path: root/contrib/python/pandas/py2/pandas/tests/indexing/test_coercion.py

# -*- coding: utf-8 -*-

import itertools

import numpy as np
import pytest

import pandas.compat as compat

import pandas as pd
import pandas.util.testing as tm

###############################################################
# Index / Series common tests which may trigger dtype coercions
###############################################################


@pytest.fixture(autouse=True, scope='class')
def check_comprehensiveness(request):
    # Iterate over combination of dtype, method and klass
    # and ensure that each are contained within a collected test
    cls = request.cls
    combos = itertools.product(cls.klasses, cls.dtypes, [cls.method])

    def has_test(combo):
        klass, dtype, method = combo
        cls_funcs = request.node.session.items
        return any(klass in x.name and dtype in x.name and
                   method in x.name for x in cls_funcs)

    for combo in combos:
        if not has_test(combo):
            msg = 'test method is not defined: {0}, {1}'
            raise AssertionError(msg.format(cls.__name__, combo))

    yield


class CoercionBase(object):

    klasses = ['index', 'series']
    dtypes = ['object', 'int64', 'float64', 'complex128', 'bool',
              'datetime64', 'datetime64tz', 'timedelta64', 'period']

    @property
    def method(self):
        raise NotImplementedError(self)

    def _assert(self, left, right, dtype):
        # explicitly check dtype to avoid any unexpected result
        if isinstance(left, pd.Series):
            tm.assert_series_equal(left, right)
        elif isinstance(left, pd.Index):
            tm.assert_index_equal(left, right)
        else:
            raise NotImplementedError
        assert left.dtype == dtype
        assert right.dtype == dtype


class TestSetitemCoercion(CoercionBase):

    method = 'setitem'

    def _assert_setitem_series_conversion(self, original_series, loc_value,
                                          expected_series, expected_dtype):
        """ test series value's coercion triggered by assignment """
        temp = original_series.copy()
        temp[1] = loc_value
        tm.assert_series_equal(temp, expected_series)
        # check dtype explicitly for sure
        assert temp.dtype == expected_dtype

        # .loc works different rule, temporary disable
        # temp = original_series.copy()
        # temp.loc[1] = loc_value
        # tm.assert_series_equal(temp, expected_series)

    @pytest.mark.parametrize("val,exp_dtype", [
        (1, np.object),
        (1.1, np.object),
        (1 + 1j, np.object),
        (True, np.object)])
    def test_setitem_series_object(self, val, exp_dtype):
        obj = pd.Series(list('abcd'))
        assert obj.dtype == np.object

        exp = pd.Series(['a', val, 'c', 'd'])
        self._assert_setitem_series_conversion(obj, val, exp, exp_dtype)

    @pytest.mark.parametrize("val,exp_dtype", [
        (1, np.int64),
        (1.1, np.float64),
        (1 + 1j, np.complex128),
        (True, np.object)])
    def test_setitem_series_int64(self, val, exp_dtype):
        obj = pd.Series([1, 2, 3, 4])
        assert obj.dtype == np.int64

        if exp_dtype is np.float64:
            exp = pd.Series([1, 1, 3, 4])
            self._assert_setitem_series_conversion(obj, 1.1, exp, np.int64)
            pytest.xfail("GH12747 The result must be float")

        exp = pd.Series([1, val, 3, 4])
        self._assert_setitem_series_conversion(obj, val, exp, exp_dtype)

    @pytest.mark.parametrize("val,exp_dtype", [
        (np.int32(1), np.int8),
        (np.int16(2**9), np.int16)])
    def test_setitem_series_int8(self, val, exp_dtype):
        obj = pd.Series([1, 2, 3, 4], dtype=np.int8)
        assert obj.dtype == np.int8

        if exp_dtype is np.int16:
            exp = pd.Series([1, 0, 3, 4], dtype=np.int8)
            self._assert_setitem_series_conversion(obj, val, exp, np.int8)
            pytest.xfail("BUG: it must be Series([1, 1, 3, 4], dtype=np.int16")

        exp = pd.Series([1, val, 3, 4], dtype=np.int8)
        self._assert_setitem_series_conversion(obj, val, exp, exp_dtype)

    @pytest.mark.parametrize("val,exp_dtype", [
        (1, np.float64),
        (1.1, np.float64),
        (1 + 1j, np.complex128),
        (True, np.object)])
    def test_setitem_series_float64(self, val, exp_dtype):
        obj = pd.Series([1.1, 2.2, 3.3, 4.4])
        assert obj.dtype == np.float64

        exp = pd.Series([1.1, val, 3.3, 4.4])
        self._assert_setitem_series_conversion(obj, val, exp, exp_dtype)

    @pytest.mark.parametrize("val,exp_dtype", [
        (1, np.complex128),
        (1.1, np.complex128),
        (1 + 1j, np.complex128),
        (True, np.object)])
    def test_setitem_series_complex128(self, val, exp_dtype):
        obj = pd.Series([1 + 1j, 2 + 2j, 3 + 3j, 4 + 4j])
        assert obj.dtype == np.complex128

        exp = pd.Series([1 + 1j, val, 3 + 3j, 4 + 4j])
        self._assert_setitem_series_conversion(obj, val, exp, exp_dtype)

    @pytest.mark.parametrize("val,exp_dtype", [
        (1, np.int64),
        (3, np.int64),
        (1.1, np.float64),
        (1 + 1j, np.complex128),
        (True, np.bool)])
    def test_setitem_series_bool(self, val, exp_dtype):
        obj = pd.Series([True, False, True, False])
        assert obj.dtype == np.bool

        if exp_dtype is np.int64:
            exp = pd.Series([True, True, True, False])
            self._assert_setitem_series_conversion(obj, val, exp, np.bool)
            pytest.xfail("TODO_GH12747 The result must be int")
        elif exp_dtype is np.float64:
            exp = pd.Series([True, True, True, False])
            self._assert_setitem_series_conversion(obj, val, exp, np.bool)
            pytest.xfail("TODO_GH12747 The result must be float")
        elif exp_dtype is np.complex128:
            exp = pd.Series([True, True, True, False])
            self._assert_setitem_series_conversion(obj, val, exp, np.bool)
            pytest.xfail("TODO_GH12747 The result must be complex")

        exp = pd.Series([True, val, True, False])
        self._assert_setitem_series_conversion(obj, val, exp, exp_dtype)

    @pytest.mark.parametrize("val,exp_dtype", [
        (pd.Timestamp('2012-01-01'), 'datetime64[ns]'),
        (1, np.object),
        ('x', np.object)])
    def test_setitem_series_datetime64(self, val, exp_dtype):
        obj = pd.Series([pd.Timestamp('2011-01-01'),
                         pd.Timestamp('2011-01-02'),
                         pd.Timestamp('2011-01-03'),
                         pd.Timestamp('2011-01-04')])
        assert obj.dtype == 'datetime64[ns]'

        exp = pd.Series([pd.Timestamp('2011-01-01'),
                         val,
                         pd.Timestamp('2011-01-03'),
                         pd.Timestamp('2011-01-04')])
        self._assert_setitem_series_conversion(obj, val, exp, exp_dtype)

    @pytest.mark.parametrize("val,exp_dtype", [
        (pd.Timestamp('2012-01-01', tz='US/Eastern'),
         'datetime64[ns, US/Eastern]'),
        (pd.Timestamp('2012-01-01', tz='US/Pacific'), np.object),
        (pd.Timestamp('2012-01-01'), np.object),
        (1, np.object)])
    def test_setitem_series_datetime64tz(self, val, exp_dtype):
        tz = 'US/Eastern'
        obj = pd.Series([pd.Timestamp('2011-01-01', tz=tz),
                         pd.Timestamp('2011-01-02', tz=tz),
                         pd.Timestamp('2011-01-03', tz=tz),
                         pd.Timestamp('2011-01-04', tz=tz)])
        assert obj.dtype == 'datetime64[ns, US/Eastern]'

        exp = pd.Series([pd.Timestamp('2011-01-01', tz=tz),
                         val,
                         pd.Timestamp('2011-01-03', tz=tz),
                         pd.Timestamp('2011-01-04', tz=tz)])
        self._assert_setitem_series_conversion(obj, val, exp, exp_dtype)

    @pytest.mark.parametrize("val,exp_dtype", [
        (pd.Timedelta('12 day'), 'timedelta64[ns]'),
        (1, np.object),
        ('x', np.object)])
    def test_setitem_series_timedelta64(self, val, exp_dtype):
        obj = pd.Series([pd.Timedelta('1 day'),
                         pd.Timedelta('2 day'),
                         pd.Timedelta('3 day'),
                         pd.Timedelta('4 day')])
        assert obj.dtype == 'timedelta64[ns]'

        exp = pd.Series([pd.Timedelta('1 day'),
                         val,
                         pd.Timedelta('3 day'),
                         pd.Timedelta('4 day')])
        self._assert_setitem_series_conversion(obj, val, exp, exp_dtype)

    def _assert_setitem_index_conversion(self, original_series, loc_key,
                                         expected_index, expected_dtype):
        """ test index's coercion triggered by assign key """
        temp = original_series.copy()
        temp[loc_key] = 5
        exp = pd.Series([1, 2, 3, 4, 5], index=expected_index)
        tm.assert_series_equal(temp, exp)
        # check dtype explicitly for sure
        assert temp.index.dtype == expected_dtype

        temp = original_series.copy()
        temp.loc[loc_key] = 5
        exp = pd.Series([1, 2, 3, 4, 5], index=expected_index)
        tm.assert_series_equal(temp, exp)
        # check dtype explicitly for sure
        assert temp.index.dtype == expected_dtype

    @pytest.mark.parametrize("val,exp_dtype", [
        ('x', np.object),
        (5, IndexError),
        (1.1, np.object)])
    def test_setitem_index_object(self, val, exp_dtype):
        obj = pd.Series([1, 2, 3, 4], index=list('abcd'))
        assert obj.index.dtype == np.object

        if exp_dtype is IndexError:
            temp = obj.copy()
            with pytest.raises(exp_dtype):
                temp[5] = 5
        else:
            exp_index = pd.Index(list('abcd') + [val])
            self._assert_setitem_index_conversion(obj, val, exp_index,
                                                  exp_dtype)

    @pytest.mark.parametrize("val,exp_dtype", [
        (5, np.int64),
        (1.1, np.float64),
        ('x', np.object)])
    def test_setitem_index_int64(self, val, exp_dtype):
        obj = pd.Series([1, 2, 3, 4])
        assert obj.index.dtype == np.int64

        exp_index = pd.Index([0, 1, 2, 3, val])
        self._assert_setitem_index_conversion(obj, val, exp_index, exp_dtype)

    @pytest.mark.parametrize("val,exp_dtype", [
        (5, IndexError),
        (5.1, np.float64),
        ('x', np.object)])
    def test_setitem_index_float64(self, val, exp_dtype):
        obj = pd.Series([1, 2, 3, 4], index=[1.1, 2.1, 3.1, 4.1])
        assert obj.index.dtype == np.float64

        if exp_dtype is IndexError:
            # float + int -> int
            temp = obj.copy()
            with pytest.raises(exp_dtype):
                temp[5] = 5
            pytest.xfail("TODO_GH12747 The result must be float")

        exp_index = pd.Index([1.1, 2.1, 3.1, 4.1, val])
        self._assert_setitem_index_conversion(obj, val, exp_index, exp_dtype)

    def test_setitem_series_period(self):
        pass

    def test_setitem_index_complex128(self):
        pass

    def test_setitem_index_bool(self):
        pass

    def test_setitem_index_datetime64(self):
        pass

    def test_setitem_index_datetime64tz(self):
        pass

    def test_setitem_index_timedelta64(self):
        pass

    def test_setitem_index_period(self):
        pass


class TestInsertIndexCoercion(CoercionBase):

    klasses = ['index']
    method = 'insert'

    def _assert_insert_conversion(self, original, value,
                                  expected, expected_dtype):
        """ test coercion triggered by insert """
        target = original.copy()
        res = target.insert(1, value)
        tm.assert_index_equal(res, expected)
        assert res.dtype == expected_dtype

    @pytest.mark.parametrize("insert, coerced_val, coerced_dtype", [
        (1, 1, np.object),
        (1.1, 1.1, np.object),
        (False, False, np.object),
        ('x', 'x', np.object)])
    def test_insert_index_object(self, insert, coerced_val, coerced_dtype):
        obj = pd.Index(list('abcd'))
        assert obj.dtype == np.object

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

    @pytest.mark.parametrize("insert, coerced_val, coerced_dtype", [
        (1, 1, np.int64),
        (1.1, 1.1, np.float64),
        (False, 0, np.int64),
        ('x', 'x', np.object)])
    def test_insert_index_int64(self, insert, coerced_val, coerced_dtype):
        obj = pd.Int64Index([1, 2, 3, 4])
        assert obj.dtype == np.int64

        exp = pd.Index([1, coerced_val, 2, 3, 4])
        self._assert_insert_conversion(obj, insert, exp, coerced_dtype)

    @pytest.mark.parametrize("insert, coerced_val, coerced_dtype", [
        (1, 1., np.float64),
        (1.1, 1.1, np.float64),
        (False, 0., np.float64),
        ('x', 'x', np.object)])
    def test_insert_index_float64(self, insert, coerced_val, coerced_dtype):
        obj = pd.Float64Index([1., 2., 3., 4.])
        assert obj.dtype == np.float64

        exp = pd.Index([1., coerced_val, 2., 3., 4.])
        self._assert_insert_conversion(obj, insert, exp, coerced_dtype)

    @pytest.mark.parametrize('fill_val,exp_dtype', [
        (pd.Timestamp('2012-01-01'), 'datetime64[ns]'),
        (pd.Timestamp('2012-01-01', tz='US/Eastern'),
         'datetime64[ns, US/Eastern]')],
        ids=['datetime64', 'datetime64tz'])
    def test_insert_index_datetimes(self, fill_val, exp_dtype):
        obj = pd.DatetimeIndex(['2011-01-01', '2011-01-02', '2011-01-03',
                                '2011-01-04'], tz=fill_val.tz)
        assert obj.dtype == exp_dtype

        exp = pd.DatetimeIndex(['2011-01-01', fill_val.date(), '2011-01-02',
                                '2011-01-03', '2011-01-04'], tz=fill_val.tz)
        self._assert_insert_conversion(obj, fill_val, exp, exp_dtype)

        msg = "Passed item and index have different timezone"
        if fill_val.tz:
            with pytest.raises(ValueError, match=msg):
                obj.insert(1, pd.Timestamp('2012-01-01'))

        with pytest.raises(ValueError, match=msg):
            obj.insert(1, pd.Timestamp('2012-01-01', tz='Asia/Tokyo'))

        msg = "cannot insert DatetimeIndex with incompatible label"
        with pytest.raises(TypeError, match=msg):
            obj.insert(1, 1)

        pytest.xfail("ToDo: must coerce to object")

    def test_insert_index_timedelta64(self):
        obj = pd.TimedeltaIndex(['1 day', '2 day', '3 day', '4 day'])
        assert obj.dtype == 'timedelta64[ns]'

        # timedelta64 + timedelta64 => timedelta64
        exp = pd.TimedeltaIndex(['1 day', '10 day', '2 day', '3 day', '4 day'])
        self._assert_insert_conversion(obj, pd.Timedelta('10 day'),
                                       exp, 'timedelta64[ns]')

        # ToDo: must coerce to object
        msg = "cannot insert TimedeltaIndex with incompatible label"
        with pytest.raises(TypeError, match=msg):
            obj.insert(1, pd.Timestamp('2012-01-01'))

        # ToDo: must coerce to object
        msg = "cannot insert TimedeltaIndex with incompatible label"
        with pytest.raises(TypeError, match=msg):
            obj.insert(1, 1)

    @pytest.mark.parametrize("insert, coerced_val, coerced_dtype", [
        (pd.Period('2012-01', freq='M'), '2012-01', 'period[M]'),
        (pd.Timestamp('2012-01-01'), pd.Timestamp('2012-01-01'), np.object),
        (1, 1, np.object),
        ('x', 'x', np.object)])
    def test_insert_index_period(self, insert, coerced_val, coerced_dtype):
        obj = pd.PeriodIndex(['2011-01', '2011-02', '2011-03', '2011-04'],
                             freq='M')
        assert obj.dtype == 'period[M]'

        if isinstance(insert, pd.Period):
            index_type = pd.PeriodIndex
        else:
            index_type = pd.Index

        exp = index_type([pd.Period('2011-01', freq='M'),
                          coerced_val,
                          pd.Period('2011-02', freq='M'),
                          pd.Period('2011-03', freq='M'),
                          pd.Period('2011-04', freq='M')], freq='M')
        self._assert_insert_conversion(obj, insert, exp, coerced_dtype)

    def test_insert_index_complex128(self):
        pass

    def test_insert_index_bool(self):
        pass


class TestWhereCoercion(CoercionBase):

    method = 'where'

    def _assert_where_conversion(self, original, cond, values,
                                 expected, expected_dtype):
        """ test coercion triggered by where """
        target = original.copy()
        res = target.where(cond, values)
        self._assert(res, expected, expected_dtype)

    @pytest.mark.parametrize("klass", [pd.Series, pd.Index],
                             ids=['series', 'index'])
    @pytest.mark.parametrize("fill_val,exp_dtype", [
        (1, np.object),
        (1.1, np.object),
        (1 + 1j, np.object),
        (True, np.object)])
    def test_where_object(self, klass, fill_val, exp_dtype):
        obj = klass(list('abcd'))
        assert obj.dtype == np.object
        cond = klass([True, False, True, False])

        if fill_val is True and klass is pd.Series:
            ret_val = 1
        else:
            ret_val = fill_val

        exp = klass(['a', ret_val, 'c', ret_val])
        self._assert_where_conversion(obj, cond, fill_val, exp, exp_dtype)

        if fill_val is True:
            values = klass([True, False, True, True])
        else:
            values = klass(fill_val * x for x in [5, 6, 7, 8])

        exp = klass(['a', values[1], 'c', values[3]])
        self._assert_where_conversion(obj, cond, values, exp, exp_dtype)

    @pytest.mark.parametrize("klass", [pd.Series, pd.Index],
                             ids=['series', 'index'])
    @pytest.mark.parametrize("fill_val,exp_dtype", [
        (1, np.int64),
        (1.1, np.float64),
        (1 + 1j, np.complex128),
        (True, np.object)])
    def test_where_int64(self, klass, fill_val, exp_dtype):
        if klass is pd.Index and exp_dtype is np.complex128:
            pytest.skip("Complex Index not supported")
        obj = klass([1, 2, 3, 4])
        assert obj.dtype == np.int64
        cond = klass([True, False, True, False])

        exp = klass([1, fill_val, 3, fill_val])
        self._assert_where_conversion(obj, cond, fill_val, exp, exp_dtype)

        if fill_val is True:
            values = klass([True, False, True, True])
        else:
            values = klass(x * fill_val for x in [5, 6, 7, 8])
        exp = klass([1, values[1], 3, values[3]])
        self._assert_where_conversion(obj, cond, values, exp, exp_dtype)

    @pytest.mark.parametrize("klass", [pd.Series, pd.Index],
                             ids=['series', 'index'])
    @pytest.mark.parametrize("fill_val, exp_dtype", [
        (1, np.float64),
        (1.1, np.float64),
        (1 + 1j, np.complex128),
        (True, np.object)])
    def test_where_float64(self, klass, fill_val, exp_dtype):
        if klass is pd.Index and exp_dtype is np.complex128:
            pytest.skip("Complex Index not supported")
        obj = klass([1.1, 2.2, 3.3, 4.4])
        assert obj.dtype == np.float64
        cond = klass([True, False, True, False])

        exp = klass([1.1, fill_val, 3.3, fill_val])
        self._assert_where_conversion(obj, cond, fill_val, exp, exp_dtype)

        if fill_val is True:
            values = klass([True, False, True, True])
        else:
            values = klass(x * fill_val for x in [5, 6, 7, 8])
        exp = klass([1.1, values[1], 3.3, values[3]])
        self._assert_where_conversion(obj, cond, values, exp, exp_dtype)

    @pytest.mark.parametrize("fill_val,exp_dtype", [
        (1, np.complex128),
        (1.1, np.complex128),
        (1 + 1j, np.complex128),
        (True, np.object)])
    def test_where_series_complex128(self, fill_val, exp_dtype):
        obj = pd.Series([1 + 1j, 2 + 2j, 3 + 3j, 4 + 4j])
        assert obj.dtype == np.complex128
        cond = pd.Series([True, False, True, False])

        exp = pd.Series([1 + 1j, fill_val, 3 + 3j, fill_val])
        self._assert_where_conversion(obj, cond, fill_val, exp, exp_dtype)

        if fill_val is True:
            values = pd.Series([True, False, True, True])
        else:
            values = pd.Series(x * fill_val for x in [5, 6, 7, 8])
        exp = pd.Series([1 + 1j, values[1], 3 + 3j, values[3]])
        self._assert_where_conversion(obj, cond, values, exp, exp_dtype)

    @pytest.mark.parametrize("fill_val,exp_dtype", [
        (1, np.object),
        (1.1, np.object),
        (1 + 1j, np.object),
        (True, np.bool)])
    def test_where_series_bool(self, fill_val, exp_dtype):

        obj = pd.Series([True, False, True, False])
        assert obj.dtype == np.bool
        cond = pd.Series([True, False, True, False])

        exp = pd.Series([True, fill_val, True, fill_val])
        self._assert_where_conversion(obj, cond, fill_val, exp, exp_dtype)

        if fill_val is True:
            values = pd.Series([True, False, True, True])
        else:
            values = pd.Series(x * fill_val for x in [5, 6, 7, 8])
        exp = pd.Series([True, values[1], True, values[3]])
        self._assert_where_conversion(obj, cond, values, exp, exp_dtype)

    @pytest.mark.parametrize("fill_val,exp_dtype", [
        (pd.Timestamp('2012-01-01'), 'datetime64[ns]'),
        (pd.Timestamp('2012-01-01', tz='US/Eastern'), np.object)],
        ids=['datetime64', 'datetime64tz'])
    def test_where_series_datetime64(self, fill_val, exp_dtype):
        obj = pd.Series([pd.Timestamp('2011-01-01'),
                         pd.Timestamp('2011-01-02'),
                         pd.Timestamp('2011-01-03'),
                         pd.Timestamp('2011-01-04')])
        assert obj.dtype == 'datetime64[ns]'
        cond = pd.Series([True, False, True, False])

        exp = pd.Series([pd.Timestamp('2011-01-01'), fill_val,
                         pd.Timestamp('2011-01-03'), fill_val])
        self._assert_where_conversion(obj, cond, fill_val, exp, exp_dtype)

        values = pd.Series(pd.date_range(fill_val, periods=4))
        if fill_val.tz:
            exp = pd.Series([pd.Timestamp('2011-01-01'),
                             pd.Timestamp('2012-01-02 00:00', tz='US/Eastern'),
                             pd.Timestamp('2011-01-03'),
                             pd.Timestamp('2012-01-04 00:00',
                                          tz='US/Eastern')])
            self._assert_where_conversion(obj, cond, values, exp, exp_dtype)

        exp = pd.Series([pd.Timestamp('2011-01-01'), values[1],
                         pd.Timestamp('2011-01-03'), values[3]])
        self._assert_where_conversion(obj, cond, values, exp, exp_dtype)

    def test_where_index_datetime(self):
        fill_val = pd.Timestamp('2012-01-01')
        exp_dtype = 'datetime64[ns]'
        obj = pd.Index([pd.Timestamp('2011-01-01'),
                        pd.Timestamp('2011-01-02'),
                        pd.Timestamp('2011-01-03'),
                        pd.Timestamp('2011-01-04')])
        assert obj.dtype == 'datetime64[ns]'
        cond = pd.Index([True, False, True, False])

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

        values = pd.Index(pd.date_range(fill_val, periods=4))
        exp = pd.Index([pd.Timestamp('2011-01-01'),
                        pd.Timestamp('2012-01-02'),
                        pd.Timestamp('2011-01-03'),
                        pd.Timestamp('2012-01-04')])

        self._assert_where_conversion(obj, cond, values, exp, exp_dtype)

    @pytest.mark.xfail(
        reason="GH 22839: do not ignore timezone, must be object")
    def test_where_index_datetimetz(self):
        fill_val = pd.Timestamp('2012-01-01', tz='US/Eastern')
        exp_dtype = np.object
        obj = pd.Index([pd.Timestamp('2011-01-01'),
                        pd.Timestamp('2011-01-02'),
                        pd.Timestamp('2011-01-03'),
                        pd.Timestamp('2011-01-04')])
        assert obj.dtype == 'datetime64[ns]'
        cond = pd.Index([True, False, True, False])

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

        values = pd.Index(pd.date_range(fill_val, periods=4))
        exp = pd.Index([pd.Timestamp('2011-01-01'),
                        pd.Timestamp('2012-01-02', tz='US/Eastern'),
                        pd.Timestamp('2011-01-03'),
                        pd.Timestamp('2012-01-04', tz='US/Eastern')],
                       dtype=exp_dtype)

        self._assert_where_conversion(obj, cond, values, exp, exp_dtype)

    def test_where_index_complex128(self):
        pass

    def test_where_index_bool(self):
        pass

    def test_where_series_datetime64tz(self):
        pass

    def test_where_series_timedelta64(self):
        pass

    def test_where_series_period(self):
        pass

    def test_where_index_datetime64tz(self):
        pass

    def test_where_index_timedelta64(self):
        pass

    def test_where_index_period(self):
        pass


class TestFillnaSeriesCoercion(CoercionBase):

    # not indexing, but place here for consisntency

    method = 'fillna'

    def test_has_comprehensive_tests(self):
        pass

    def _assert_fillna_conversion(self, original, value,
                                  expected, expected_dtype):
        """ test coercion triggered by fillna """
        target = original.copy()
        res = target.fillna(value)
        self._assert(res, expected, expected_dtype)

    @pytest.mark.parametrize("klass", [pd.Series, pd.Index],
                             ids=['series', 'index'])
    @pytest.mark.parametrize("fill_val, fill_dtype", [
        (1, np.object),
        (1.1, np.object),
        (1 + 1j, np.object),
        (True, np.object)])
    def test_fillna_object(self, klass, fill_val, fill_dtype):
        obj = klass(['a', np.nan, 'c', 'd'])
        assert obj.dtype == np.object

        exp = klass(['a', fill_val, 'c', 'd'])
        self._assert_fillna_conversion(obj, fill_val, exp, fill_dtype)

    @pytest.mark.parametrize("klass", [pd.Series, pd.Index],
                             ids=['series', 'index'])
    @pytest.mark.parametrize("fill_val,fill_dtype", [
        (1, np.float64),
        (1.1, np.float64),
        (1 + 1j, np.complex128),
        (True, np.object)])
    def test_fillna_float64(self, klass, fill_val, fill_dtype):
        obj = klass([1.1, np.nan, 3.3, 4.4])
        assert obj.dtype == np.float64

        exp = klass([1.1, fill_val, 3.3, 4.4])
        # float + complex -> we don't support a complex Index
        # complex for Series,
        # object for Index
        if fill_dtype == np.complex128 and klass == pd.Index:
            fill_dtype = np.object
        self._assert_fillna_conversion(obj, fill_val, exp, fill_dtype)

    @pytest.mark.parametrize("fill_val,fill_dtype", [
        (1, np.complex128),
        (1.1, np.complex128),
        (1 + 1j, np.complex128),
        (True, np.object)])
    def test_fillna_series_complex128(self, fill_val, fill_dtype):
        obj = pd.Series([1 + 1j, np.nan, 3 + 3j, 4 + 4j])
        assert obj.dtype == np.complex128

        exp = pd.Series([1 + 1j, fill_val, 3 + 3j, 4 + 4j])
        self._assert_fillna_conversion(obj, fill_val, exp, fill_dtype)

    @pytest.mark.parametrize("klass", [pd.Series, pd.Index],
                             ids=['series', 'index'])
    @pytest.mark.parametrize("fill_val,fill_dtype", [
        (pd.Timestamp('2012-01-01'), 'datetime64[ns]'),
        (pd.Timestamp('2012-01-01', tz='US/Eastern'), np.object),
        (1, np.object), ('x', np.object)],
        ids=['datetime64', 'datetime64tz', 'object', 'object'])
    def test_fillna_datetime(self, klass, fill_val, fill_dtype):
        obj = klass([pd.Timestamp('2011-01-01'),
                     pd.NaT,
                     pd.Timestamp('2011-01-03'),
                     pd.Timestamp('2011-01-04')])
        assert obj.dtype == 'datetime64[ns]'

        exp = klass([pd.Timestamp('2011-01-01'),
                     fill_val,
                     pd.Timestamp('2011-01-03'),
                     pd.Timestamp('2011-01-04')])
        self._assert_fillna_conversion(obj, fill_val, exp, fill_dtype)

    @pytest.mark.parametrize("klass", [pd.Series, pd.Index])
    @pytest.mark.parametrize("fill_val,fill_dtype", [
        (pd.Timestamp('2012-01-01', tz='US/Eastern'),
         'datetime64[ns, US/Eastern]'),
        (pd.Timestamp('2012-01-01'), np.object),
        (pd.Timestamp('2012-01-01', tz='Asia/Tokyo'), np.object),
        (1, np.object),
        ('x', np.object)])
    def test_fillna_datetime64tz(self, klass, fill_val, fill_dtype):
        tz = 'US/Eastern'

        obj = klass([pd.Timestamp('2011-01-01', tz=tz),
                     pd.NaT,
                     pd.Timestamp('2011-01-03', tz=tz),
                     pd.Timestamp('2011-01-04', tz=tz)])
        assert obj.dtype == 'datetime64[ns, US/Eastern]'

        exp = klass([pd.Timestamp('2011-01-01', tz=tz),
                     fill_val,
                     pd.Timestamp('2011-01-03', tz=tz),
                     pd.Timestamp('2011-01-04', tz=tz)])
        self._assert_fillna_conversion(obj, fill_val, exp, fill_dtype)

    def test_fillna_series_int64(self):
        pass

    def test_fillna_index_int64(self):
        pass

    def test_fillna_series_bool(self):
        pass

    def test_fillna_index_bool(self):
        pass

    def test_fillna_series_timedelta64(self):
        pass

    def test_fillna_series_period(self):
        pass

    def test_fillna_index_timedelta64(self):
        pass

    def test_fillna_index_period(self):
        pass


class TestReplaceSeriesCoercion(CoercionBase):

    klasses = ['series']
    method = 'replace'

    rep = {}
    rep['object'] = ['a', 'b']
    rep['int64'] = [4, 5]
    rep['float64'] = [1.1, 2.2]
    rep['complex128'] = [1 + 1j, 2 + 2j]
    rep['bool'] = [True, False]
    rep['datetime64[ns]'] = [pd.Timestamp('2011-01-01'),
                             pd.Timestamp('2011-01-03')]

    for tz in ['UTC', 'US/Eastern']:
        # to test tz => different tz replacement
        key = 'datetime64[ns, {0}]'.format(tz)
        rep[key] = [pd.Timestamp('2011-01-01', tz=tz),
                    pd.Timestamp('2011-01-03', tz=tz)]

    rep['timedelta64[ns]'] = [pd.Timedelta('1 day'),
                              pd.Timedelta('2 day')]

    @pytest.mark.parametrize('how', ['dict', 'series'])
    @pytest.mark.parametrize('to_key', [
        'object', 'int64', 'float64', 'complex128', 'bool', 'datetime64[ns]',
        'datetime64[ns, UTC]', 'datetime64[ns, US/Eastern]', 'timedelta64[ns]'
    ], ids=['object', 'int64', 'float64', 'complex128', 'bool',
            'datetime64', 'datetime64tz', 'datetime64tz', 'timedelta64'])
    @pytest.mark.parametrize('from_key', [
        'object', 'int64', 'float64', 'complex128', 'bool', 'datetime64[ns]',
        'datetime64[ns, UTC]', 'datetime64[ns, US/Eastern]', 'timedelta64[ns]']
    )
    def test_replace_series(self, how, to_key, from_key):
        if from_key == 'bool' and how == 'series' and compat.PY3:
            # doesn't work in PY3, though ...dict_from_bool works fine
            pytest.skip("doesn't work as in PY3")

        index = pd.Index([3, 4], name='xxx')
        obj = pd.Series(self.rep[from_key], index=index, name='yyy')
        assert obj.dtype == from_key

        if (from_key.startswith('datetime') and to_key.startswith('datetime')):
            # tested below
            return
        elif from_key in ['datetime64[ns, US/Eastern]', 'datetime64[ns, UTC]']:
            # tested below
            return

        if how == 'dict':
            replacer = dict(zip(self.rep[from_key], self.rep[to_key]))
        elif how == 'series':
            replacer = pd.Series(self.rep[to_key], index=self.rep[from_key])
        else:
            raise ValueError

        result = obj.replace(replacer)

        if ((from_key == 'float64' and to_key in ('int64')) or
            (from_key == 'complex128' and
             to_key in ('int64', 'float64'))):

            if compat.is_platform_32bit() or compat.is_platform_windows():
                pytest.skip("32-bit platform buggy: {0} -> {1}".format
                            (from_key, to_key))

            # Expected: do not downcast by replacement
            exp = pd.Series(self.rep[to_key], index=index,
                            name='yyy', dtype=from_key)

        else:
            exp = pd.Series(self.rep[to_key], index=index, name='yyy')
            assert exp.dtype == to_key

        tm.assert_series_equal(result, exp)

    # TODO(jbrockmendel) commented out to only have a single xfail printed
    @pytest.mark.xfail(reason='GH #18376, tzawareness-compat bug '
                              'in BlockManager.replace_list')
    # @pytest.mark.parametrize('how', ['dict', 'series'])
    # @pytest.mark.parametrize('to_key', ['timedelta64[ns]', 'bool', 'object',
    #                                     'complex128', 'float64', 'int64'])
    # @pytest.mark.parametrize('from_key', ['datetime64[ns, UTC]',
    #                                       'datetime64[ns, US/Eastern]'])
    # def test_replace_series_datetime_tz(self, how, to_key, from_key):
    def test_replace_series_datetime_tz(self):
        how = 'series'
        from_key = 'datetime64[ns, US/Eastern]'
        to_key = 'timedelta64[ns]'

        index = pd.Index([3, 4], name='xxx')
        obj = pd.Series(self.rep[from_key], index=index, name='yyy')
        assert obj.dtype == from_key

        if how == 'dict':
            replacer = dict(zip(self.rep[from_key], self.rep[to_key]))
        elif how == 'series':
            replacer = pd.Series(self.rep[to_key], index=self.rep[from_key])
        else:
            raise ValueError

        result = obj.replace(replacer)
        exp = pd.Series(self.rep[to_key], index=index, name='yyy')
        assert exp.dtype == to_key

        tm.assert_series_equal(result, exp)

    # TODO(jreback) commented out to only have a single xfail printed
    @pytest.mark.xfail(reason="different tz, "
                       "currently mask_missing raises SystemError",
                       strict=False)
    # @pytest.mark.parametrize('how', ['dict', 'series'])
    # @pytest.mark.parametrize('to_key', [
    #    'datetime64[ns]', 'datetime64[ns, UTC]',
    #    'datetime64[ns, US/Eastern]'])
    # @pytest.mark.parametrize('from_key', [
    #    'datetime64[ns]', 'datetime64[ns, UTC]',
    #    'datetime64[ns, US/Eastern]'])
    # def test_replace_series_datetime_datetime(self, how, to_key, from_key):
    def test_replace_series_datetime_datetime(self):
        how = 'dict'
        to_key = 'datetime64[ns]'
        from_key = 'datetime64[ns]'

        index = pd.Index([3, 4], name='xxx')
        obj = pd.Series(self.rep[from_key], index=index, name='yyy')
        assert obj.dtype == from_key

        if how == 'dict':
            replacer = dict(zip(self.rep[from_key], self.rep[to_key]))
        elif how == 'series':
            replacer = pd.Series(self.rep[to_key], index=self.rep[from_key])
        else:
            raise ValueError

        result = obj.replace(replacer)
        exp = pd.Series(self.rep[to_key], index=index, name='yyy')
        assert exp.dtype == to_key

        tm.assert_series_equal(result, exp)

    def test_replace_series_period(self):
        pass