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Apr 17, 2020
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TST: make expected DTI/TDI results more specific #33609

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26 changes: 17 additions & 9 deletions pandas/tests/indexes/datetimes/test_misc.py
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Original file line number Diff line number Diff line change
Expand Up @@ -25,7 +25,8 @@ def test_range_edges(self):
"1970-01-01 00:00:00.000000002",
"1970-01-01 00:00:00.000000003",
"1970-01-01 00:00:00.000000004",
]
],
freq="N",
)
tm.assert_index_equal(idx, exp)

Expand All @@ -34,15 +35,15 @@ def test_range_edges(self):
end=Timestamp("1970-01-01 00:00:00.000000001"),
freq="N",
)
exp = DatetimeIndex([])
exp = DatetimeIndex([], freq="N")
tm.assert_index_equal(idx, exp)

idx = pd.date_range(
start=Timestamp("1970-01-01 00:00:00.000000001"),
end=Timestamp("1970-01-01 00:00:00.000000001"),
freq="N",
)
exp = DatetimeIndex(["1970-01-01 00:00:00.000000001"])
exp = DatetimeIndex(["1970-01-01 00:00:00.000000001"], freq="N")
tm.assert_index_equal(idx, exp)

idx = pd.date_range(
Expand All @@ -56,7 +57,8 @@ def test_range_edges(self):
"1970-01-01 00:00:00.000002",
"1970-01-01 00:00:00.000003",
"1970-01-01 00:00:00.000004",
]
],
freq="U",
)
tm.assert_index_equal(idx, exp)

Expand All @@ -71,7 +73,8 @@ def test_range_edges(self):
"1970-01-01 00:00:00.002",
"1970-01-01 00:00:00.003",
"1970-01-01 00:00:00.004",
]
],
freq="L",
)
tm.assert_index_equal(idx, exp)

Expand All @@ -86,7 +89,8 @@ def test_range_edges(self):
"1970-01-01 00:00:02",
"1970-01-01 00:00:03",
"1970-01-01 00:00:04",
]
],
freq="S",
)
tm.assert_index_equal(idx, exp)

Expand All @@ -101,7 +105,8 @@ def test_range_edges(self):
"1970-01-01 00:02",
"1970-01-01 00:03",
"1970-01-01 00:04",
]
],
freq="T",
)
tm.assert_index_equal(idx, exp)

Expand All @@ -116,14 +121,17 @@ def test_range_edges(self):
"1970-01-01 02:00",
"1970-01-01 03:00",
"1970-01-01 04:00",
]
],
freq="H",
)
tm.assert_index_equal(idx, exp)

idx = pd.date_range(
start=Timestamp("1970-01-01"), end=Timestamp("1970-01-04"), freq="D"
)
exp = DatetimeIndex(["1970-01-01", "1970-01-02", "1970-01-03", "1970-01-04"])
exp = DatetimeIndex(
["1970-01-01", "1970-01-02", "1970-01-03", "1970-01-04"], freq="D"
)
tm.assert_index_equal(idx, exp)


Expand Down
14 changes: 9 additions & 5 deletions pandas/tests/indexes/datetimes/test_partial_slicing.py
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Original file line number Diff line number Diff line change
Expand Up @@ -26,9 +26,11 @@ def test_slice_with_negative_step(self):
SLC = pd.IndexSlice

def assert_slices_equivalent(l_slc, i_slc):
tm.assert_series_equal(ts[l_slc], ts.iloc[i_slc])
tm.assert_series_equal(ts.loc[l_slc], ts.iloc[i_slc])
tm.assert_series_equal(ts.loc[l_slc], ts.iloc[i_slc])
expected = ts.iloc[i_slc]

tm.assert_series_equal(ts[l_slc], expected)
tm.assert_series_equal(ts.loc[l_slc], expected)
tm.assert_series_equal(ts.loc[l_slc], expected)

assert_slices_equivalent(SLC[Timestamp("2014-10-01") :: -1], SLC[9::-1])
assert_slices_equivalent(SLC["2014-10-01"::-1], SLC[9::-1])
Expand All @@ -47,7 +49,7 @@ def assert_slices_equivalent(l_slc, i_slc):
SLC[Timestamp("2015-02-01") : "2014-10-01" : -1], SLC[13:8:-1]
)

assert_slices_equivalent(SLC["2014-10-01":"2015-02-01":-1], SLC[:0])
assert_slices_equivalent(SLC["2014-10-01":"2015-02-01":-1], SLC[0:0:-1])

def test_slice_with_zero_step_raises(self):
ts = Series(np.arange(20), date_range("2014-01-01", periods=20, freq="MS"))
Expand Down Expand Up @@ -79,7 +81,9 @@ def test_monotone_DTI_indexing_bug(self):
df = pd.DataFrame(
{"A": [1, 2, 3]}, index=pd.date_range("20170101", periods=3)[::-1]
)
expected = pd.DataFrame({"A": 1}, index=pd.date_range("20170103", periods=1))
expected = pd.DataFrame(
{"A": 1}, index=pd.date_range("20170103", periods=1)[::-1]
)
tm.assert_frame_equal(df.loc["2017-01-03"], expected)

def test_slice_year(self):
Expand Down
3 changes: 3 additions & 0 deletions pandas/tests/indexes/datetimes/test_shift.py
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Original file line number Diff line number Diff line change
Expand Up @@ -28,18 +28,21 @@ def test_dti_shift_tzaware(self, tz_naive_fixture):
["2011-01-01 10:00", "2011-01-01 11:00", "2011-01-01 12:00"],
name="xxx",
tz=tz,
freq="H",
)
tm.assert_index_equal(idx.shift(0, freq="H"), idx)
exp = pd.DatetimeIndex(
["2011-01-01 13:00", "2011-01-01 14:00", "2011-01-01 15:00"],
name="xxx",
tz=tz,
freq="H",
)
tm.assert_index_equal(idx.shift(3, freq="H"), exp)
exp = pd.DatetimeIndex(
["2011-01-01 07:00", "2011-01-01 08:00", "2011-01-01 09:00"],
name="xxx",
tz=tz,
freq="H",
)
tm.assert_index_equal(idx.shift(-3, freq="H"), exp)

Expand Down
2 changes: 1 addition & 1 deletion pandas/tests/indexes/period/test_to_timestamp.py
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Original file line number Diff line number Diff line change
Expand Up @@ -60,7 +60,7 @@ def test_to_timestamp_quarterly_bug(self):
pindex = PeriodIndex(year=years, quarter=quarters)

stamps = pindex.to_timestamp("D", "end")
expected = DatetimeIndex([x.to_timestamp("D", "end") for x in pindex])
expected = DatetimeIndex([x.to_timestamp("D", "end") for x in pindex], freq="Q")
tm.assert_index_equal(stamps, expected)

def test_to_timestamp_pi_mult(self):
Expand Down
10 changes: 6 additions & 4 deletions pandas/tests/indexes/timedeltas/test_partial_slicing.py
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Original file line number Diff line number Diff line change
Expand Up @@ -52,9 +52,11 @@ def test_slice_with_negative_step(self):
SLC = pd.IndexSlice

def assert_slices_equivalent(l_slc, i_slc):
tm.assert_series_equal(ts[l_slc], ts.iloc[i_slc])
tm.assert_series_equal(ts.loc[l_slc], ts.iloc[i_slc])
tm.assert_series_equal(ts.loc[l_slc], ts.iloc[i_slc])
expected = ts.iloc[i_slc]

tm.assert_series_equal(ts[l_slc], expected)
tm.assert_series_equal(ts.loc[l_slc], expected)
tm.assert_series_equal(ts.loc[l_slc], expected)

assert_slices_equivalent(SLC[Timedelta(hours=7) :: -1], SLC[7::-1])
assert_slices_equivalent(SLC["7 hours"::-1], SLC[7::-1])
Expand All @@ -73,7 +75,7 @@ def assert_slices_equivalent(l_slc, i_slc):
SLC[Timedelta(hours=15) : "7 hours" : -1], SLC[15:6:-1]
)

assert_slices_equivalent(SLC["7 hours":"15 hours":-1], SLC[:0])
assert_slices_equivalent(SLC["7 hours":"15 hours":-1], SLC[0:0:-1])

def test_slice_with_zero_step_raises(self):
ts = Series(np.arange(20), timedelta_range("0", periods=20, freq="H"))
Expand Down
6 changes: 4 additions & 2 deletions pandas/tests/series/methods/test_append.py
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Original file line number Diff line number Diff line change
Expand Up @@ -175,7 +175,7 @@ def test_series_append_aware(self):
ts_result = ser1.append(ser2)

exp_index = DatetimeIndex(
["2011-01-01 01:00", "2011-01-01 02:00"], tz="US/Eastern"
["2011-01-01 01:00", "2011-01-01 02:00"], tz="US/Eastern", freq="H"
)
exp = Series([1, 2], index=exp_index)
tm.assert_series_equal(ts_result, exp)
Expand All @@ -187,7 +187,9 @@ def test_series_append_aware(self):
ser2 = Series([2], index=rng2)
ts_result = ser1.append(ser2)

exp_index = DatetimeIndex(["2011-01-01 01:00", "2011-01-01 02:00"], tz="UTC")
exp_index = DatetimeIndex(
["2011-01-01 01:00", "2011-01-01 02:00"], tz="UTC", freq="H"
)
exp = Series([1, 2], index=exp_index)
tm.assert_series_equal(ts_result, exp)
utc = rng1.tz
Expand Down
13 changes: 8 additions & 5 deletions pandas/tests/series/methods/test_asfreq.py
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Original file line number Diff line number Diff line change
Expand Up @@ -39,11 +39,14 @@ def test_tz_aware_asfreq(self, tz):
def test_asfreq(self):
ts = Series(
[0.0, 1.0, 2.0],
index=[
datetime(2009, 10, 30),
datetime(2009, 11, 30),
datetime(2009, 12, 31),
],
index=DatetimeIndex(
[
datetime(2009, 10, 30),
datetime(2009, 11, 30),
datetime(2009, 12, 31),
],
freq="BM",
),
)

daily_ts = ts.asfreq("B")
Expand Down
4 changes: 2 additions & 2 deletions pandas/tests/tseries/offsets/test_offsets.py
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Original file line number Diff line number Diff line change
Expand Up @@ -3501,7 +3501,7 @@ def test_offset_whole_year(self):

# ensure generating a range with DatetimeIndex gives same result
result = date_range(start=dates[0], end=dates[-1], freq="SM")
exp = DatetimeIndex(dates)
exp = DatetimeIndex(dates, freq="SM")
tm.assert_index_equal(result, exp)

offset_cases = []
Expand Down Expand Up @@ -3760,7 +3760,7 @@ def test_offset_whole_year(self):

# ensure generating a range with DatetimeIndex gives same result
result = date_range(start=dates[0], end=dates[-1], freq="SMS")
exp = DatetimeIndex(dates)
exp = DatetimeIndex(dates, freq="SMS")
tm.assert_index_equal(result, exp)

offset_cases = []
Expand Down
26 changes: 19 additions & 7 deletions pandas/tests/window/moments/test_moments_rolling.py
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Original file line number Diff line number Diff line change
Expand Up @@ -9,7 +9,7 @@
import pandas.util._test_decorators as td

import pandas as pd
from pandas import DataFrame, Index, Series, isna, notna
from pandas import DataFrame, DatetimeIndex, Index, Series, isna, notna
import pandas._testing as tm
from pandas.core.window.common import _flex_binary_moment
from pandas.tests.window.common import Base, ConsistencyBase
Expand Down Expand Up @@ -1346,7 +1346,9 @@ def test_rolling_max_gh6297(self):

expected = Series(
[1.0, 2.0, 6.0, 4.0, 5.0],
index=[datetime(1975, 1, i, 0) for i in range(1, 6)],
index=DatetimeIndex(
[datetime(1975, 1, i, 0) for i in range(1, 6)], freq="D"
),
)
x = series.resample("D").max().rolling(window=1).max()
tm.assert_series_equal(expected, x)
Expand All @@ -1366,15 +1368,19 @@ def test_rolling_max_resample(self):
# Default how should be max
expected = Series(
[0.0, 1.0, 2.0, 3.0, 20.0],
index=[datetime(1975, 1, i, 0) for i in range(1, 6)],
index=DatetimeIndex(
[datetime(1975, 1, i, 0) for i in range(1, 6)], freq="D"
),
)
x = series.resample("D").max().rolling(window=1).max()
tm.assert_series_equal(expected, x)

# Now specify median (10.0)
expected = Series(
[0.0, 1.0, 2.0, 3.0, 10.0],
index=[datetime(1975, 1, i, 0) for i in range(1, 6)],
index=DatetimeIndex(
[datetime(1975, 1, i, 0) for i in range(1, 6)], freq="D"
),
)
x = series.resample("D").median().rolling(window=1).max()
tm.assert_series_equal(expected, x)
Expand All @@ -1383,7 +1389,9 @@ def test_rolling_max_resample(self):
v = (4.0 + 10.0 + 20.0) / 3.0
expected = Series(
[0.0, 1.0, 2.0, 3.0, v],
index=[datetime(1975, 1, i, 0) for i in range(1, 6)],
index=DatetimeIndex(
[datetime(1975, 1, i, 0) for i in range(1, 6)], freq="D"
),
)
x = series.resample("D").mean().rolling(window=1).max()
tm.assert_series_equal(expected, x)
Expand All @@ -1403,7 +1411,9 @@ def test_rolling_min_resample(self):
# Default how should be min
expected = Series(
[0.0, 1.0, 2.0, 3.0, 4.0],
index=[datetime(1975, 1, i, 0) for i in range(1, 6)],
index=DatetimeIndex(
[datetime(1975, 1, i, 0) for i in range(1, 6)], freq="D"
),
)
r = series.resample("D").min().rolling(window=1)
tm.assert_series_equal(expected, r.min())
Expand All @@ -1423,7 +1433,9 @@ def test_rolling_median_resample(self):
# Default how should be median
expected = Series(
[0.0, 1.0, 2.0, 3.0, 10],
index=[datetime(1975, 1, i, 0) for i in range(1, 6)],
index=DatetimeIndex(
[datetime(1975, 1, i, 0) for i in range(1, 6)], freq="D"
),
)
x = series.resample("D").median().rolling(window=1).median()
tm.assert_series_equal(expected, x)
Expand Down