Python pandas.UInt64Index方法代码示例

# 需要导入模块: import pandas [as 别名]
# 或者: from pandas import UInt64Index [as 别名]
def test_constructor(self):
        idx = UInt64Index([1, 2, 3])
        res = Index([1, 2, 3], dtype=np.uint64)
        tm.assert_index_equal(res, idx)

        idx = UInt64Index([1, 2**63])
        res = Index([1, 2**63], dtype=np.uint64)
        tm.assert_index_equal(res, idx)

        idx = UInt64Index([1, 2**63])
        res = Index([1, 2**63])
        tm.assert_index_equal(res, idx)

        idx = Index([-1, 2**63], dtype=object)
        res = Index(np.array([-1, 2**63], dtype=object))
        tm.assert_index_equal(res, idx) 

# 需要导入模块: import pandas [as 别名]
# 或者: from pandas import UInt64Index [as 别名]
def test_get_indexer(self):
        target = UInt64Index(np.arange(10).astype('uint64') * 5 + 2**63)
        indexer = self.index.get_indexer(target)
        expected = np.array([0, -1, 1, 2, 3, 4,
                             -1, -1, -1, -1], dtype=np.intp)
        tm.assert_numpy_array_equal(indexer, expected)

        target = UInt64Index(np.arange(10).astype('uint64') * 5 + 2**63)
        indexer = self.index.get_indexer(target, method='pad')
        expected = np.array([0, 0, 1, 2, 3, 4,
                             4, 4, 4, 4], dtype=np.intp)
        tm.assert_numpy_array_equal(indexer, expected)

        target = UInt64Index(np.arange(10).astype('uint64') * 5 + 2**63)
        indexer = self.index.get_indexer(target, method='backfill')
        expected = np.array([0, 1, 1, 2, 3, 4,
                             -1, -1, -1, -1], dtype=np.intp)
        tm.assert_numpy_array_equal(indexer, expected) 

# 需要导入模块: import pandas [as 别名]
# 或者: from pandas import UInt64Index [as 别名]
def test_map_dictlike(idx, mapper):

    if isinstance(idx, (pd.CategoricalIndex, pd.IntervalIndex)):
        pytest.skip("skipping tests for {}".format(type(idx)))

    identity = mapper(idx.values, idx)

    # we don't infer to UInt64 for a dict
    if isinstance(idx, pd.UInt64Index) and isinstance(identity, dict):
        expected = idx.astype('int64')
    else:
        expected = idx

    result = idx.map(identity)
    tm.assert_index_equal(result, expected)

    # empty mappable
    expected = pd.Index([np.nan] * len(idx))
    result = idx.map(mapper(expected, idx))
    tm.assert_index_equal(result, expected) 

# 需要导入模块: import pandas [as 别名]
# 或者: from pandas import UInt64Index [as 别名]
def test_map_dictlike(self, mapper):

        index = self.create_index()
        if isinstance(index, (pd.CategoricalIndex, pd.IntervalIndex)):
            pytest.skip("skipping tests for {}".format(type(index)))

        identity = mapper(index.values, index)

        # we don't infer to UInt64 for a dict
        if isinstance(index, pd.UInt64Index) and isinstance(identity, dict):
            expected = index.astype('int64')
        else:
            expected = index

        result = index.map(identity)
        tm.assert_index_equal(result, expected)

        # empty mappable
        expected = pd.Index([np.nan] * len(index))
        result = index.map(mapper(expected, index))
        tm.assert_index_equal(result, expected) 

# 需要导入模块: import pandas [as 别名]
# 或者: from pandas import UInt64Index [as 别名]
def test_astype_uint(self):
        arr = timedelta_range('1H', periods=2)
        expected = pd.UInt64Index(
            np.array([3600000000000, 90000000000000], dtype="uint64")
        )

        tm.assert_index_equal(arr.astype("uint64"), expected)
        tm.assert_index_equal(arr.astype("uint32"), expected) 

# 需要导入模块: import pandas [as 别名]
# 或者: from pandas import UInt64Index [as 别名]
def test_hasnans_isnans(self):
        # GH 11343, added tests for hasnans / isnans
        for name, index in self.indices.items():
            if isinstance(index, MultiIndex):
                pass
            else:
                idx = index.copy()

                # cases in indices doesn't include NaN
                expected = np.array([False] * len(idx), dtype=bool)
                tm.assert_numpy_array_equal(idx._isnan, expected)
                assert idx.hasnans is False

                idx = index.copy()
                values = np.asarray(idx.values)

                if len(index) == 0:
                    continue
                elif isinstance(index, DatetimeIndexOpsMixin):
                    values[1] = iNaT
                elif isinstance(index, (Int64Index, UInt64Index)):
                    continue
                else:
                    values[1] = np.nan

                if isinstance(index, PeriodIndex):
                    idx = index.__class__(values, freq=index.freq)
                else:
                    idx = index.__class__(values)

                expected = np.array([False] * len(idx), dtype=bool)
                expected[1] = True
                tm.assert_numpy_array_equal(idx._isnan, expected)
                assert idx.hasnans is True 

# 需要导入模块: import pandas [as 别名]
# 或者: from pandas import UInt64Index [as 别名]
def test_fillna(self):
        # GH 11343
        for name, index in self.indices.items():
            if len(index) == 0:
                pass
            elif isinstance(index, MultiIndex):
                idx = index.copy()
                msg = "isna is not defined for MultiIndex"
                with pytest.raises(NotImplementedError, match=msg):
                    idx.fillna(idx[0])
            else:
                idx = index.copy()
                result = idx.fillna(idx[0])
                tm.assert_index_equal(result, idx)
                assert result is not idx

                msg = "'value' must be a scalar, passed: "
                with pytest.raises(TypeError, match=msg):
                    idx.fillna([idx[0]])

                idx = index.copy()
                values = np.asarray(idx.values)

                if isinstance(index, DatetimeIndexOpsMixin):
                    values[1] = iNaT
                elif isinstance(index, (Int64Index, UInt64Index)):
                    continue
                else:
                    values[1] = np.nan

                if isinstance(index, PeriodIndex):
                    idx = index.__class__(values, freq=index.freq)
                else:
                    idx = index.__class__(values)

                expected = np.array([False] * len(idx), dtype=bool)
                expected[1] = True
                tm.assert_numpy_array_equal(idx._isnan, expected)
                assert idx.hasnans is True 

# 需要导入模块: import pandas [as 别名]
# 或者: from pandas import UInt64Index [as 别名]
def test_map(self):
        # callable
        index = self.create_index()

        # we don't infer UInt64
        if isinstance(index, pd.UInt64Index):
            expected = index.astype('int64')
        else:
            expected = index

        result = index.map(lambda x: x)
        tm.assert_index_equal(result, expected) 

# 需要导入模块: import pandas [as 别名]
# 或者: from pandas import UInt64Index [as 别名]
def setup_method(self, method):
        vals = [2**63, 2**63 + 10, 2**63 + 15, 2**63 + 20, 2**63 + 25]
        self.indices = dict(index=UInt64Index(vals),
                            index_dec=UInt64Index(reversed(vals)))
        self.setup_indices() 

# 需要导入模块: import pandas [as 别名]
# 或者: from pandas import UInt64Index [as 别名]
def create_index(self):
        return UInt64Index(np.arange(5, dtype='uint64')) 

# 需要导入模块: import pandas [as 别名]
# 或者: from pandas import UInt64Index [as 别名]
def test_join_inner(self):
        other = UInt64Index(2**63 + np.array(
            [7, 12, 25, 1, 2, 10], dtype='uint64'))
        other_mono = UInt64Index(2**63 + np.array(
            [1, 2, 7, 10, 12, 25], dtype='uint64'))

        # not monotonic
        res, lidx, ridx = self.index.join(other, how='inner',
                                          return_indexers=True)

        # no guarantee of sortedness, so sort for comparison purposes
        ind = res.argsort()
        res = res.take(ind)
        lidx = lidx.take(ind)
        ridx = ridx.take(ind)

        eres = UInt64Index(2**63 + np.array([10, 25], dtype='uint64'))
        elidx = np.array([1, 4], dtype=np.intp)
        eridx = np.array([5, 2], dtype=np.intp)

        assert isinstance(res, UInt64Index)
        tm.assert_index_equal(res, eres)
        tm.assert_numpy_array_equal(lidx, elidx)
        tm.assert_numpy_array_equal(ridx, eridx)

        # monotonic
        res, lidx, ridx = self.index.join(other_mono, how='inner',
                                          return_indexers=True)

        res2 = self.index.intersection(other_mono)
        tm.assert_index_equal(res, res2)

        elidx = np.array([1, 4], dtype=np.intp)
        eridx = np.array([3, 5], dtype=np.intp)

        assert isinstance(res, UInt64Index)
        tm.assert_index_equal(res, eres)
        tm.assert_numpy_array_equal(lidx, elidx)
        tm.assert_numpy_array_equal(ridx, eridx) 

# 需要导入模块: import pandas [as 别名]
# 或者: from pandas import UInt64Index [as 别名]
def test_join_outer(self):
        other = UInt64Index(2**63 + np.array(
            [7, 12, 25, 1, 2, 10], dtype='uint64'))
        other_mono = UInt64Index(2**63 + np.array(
            [1, 2, 7, 10, 12, 25], dtype='uint64'))

        # not monotonic
        # guarantee of sortedness
        res, lidx, ridx = self.index.join(other, how='outer',
                                          return_indexers=True)
        noidx_res = self.index.join(other, how='outer')
        tm.assert_index_equal(res, noidx_res)

        eres = UInt64Index(2**63 + np.array(
            [0, 1, 2, 7, 10, 12, 15, 20, 25], dtype='uint64'))
        elidx = np.array([0, -1, -1, -1, 1, -1, 2, 3, 4], dtype=np.intp)
        eridx = np.array([-1, 3, 4, 0, 5, 1, -1, -1, 2], dtype=np.intp)

        assert isinstance(res, UInt64Index)
        tm.assert_index_equal(res, eres)
        tm.assert_numpy_array_equal(lidx, elidx)
        tm.assert_numpy_array_equal(ridx, eridx)

        # monotonic
        res, lidx, ridx = self.index.join(other_mono, how='outer',
                                          return_indexers=True)
        noidx_res = self.index.join(other_mono, how='outer')
        tm.assert_index_equal(res, noidx_res)

        elidx = np.array([0, -1, -1, -1, 1, -1, 2, 3, 4], dtype=np.intp)
        eridx = np.array([-1, 0, 1, 2, 3, 4, -1, -1, 5], dtype=np.intp)

        assert isinstance(res, UInt64Index)
        tm.assert_index_equal(res, eres)
        tm.assert_numpy_array_equal(lidx, elidx)
        tm.assert_numpy_array_equal(ridx, eridx) 

# 需要导入模块: import pandas [as 别名]
# 或者: from pandas import UInt64Index [as 别名]
def test_astype_uint(self):
        arr = date_range('2000', periods=2)
        expected = pd.UInt64Index(
            np.array([946684800000000000, 946771200000000000], dtype="uint64")
        )

        tm.assert_index_equal(arr.astype("uint64"), expected)
        tm.assert_index_equal(arr.astype("uint32"), expected) 

# 需要导入模块: import pandas [as 别名]
# 或者: from pandas import UInt64Index [as 别名]
def test_astype_uint(self):
        arr = period_range('2000', periods=2)
        expected = pd.UInt64Index(np.array([10957, 10958], dtype='uint64'))
        tm.assert_index_equal(arr.astype("uint64"), expected)
        tm.assert_index_equal(arr.astype("uint32"), expected) 

# 需要导入模块: import pandas [as 别名]
# 或者: from pandas import UInt64Index [as 别名]
def test_fillna(idx):
    # GH 11343

    # TODO: Remove or Refactor.  Not Implemented for MultiIndex
    for name, index in [('idx', idx), ]:
        if len(index) == 0:
            pass
        elif isinstance(index, MultiIndex):
            idx = index.copy()
            msg = "isna is not defined for MultiIndex"
            with pytest.raises(NotImplementedError, match=msg):
                idx.fillna(idx[0])
        else:
            idx = index.copy()
            result = idx.fillna(idx[0])
            tm.assert_index_equal(result, idx)
            assert result is not idx

            msg = "'value' must be a scalar, passed: "
            with pytest.raises(TypeError, match=msg):
                idx.fillna([idx[0]])

            idx = index.copy()
            values = idx.values

            if isinstance(index, DatetimeIndexOpsMixin):
                values[1] = iNaT
            elif isinstance(index, (Int64Index, UInt64Index)):
                continue
            else:
                values[1] = np.nan

            if isinstance(index, PeriodIndex):
                idx = index.__class__(values, freq=index.freq)
            else:
                idx = index.__class__(values)

            expected = np.array([False] * len(idx), dtype=bool)
            expected[1] = True
            tm.assert_numpy_array_equal(idx._isnan, expected)
            assert idx.hasnans is True