values - delta, dtype=dtype)
          tm.assert_index_equal(result, expected)
  
          tm.assert_index_equal(index + index, 2 * index)
          tm.assert_index_equal(index - index, 0 * index)
          assert not (index - index).empty
  
      def test_iadd_preserves_name(self):
          # GH#17067, GH#19723 __iadd__ and __isub__ should preserve index name
          ser = pd.Series([1, 2, 3])
          ser.index.name = 'foo'
  
          ser.index += 1
          assert ser.index.name == "foo"
  
          ser.index -= 1
          assert ser.index.name == "foo"
  
      def test_cached_properties_not_settable(self):
          index = pd.Index([1, 2, 3])
          with tm.assert_raises_regex(AttributeError, "Can't set attribute"):
              index.is_unique = False
  
      def test_get_duplicates_deprecated(self):
          index = pd.Index([1, 2, 3])
          with tm.assert_produces_warning(FutureWarning):
              index.get_duplicates()
  
      def test_tab_complete_warning(self, ip):
          # https://github.com/pandas-dev/pandas/issues/16409
          pytest.importorskip('IPython', minversion="6.0.0")
          from IPython.core.completer import provisionalcompleter
  
          code = "import pandas as pd; idx = pd.Index([1, 2])"
          ip.run_code(code)
          with tm.assert_produces_warning(None):
              with provisionalcompleter('ignore'):
                  list(ip.Completer.completions('idx.', 4))
  
  
  class TestMixedIntIndex(Base):
      # Mostly the tests from common.py for which the results differ
      # in py2 and py3 because ints and strings are uncomparable in py3
      # (GH 13514)
  
      _holder = Index
  
      def setup_method(self, method):
          self.indices = dict(mixedIndex=Index([0, 'a', 1, 'b', 2, 'c']))
          self.setup_indices()
  
      def create_index(self):
          return self.mixedIndex
  
      def test_argsort(self):
          index = self.create_index()
          if PY36:
              with tm.assert_raises_regex(TypeError, "'>|<' not supported"):
                  result = index.argsort()
          elif PY3:
              with tm.assert_raises_regex(TypeError, "unorderable types"):
                  result = index.argsort()
          else:
              result = index.argsort()
              expected = np.array(index).argsort()
              tm.assert_numpy_array_equal(result, expected, check_dtype=False)
  
      def test_numpy_argsort(self):
          index = self.create_index()
          if PY36:
              with tm.assert_raises_regex(TypeError, "'>|<' not supported"):
                  result = np.argsort(index)
          elif PY3:
              with tm.assert_raises_regex(TypeError, "unorderable types"):
                  result = np.argsort(index)
          else:
              result = np.argsort(index)
              expected = index.argsort()
              tm.assert_numpy_array_equal(result, expected)
  
      def test_copy_name(self):
          # Check that "name" argument passed at initialization is honoured
          # GH12309
          index = self.create_index()
  
          first = index.__class__(index, copy=True, name='mario')
          second = first.__class__(first, copy=False)
  
          # Even though "copy=False", we want a new object.
          assert first is not second
          tm.assert_index_equal(first, second)
  
          assert first.name == 'mario'
          assert second.name == 'mario'
  
          s1 = Series(2, index=first)
          s2 = Series(3, index=second[:-1])
  
          warning_type = RuntimeWarning if PY3 else None
          with tm.assert_produces_warning(warning_type):
              # Python 3: Unorderable types
              s3 = s1 * s2
  
          assert s3.index.name == 'mario'
  
      def test_copy_name2(self):
          # Check that adding a "name" parameter to the copy is honored
          # GH14302
          index = pd.Index([1, 2], name='MyName')
          index1 = index.copy()
  
          tm.assert_index_equal(index, index1)
  
          index2 = index.copy(name='NewName')
          tm.assert_index_equal(index, index2, check_names=False)
          assert index.name == 'MyName'
          assert index2.name == 'NewName'
  
          index3 = index.copy(names=['NewName'])
          tm.assert_index_equal(index, index3, check_names=False)
          assert index.name == 'MyName'
          assert index.names == ['MyName']
          assert index3.name == 'NewName'
          assert index3.names == ['NewName']
  
      def test_union_base(self):
          index = self.create_index()
          first = index[3:]
          second = index[:5]
  
          if PY3:
              # unorderable types
              warn_type = RuntimeWarning
          else:
              warn_type = None
  
          with tm.assert_produces_warning(warn_type):
              result = first.union(second)
  
          expected = Index(['b', 2, 'c', 0, 'a', 1])
          tm.assert_index_equal(result, expected)
  
      @pytest.mark.parametrize("klass", [
          np.array, Series, list])
      def test_union_different_type_base(self, klass):
          # GH 10149
          index = self.create_index()
          first = index[3:]
          second = index[:5]
  
          if PY3:
              # unorderable types
              warn_type = RuntimeWarning
          else:
              warn_type = None
  
          with tm.assert_produces_warning(warn_type):
              result = first.union(klass(second.values))
  
          assert tm.equalContents(result, index)
  
      def test_intersection_base(self):
          # (same results for py2 and py3 but sortedness not tested elsewhere)
          index = self.create_index()
          first = index[:5]
          second = index[:3]
  
          result = first.intersection(second)
          expected = Index([0, 'a', 1])
          tm.assert_index_equal(result, expected)
  
      @pytest.mark.parametrize("klass", [
          np.array, Series, list])
      def test_intersection_different_type_base(self, klass):
          # GH 10149
          index = self.create_index()
          first = index[:5]
          second = index[:3]
  
          result = first.intersection(klass(second.values))
          assert tm.equalContents(result, second)
  
      def test_difference_base(self):
          # (same results for py2 and py3 but sortedness not tested elsewhere)
          index = self.create_index()
          first = index[:4]
          second = index[3:]
  
          result = first.difference(second)
          expected = Index([0, 1, 'a'])
          tm.assert_index_equal(result, expected)
  
      def test_symmetric_difference(self):
          # (same results for py2 and py3 but sortedness not tested elsewhere)
          index = self.create_index()
          first = index[:4]
          second = index[3:]
  
          result = first.symmetric_difference(second)
          expected = Index([0, 1, 2, 'a', 'c'])
          tm.assert_index_equal(result, expected)
  
      def test_logical_compat(self):
          index = self.create_index()
          assert index.all() == index.values.all()
          assert index.any() == index.values.any()
  
      @pytest.mark.parametrize("how", ['any', 'all'])
      @pytest.mark.parametrize("dtype", [
          None, object, 'category'])
      @pytest.mark.parametrize("vals,expected", [
          ([1, 2, 3], [1, 2, 3]), ([1., 2., 3.], [1., 2., 3.]),
          ([1., 2., np.nan, 3.], [1., 2., 3.]),
          (['A', 'B', 'C'], ['A', 'B', 'C']),
          (['A', np.nan, 'B', 'C'], ['A', 'B', 'C'])])
      def test_dropna(self, how, dtype, vals, expected):
          # GH 6194
          index = pd.Index(vals, dtype=dtype)
          result = index.dropna(how=how)
          expected = pd.Index(expected, dtype=dtype)
          tm.assert_index_equal(result, expected)
  
      @pytest.mark.parametrize("how", ['any', 'all'])
      @pytest.mark.parametrize("index,expected", [
          (pd.DatetimeIndex(['2011-01-01', '2011-01-02', '2011-01-03']),
           pd.DatetimeIndex(['2011-01-01', '2011-01-02', '2011-01-03'])),
          (pd.DatetimeIndex(['2011-01-01', '2011-01-02', '2011-01-03', pd.NaT]),
           pd.DatetimeIndex(['2011-01-01', '2011-01-02', '2011-01-03'])),
          (pd.TimedeltaIndex(['1 days', '2 days', '3 days']),
           pd.TimedeltaIndex(['1 days', '2 days', '3 days'])),
          (pd.TimedeltaIndex([pd.NaT, '1 days', '2 days', '3 days', pd.NaT]),
           pd.TimedeltaIndex(['1 days', '2 days', '3 days'])),
          (pd.PeriodIndex(['2012-02', '2012-04', '2012-05'], freq='M'),
           pd.PeriodIndex(['2012-02', '2012-04', '2012-05'], freq='M')),
          (pd.PeriodIndex(['2012-02', '2012-04', 'NaT', '2012-05'], freq='M'),
           pd.PeriodIndex(['2012-02', '2012-04', '2012-05'], freq='M'))])
      def test_dropna_dt_like(self, how, index, expected):
          result = index.dropna(how=how)
          tm.assert_index_equal(result, expected)
  
      def test_dropna_invalid_how_raises(self):
          msg = "invalid how option: xxx"
          with tm.assert_raises_regex(ValueError, msg):
              pd.Index([1, 2, 3]).dropna(how='xxx')
  
      def test_get_combined_index(self):
          result = _get_combined_index([])
          expected = Index([])
          tm.assert_index_equal(result, expected)
  
      def test_repeat(self):
          repeats = 2
          index = pd.Index([1, 2, 3])
          expected = pd.Index([1, 1, 2, 2, 3, 3])
  
          result = index.repeat(repeats)
          tm.assert_index_equal(result, expected)
  
      @pytest.mark.parametrize("index", [
          pd.Index([np.nan]), pd.Index([np.nan, 1]),
          pd.Index([1, 2, np.nan]), pd.Index(['a', 'b', np.nan]),
          pd.to_datetime(['NaT']), pd.to_datetime(['NaT', '2000-01-01']),
          pd.to_datetime(['2000-01-01', 'NaT', '2000-01-02']),
          pd.to_timedelta(['1 day', 'NaT'])])
      def test_is_monotonic_na(self, index):
          assert not index.is_monotonic_increasing
          assert not index.is_monotonic_decreasing
          assert not index._is_strictly_monotonic_increasing
          assert not index._is_strictly_monotonic_decreasing
  
      def test_repr_summary(self):
          with cf.option_context('display.max_seq_items', 10):
              result = repr(pd.Index(np.arange(1000)))
              assert len(result) < 200
              assert "..." in result
  
      @pytest.mark.parametrize("klass", [Series, DataFrame])
      def test_int_name_format(self, klass):
          index = Index(['a', 'b', 'c'], name=0)
          result = klass(lrange(3), index=index)
          assert '0' in repr(result)
  
      def test_print_unicode_columns(self):
          df = pd.DataFrame({u("\u05d0"): [1, 2, 3],
                             "\u05d1": [4, 5, 6],
                             "c": [7, 8, 9]})
          repr(df.columns)  # should not raise UnicodeDecodeError
  
      @pytest.mark.parametrize("func,compat_func", [
          (str, text_type),  # unicode string
          (bytes, str)  # byte string
      ])
      def test_with_unicode(self, func, compat_func):
          index = Index(lrange(1000))
  
          if PY3:
              func(index)
          else:
              compat_func(index)
  
      def test_intersect_str_dates(self):
          dt_dates = [datetime(2012, 2, 9), datetime(2012, 2, 22)]
  
          index1 = Index(dt_dates, dtype=object)
          index2 = Index(['aa'], dtype=object)
          result = index2.intersection(index1)
  
          expected = Index([], dtype=object)
          tm.assert_index_equal(result, expected)
  
      @pytest.mark.parametrize('op', [operator.eq, operator.ne,
                                      operator.gt, operator.ge,
                                      operator.lt, operator.le])
      def test_comparison_tzawareness_compat(self, op):
          # GH#18162
          dr = pd.date_range('2016-01-01', periods=6)
          dz = dr.tz_localize('US/Pacific')
  
          # Check that there isn't a problem aware-aware and naive-naive do not
          # raise
          naive_series = Series(dr)
          aware_series = Series(dz)
          with pytest.raises(TypeError):
              op(dz, naive_series)
          with pytest.raises(TypeError):
              op(dr, aware_series)
  
          # TODO: implement _assert_tzawareness_compat for the reverse
          # comparison with the Series on the left-hand side
  
  
  class TestIndexUtils(object):
  
      @pytest.mark.parametrize('data, names, expected', [
          ([[1, 2, 3]], None, Index([1, 2, 3])),
          ([[1, 2, 3]], ['name'], Index([1, 2, 3], name='name')),
          ([['a', 'a'], ['c', 'd']], None,
           MultiIndex([['a'], ['c', 'd']], [[0, 0], [0, 1]])),
          ([['a', 'a'], ['c', 'd']], ['L1', 'L2'],
           MultiIndex([['a'], ['c', 'd']], [[0, 0], [0, 1]],
                      names=['L1', 'L2'])),
      ])
      def test_ensure_index_from_sequences(self, data, names, expected):
          result = ensure_index_from_sequences(data, names)
          tm.assert_index_equal(result, expected)
  
  
  @pytest.mark.parametrize('opname', ['eq', 'ne', 'le', 'lt', 'ge', 'gt',
                                      'add', 'radd', 'sub', 'rsub',
                                      'mul', 'rmul', 'truediv', 'rtruediv',
                                      'floordiv', 'rfloordiv',
                                      'pow', 'rpow', 'mod', 'divmod'])
  def test_generated_op_names(opname, indices):
      index = indices
      if isinstance(index, ABCIndex) and opname == 'rsub':
          # pd.Index.__rsub__ does not exist; though the method does exist
          # for subclasses.  see GH#19723
          return
      opname = '__{name}__'.format(name=opname)
      method = getattr(index, opname)
      assert method.__name__ == opname
  
  
  @pytest.mark.parametrize('index_maker', tm.index_subclass_makers_generator())
  def test_index_subclass_constructor_wrong_kwargs(index_maker):
      # GH #19348
      with tm.assert_raises_regex(TypeError, 'unexpected keyword argument'):
          index_maker(foo='bar')
  