diff --git a/pandas/tests/indexes/datetimes/test_misc.py b/pandas/tests/indexes/datetimes/test_misc.py index bb228eadccc6c..42a72125ba411 100644 --- a/pandas/tests/indexes/datetimes/test_misc.py +++ b/pandas/tests/indexes/datetimes/test_misc.py @@ -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) @@ -34,7 +35,7 @@ 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( @@ -42,7 +43,7 @@ def test_range_edges(self): 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( @@ -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) @@ -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) @@ -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) @@ -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) @@ -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) diff --git a/pandas/tests/indexes/datetimes/test_partial_slicing.py b/pandas/tests/indexes/datetimes/test_partial_slicing.py index ddde30d0f8fbf..028a713a8af81 100644 --- a/pandas/tests/indexes/datetimes/test_partial_slicing.py +++ b/pandas/tests/indexes/datetimes/test_partial_slicing.py @@ -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]) @@ -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")) @@ -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): diff --git a/pandas/tests/indexes/datetimes/test_shift.py b/pandas/tests/indexes/datetimes/test_shift.py index 6e53492b71578..8724bfeb05c4d 100644 --- a/pandas/tests/indexes/datetimes/test_shift.py +++ b/pandas/tests/indexes/datetimes/test_shift.py @@ -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) diff --git a/pandas/tests/indexes/period/test_to_timestamp.py b/pandas/tests/indexes/period/test_to_timestamp.py index 23787586cb3d3..a7846d1864d40 100644 --- a/pandas/tests/indexes/period/test_to_timestamp.py +++ b/pandas/tests/indexes/period/test_to_timestamp.py @@ -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): diff --git a/pandas/tests/indexes/timedeltas/test_partial_slicing.py b/pandas/tests/indexes/timedeltas/test_partial_slicing.py index a0ef953db3600..10ad521ce4f76 100644 --- a/pandas/tests/indexes/timedeltas/test_partial_slicing.py +++ b/pandas/tests/indexes/timedeltas/test_partial_slicing.py @@ -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]) @@ -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")) diff --git a/pandas/tests/series/methods/test_append.py b/pandas/tests/series/methods/test_append.py index 158c759fdaef3..82bde7c233626 100644 --- a/pandas/tests/series/methods/test_append.py +++ b/pandas/tests/series/methods/test_append.py @@ -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) @@ -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 diff --git a/pandas/tests/series/methods/test_asfreq.py b/pandas/tests/series/methods/test_asfreq.py index d94b60384a07c..cd61c510c75f5 100644 --- a/pandas/tests/series/methods/test_asfreq.py +++ b/pandas/tests/series/methods/test_asfreq.py @@ -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") diff --git a/pandas/tests/tseries/offsets/test_offsets.py b/pandas/tests/tseries/offsets/test_offsets.py index 2f00a58fe80be..044dfa703c081 100644 --- a/pandas/tests/tseries/offsets/test_offsets.py +++ b/pandas/tests/tseries/offsets/test_offsets.py @@ -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 = [] @@ -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 = [] diff --git a/pandas/tests/window/moments/test_moments_rolling.py b/pandas/tests/window/moments/test_moments_rolling.py index f3a14971ef2e7..3c5352fcd997d 100644 --- a/pandas/tests/window/moments/test_moments_rolling.py +++ b/pandas/tests/window/moments/test_moments_rolling.py @@ -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 @@ -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) @@ -1366,7 +1368,9 @@ 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) @@ -1374,7 +1378,9 @@ def test_rolling_max_resample(self): # 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) @@ -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) @@ -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()) @@ -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)