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TST: reorg datetime with tz tests a bit #13301

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219 changes: 37 additions & 182 deletions pandas/tests/frame/test_constructors.py
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Original file line number Diff line number Diff line change
Expand Up @@ -17,16 +17,14 @@
from pandas.compat import (lmap, long, zip, range, lrange, lzip,
OrderedDict, is_platform_little_endian)
from pandas import compat
from pandas import (DataFrame, Index, Series, notnull, isnull,
from pandas import (DataFrame, Index, Series, isnull,
MultiIndex, Timedelta, Timestamp,
date_range)
from pandas.core.common import PandasError
import pandas as pd
import pandas.core.common as com
import pandas.lib as lib

from pandas.types.api import DatetimeTZDtype

from pandas.util.testing import (assert_numpy_array_equal,
assert_series_equal,
assert_frame_equal,
Expand Down Expand Up @@ -1329,185 +1327,6 @@ def test_constructor_with_datetimes(self):
.reset_index(drop=True), 'b': i_no_tz})
assert_frame_equal(df, expected)

def test_constructor_with_datetime_tz(self):

# 8260
# support datetime64 with tz

idx = Index(date_range('20130101', periods=3, tz='US/Eastern'),
name='foo')
dr = date_range('20130110', periods=3)

# construction
df = DataFrame({'A': idx, 'B': dr})
self.assertTrue(df['A'].dtype, 'M8[ns, US/Eastern')
self.assertTrue(df['A'].name == 'A')
assert_series_equal(df['A'], Series(idx, name='A'))
assert_series_equal(df['B'], Series(dr, name='B'))

# construction from dict
df2 = DataFrame(dict(A=Timestamp('20130102', tz='US/Eastern'),
B=Timestamp('20130603', tz='CET')),
index=range(5))
assert_series_equal(df2.dtypes, Series(['datetime64[ns, US/Eastern]',
'datetime64[ns, CET]'],
index=['A', 'B']))

# dtypes
tzframe = DataFrame({'A': date_range('20130101', periods=3),
'B': date_range('20130101', periods=3,
tz='US/Eastern'),
'C': date_range('20130101', periods=3, tz='CET')})
tzframe.iloc[1, 1] = pd.NaT
tzframe.iloc[1, 2] = pd.NaT
result = tzframe.dtypes.sort_index()
expected = Series([np.dtype('datetime64[ns]'),
DatetimeTZDtype('datetime64[ns, US/Eastern]'),
DatetimeTZDtype('datetime64[ns, CET]')],
['A', 'B', 'C'])

# concat
df3 = pd.concat([df2.A.to_frame(), df2.B.to_frame()], axis=1)
assert_frame_equal(df2, df3)

# select_dtypes
result = df3.select_dtypes(include=['datetime64[ns]'])
expected = df3.reindex(columns=[])
assert_frame_equal(result, expected)

# this will select based on issubclass, and these are the same class
result = df3.select_dtypes(include=['datetime64[ns, CET]'])
expected = df3
assert_frame_equal(result, expected)

# from index
idx2 = date_range('20130101', periods=3, tz='US/Eastern', name='foo')
df2 = DataFrame(idx2)
assert_series_equal(df2['foo'], Series(idx2, name='foo'))
df2 = DataFrame(Series(idx2))
assert_series_equal(df2['foo'], Series(idx2, name='foo'))

idx2 = date_range('20130101', periods=3, tz='US/Eastern')
df2 = DataFrame(idx2)
assert_series_equal(df2[0], Series(idx2, name=0))
df2 = DataFrame(Series(idx2))
assert_series_equal(df2[0], Series(idx2, name=0))

# interleave with object
result = self.tzframe.assign(D='foo').values
expected = np.array([[Timestamp('2013-01-01 00:00:00'),
Timestamp('2013-01-02 00:00:00'),
Timestamp('2013-01-03 00:00:00')],
[Timestamp('2013-01-01 00:00:00-0500',
tz='US/Eastern'),
pd.NaT,
Timestamp('2013-01-03 00:00:00-0500',
tz='US/Eastern')],
[Timestamp('2013-01-01 00:00:00+0100', tz='CET'),
pd.NaT,
Timestamp('2013-01-03 00:00:00+0100', tz='CET')],
['foo', 'foo', 'foo']], dtype=object).T
self.assert_numpy_array_equal(result, expected)

# interleave with only datetime64[ns]
result = self.tzframe.values
expected = np.array([[Timestamp('2013-01-01 00:00:00'),
Timestamp('2013-01-02 00:00:00'),
Timestamp('2013-01-03 00:00:00')],
[Timestamp('2013-01-01 00:00:00-0500',
tz='US/Eastern'),
pd.NaT,
Timestamp('2013-01-03 00:00:00-0500',
tz='US/Eastern')],
[Timestamp('2013-01-01 00:00:00+0100', tz='CET'),
pd.NaT,
Timestamp('2013-01-03 00:00:00+0100',
tz='CET')]], dtype=object).T
self.assert_numpy_array_equal(result, expected)

# astype
expected = np.array([[Timestamp('2013-01-01 00:00:00'),
Timestamp('2013-01-02 00:00:00'),
Timestamp('2013-01-03 00:00:00')],
[Timestamp('2013-01-01 00:00:00-0500',
tz='US/Eastern'),
pd.NaT,
Timestamp('2013-01-03 00:00:00-0500',
tz='US/Eastern')],
[Timestamp('2013-01-01 00:00:00+0100', tz='CET'),
pd.NaT,
Timestamp('2013-01-03 00:00:00+0100',
tz='CET')]],
dtype=object).T
result = self.tzframe.astype(object)
assert_frame_equal(result, DataFrame(
expected, index=self.tzframe.index, columns=self.tzframe.columns))

result = self.tzframe.astype('datetime64[ns]')
expected = DataFrame({'A': date_range('20130101', periods=3),
'B': (date_range('20130101', periods=3,
tz='US/Eastern')
.tz_convert('UTC')
.tz_localize(None)),
'C': (date_range('20130101', periods=3,
tz='CET')
.tz_convert('UTC')
.tz_localize(None))})
expected.iloc[1, 1] = pd.NaT
expected.iloc[1, 2] = pd.NaT
assert_frame_equal(result, expected)

# str formatting
result = self.tzframe.astype(str)
expected = np.array([['2013-01-01', '2013-01-01 00:00:00-05:00',
'2013-01-01 00:00:00+01:00'],
['2013-01-02', 'NaT', 'NaT'],
['2013-01-03', '2013-01-03 00:00:00-05:00',
'2013-01-03 00:00:00+01:00']], dtype=object)
self.assert_numpy_array_equal(result, expected)

result = str(self.tzframe)
self.assertTrue('0 2013-01-01 2013-01-01 00:00:00-05:00 '
'2013-01-01 00:00:00+01:00' in result)
self.assertTrue('1 2013-01-02 '
'NaT NaT' in result)
self.assertTrue('2 2013-01-03 2013-01-03 00:00:00-05:00 '
'2013-01-03 00:00:00+01:00' in result)

# setitem
df['C'] = idx
assert_series_equal(df['C'], Series(idx, name='C'))

df['D'] = 'foo'
df['D'] = idx
assert_series_equal(df['D'], Series(idx, name='D'))
del df['D']

# assert that A & C are not sharing the same base (e.g. they
# are copies)
b1 = df._data.blocks[1]
b2 = df._data.blocks[2]
self.assertTrue(b1.values.equals(b2.values))
self.assertFalse(id(b1.values.values.base) ==
id(b2.values.values.base))

# with nan
df2 = df.copy()
df2.iloc[1, 1] = pd.NaT
df2.iloc[1, 2] = pd.NaT
result = df2['B']
assert_series_equal(notnull(result), Series(
[True, False, True], name='B'))
assert_series_equal(df2.dtypes, df.dtypes)

# set/reset
df = DataFrame({'A': [0, 1, 2]}, index=idx)
result = df.reset_index()
self.assertTrue(result['foo'].dtype, 'M8[ns, US/Eastern')

result = result.set_index('foo')
tm.assert_index_equal(df.index, idx)

def test_constructor_for_list_with_dtypes(self):
# TODO(wesm): unused
intname = np.dtype(np.int_).name # noqa
Expand Down Expand Up @@ -2018,3 +1837,39 @@ def test_from_records_len0_with_columns(self):
self.assertTrue(np.array_equal(result.columns, ['bar']))
self.assertEqual(len(result), 0)
self.assertEqual(result.index.name, 'foo')


class TestDataFrameConstructorWithDatetimeTZ(tm.TestCase, TestData):

_multiprocess_can_split_ = True

def test_from_dict(self):

# 8260
# support datetime64 with tz

idx = Index(date_range('20130101', periods=3, tz='US/Eastern'),
name='foo')
dr = date_range('20130110', periods=3)

# construction
df = DataFrame({'A': idx, 'B': dr})
self.assertTrue(df['A'].dtype, 'M8[ns, US/Eastern')
self.assertTrue(df['A'].name == 'A')
assert_series_equal(df['A'], Series(idx, name='A'))
assert_series_equal(df['B'], Series(dr, name='B'))

def test_from_index(self):

# from index
idx2 = date_range('20130101', periods=3, tz='US/Eastern', name='foo')
df2 = DataFrame(idx2)
assert_series_equal(df2['foo'], Series(idx2, name='foo'))
df2 = DataFrame(Series(idx2))
assert_series_equal(df2['foo'], Series(idx2, name='foo'))

idx2 = date_range('20130101', periods=3, tz='US/Eastern')
df2 = DataFrame(idx2)
assert_series_equal(df2[0], Series(idx2, name=0))
df2 = DataFrame(Series(idx2))
assert_series_equal(df2[0], Series(idx2, name=0))
116 changes: 116 additions & 0 deletions pandas/tests/frame/test_dtypes.py
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Original file line number Diff line number Diff line change
Expand Up @@ -9,6 +9,7 @@
from pandas import (DataFrame, Series, date_range, Timedelta, Timestamp,
compat, option_context)
from pandas.compat import u
from pandas.core import common as com
from pandas.tests.frame.common import TestData
from pandas.util.testing import (assert_series_equal,
assert_frame_equal,
Expand Down Expand Up @@ -74,6 +75,21 @@ def test_empty_frame_dtypes_ftypes(self):
assert_series_equal(df[:0].dtypes, ex_dtypes)
assert_series_equal(df[:0].ftypes, ex_ftypes)

def test_datetime_with_tz_dtypes(self):
tzframe = DataFrame({'A': date_range('20130101', periods=3),
'B': date_range('20130101', periods=3,
tz='US/Eastern'),
'C': date_range('20130101', periods=3, tz='CET')})
tzframe.iloc[1, 1] = pd.NaT
tzframe.iloc[1, 2] = pd.NaT
result = tzframe.dtypes.sort_index()
expected = Series([np.dtype('datetime64[ns]'),
com.DatetimeTZDtype('datetime64[ns, US/Eastern]'),
com.DatetimeTZDtype('datetime64[ns, CET]')],
['A', 'B', 'C'])

assert_series_equal(result, expected)

def test_dtypes_are_correct_after_column_slice(self):
# GH6525
df = pd.DataFrame(index=range(5), columns=list("abc"), dtype=np.float_)
Expand Down Expand Up @@ -178,6 +194,16 @@ def test_select_dtypes_bad_datetime64(self):
with tm.assertRaisesRegexp(ValueError, '.+ is too specific'):
df.select_dtypes(exclude=['datetime64[as]'])

def test_select_dtypes_datetime_with_tz(self):

df2 = DataFrame(dict(A=Timestamp('20130102', tz='US/Eastern'),
B=Timestamp('20130603', tz='CET')),
index=range(5))
df3 = pd.concat([df2.A.to_frame(), df2.B.to_frame()], axis=1)
result = df3.select_dtypes(include=['datetime64[ns]'])
expected = df3.reindex(columns=[])
assert_frame_equal(result, expected)

def test_select_dtypes_str_raises(self):
df = DataFrame({'a': list('abc'),
'g': list(u('abc')),
Expand Down Expand Up @@ -394,3 +420,93 @@ def test_timedeltas(self):
'int64': 1}).sort_values()
result = df.get_dtype_counts().sort_values()
assert_series_equal(result, expected)


class TestDataFrameDatetimeWithTZ(tm.TestCase, TestData):

_multiprocess_can_split_ = True

def test_interleave(self):

# interleave with object
result = self.tzframe.assign(D='foo').values
expected = np.array([[Timestamp('2013-01-01 00:00:00'),
Timestamp('2013-01-02 00:00:00'),
Timestamp('2013-01-03 00:00:00')],
[Timestamp('2013-01-01 00:00:00-0500',
tz='US/Eastern'),
pd.NaT,
Timestamp('2013-01-03 00:00:00-0500',
tz='US/Eastern')],
[Timestamp('2013-01-01 00:00:00+0100', tz='CET'),
pd.NaT,
Timestamp('2013-01-03 00:00:00+0100', tz='CET')],
['foo', 'foo', 'foo']], dtype=object).T
self.assert_numpy_array_equal(result, expected)

# interleave with only datetime64[ns]
result = self.tzframe.values
expected = np.array([[Timestamp('2013-01-01 00:00:00'),
Timestamp('2013-01-02 00:00:00'),
Timestamp('2013-01-03 00:00:00')],
[Timestamp('2013-01-01 00:00:00-0500',
tz='US/Eastern'),
pd.NaT,
Timestamp('2013-01-03 00:00:00-0500',
tz='US/Eastern')],
[Timestamp('2013-01-01 00:00:00+0100', tz='CET'),
pd.NaT,
Timestamp('2013-01-03 00:00:00+0100',
tz='CET')]], dtype=object).T
self.assert_numpy_array_equal(result, expected)

def test_astype(self):
# astype
expected = np.array([[Timestamp('2013-01-01 00:00:00'),
Timestamp('2013-01-02 00:00:00'),
Timestamp('2013-01-03 00:00:00')],
[Timestamp('2013-01-01 00:00:00-0500',
tz='US/Eastern'),
pd.NaT,
Timestamp('2013-01-03 00:00:00-0500',
tz='US/Eastern')],
[Timestamp('2013-01-01 00:00:00+0100', tz='CET'),
pd.NaT,
Timestamp('2013-01-03 00:00:00+0100',
tz='CET')]],
dtype=object).T
result = self.tzframe.astype(object)
assert_frame_equal(result, DataFrame(
expected, index=self.tzframe.index, columns=self.tzframe.columns))

result = self.tzframe.astype('datetime64[ns]')
expected = DataFrame({'A': date_range('20130101', periods=3),
'B': (date_range('20130101', periods=3,
tz='US/Eastern')
.tz_convert('UTC')
.tz_localize(None)),
'C': (date_range('20130101', periods=3,
tz='CET')
.tz_convert('UTC')
.tz_localize(None))})
expected.iloc[1, 1] = pd.NaT
expected.iloc[1, 2] = pd.NaT
assert_frame_equal(result, expected)

def test_astype_str(self):
# str formatting
result = self.tzframe.astype(str)
expected = np.array([['2013-01-01', '2013-01-01 00:00:00-05:00',
'2013-01-01 00:00:00+01:00'],
['2013-01-02', 'NaT', 'NaT'],
['2013-01-03', '2013-01-03 00:00:00-05:00',
'2013-01-03 00:00:00+01:00']], dtype=object)
self.assert_numpy_array_equal(result, expected)

result = str(self.tzframe)
self.assertTrue('0 2013-01-01 2013-01-01 00:00:00-05:00 '
'2013-01-01 00:00:00+01:00' in result)
self.assertTrue('1 2013-01-02 '
'NaT NaT' in result)
self.assertTrue('2 2013-01-03 2013-01-03 00:00:00-05:00 '
'2013-01-03 00:00:00+01:00' in result)
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