STYLE: Inconsistent namespace - resample #39992 (#40220)

* Fix styling

* Fix other linting issues

* Revert

Author: thomasyu888

pandas/tests/resample/test_datetime_index.py

@@ -125,20 +125,20 @@ def test_resample_basic(series, closed, expected):
 def test_resample_integerarray():
     # GH 25580, resample on IntegerArray
     ts = Series(
-        range(9), index=pd.date_range("1/1/2000", periods=9, freq="T"), dtype="Int64"
+        range(9), index=date_range("1/1/2000", periods=9, freq="T"), dtype="Int64"
     )
     result = ts.resample("3T").sum()
     expected = Series(
         [3, 12, 21],
-        index=pd.date_range("1/1/2000", periods=3, freq="3T"),
+        index=date_range("1/1/2000", periods=3, freq="3T"),
         dtype="Int64",
     )
     tm.assert_series_equal(result, expected)
 
     result = ts.resample("3T").mean()
     expected = Series(
         [1, 4, 7],
-        index=pd.date_range("1/1/2000", periods=3, freq="3T"),
+        index=date_range("1/1/2000", periods=3, freq="3T"),
         dtype="Float64",
     )
     tm.assert_series_equal(result, expected)
@@ -529,8 +529,8 @@ def test_resample_ohlc(series):
 def test_resample_ohlc_result():
 
     # GH 12332
-    index = pd.date_range("1-1-2000", "2-15-2000", freq="h")
-    index = index.union(pd.date_range("4-15-2000", "5-15-2000", freq="h"))
+    index = date_range("1-1-2000", "2-15-2000", freq="h")
+    index = index.union(date_range("4-15-2000", "5-15-2000", freq="h"))
     s = Series(range(len(index)), index=index)
 
     a = s.loc[:"4-15-2000"].resample("30T").ohlc()
@@ -805,7 +805,7 @@ def test_resample_bad_offset(offset):
 def test_resample_origin_prime_freq():
     # GH 31809
     start, end = "2000-10-01 23:30:00", "2000-10-02 00:30:00"
-    rng = pd.date_range(start, end, freq="7min")
+    rng = date_range(start, end, freq="7min")
     ts = Series(np.random.randn(len(rng)), index=rng)
 
     exp_rng = date_range("2000-10-01 23:14:00", "2000-10-02 00:22:00", freq="17min")
@@ -863,7 +863,7 @@ def test_resample_origin_with_tz():
 def test_resample_origin_epoch_with_tz_day_vs_24h():
     # GH 34474
     start, end = "2000-10-01 23:30:00+0500", "2000-12-02 00:30:00+0500"
-    rng = pd.date_range(start, end, freq="7min")
+    rng = date_range(start, end, freq="7min")
     random_values = np.random.randn(len(rng))
     ts_1 = Series(random_values, index=rng)
 
@@ -880,7 +880,7 @@ def test_resample_origin_epoch_with_tz_day_vs_24h():
 
     # check that we have the similar results with two different timezones (+2H and +5H)
     start, end = "2000-10-01 23:30:00+0200", "2000-12-02 00:30:00+0200"
-    rng = pd.date_range(start, end, freq="7min")
+    rng = date_range(start, end, freq="7min")
     ts_2 = Series(random_values, index=rng)
     result_5 = ts_2.resample("D", origin="epoch").mean()
     result_6 = ts_2.resample("24H", origin="epoch").mean()
@@ -903,7 +903,7 @@ def _create_series(values, timestamps, freq="D"):
     # test classical behavior of origin in a DST context
     start = Timestamp("2013-11-02", tz=tz)
     end = Timestamp("2013-11-03 23:59", tz=tz)
-    rng = pd.date_range(start, end, freq="1h")
+    rng = date_range(start, end, freq="1h")
     ts = Series(np.ones(len(rng)), index=rng)
 
     expected = _create_series([24.0, 25.0], ["2013-11-02", "2013-11-03"])
@@ -914,7 +914,7 @@ def _create_series(values, timestamps, freq="D"):
     # test complex behavior of origin/offset in a DST context
     start = Timestamp("2013-11-03", tz=tz)
     end = Timestamp("2013-11-03 23:59", tz=tz)
-    rng = pd.date_range(start, end, freq="1h")
+    rng = date_range(start, end, freq="1h")
     ts = Series(np.ones(len(rng)), index=rng)
 
     expected_ts = ["2013-11-02 22:00-05:00", "2013-11-03 22:00-06:00"]
@@ -969,7 +969,7 @@ def test_period_with_agg():
     # aggregate a period resampler with a lambda
     s2 = Series(
         np.random.randint(0, 5, 50),
-        index=pd.period_range("2012-01-01", freq="H", periods=50),
+        index=period_range("2012-01-01", freq="H", periods=50),
         dtype="float64",
     )
 
@@ -1003,7 +1003,7 @@ def test_resample_dtype_preservation():
 
     df = DataFrame(
         {
-            "date": pd.date_range(start="2016-01-01", periods=4, freq="W"),
+            "date": date_range(start="2016-01-01", periods=4, freq="W"),
             "group": [1, 1, 2, 2],
             "val": Series([5, 6, 7, 8], dtype="int32"),
         }
@@ -1022,7 +1022,7 @@ def test_resample_dtype_coercion():
 
     # GH 16361
     df = {"a": [1, 3, 1, 4]}
-    df = DataFrame(df, index=pd.date_range("2017-01-01", "2017-01-04"))
+    df = DataFrame(df, index=date_range("2017-01-01", "2017-01-04"))
 
     expected = df.astype("float64").resample("H").mean()["a"].interpolate("cubic")
 
@@ -1056,12 +1056,12 @@ def test_nanosecond_resample_error():
     # Resampling using pd.tseries.offsets.Nano as period
     start = 1443707890427
     exp_start = 1443707890400
-    indx = pd.date_range(start=pd.to_datetime(start), periods=10, freq="100n")
+    indx = date_range(start=pd.to_datetime(start), periods=10, freq="100n")
     ts = Series(range(len(indx)), index=indx)
     r = ts.resample(pd.tseries.offsets.Nano(100))
     result = r.agg("mean")
 
-    exp_indx = pd.date_range(start=pd.to_datetime(exp_start), periods=10, freq="100n")
+    exp_indx = date_range(start=pd.to_datetime(exp_start), periods=10, freq="100n")
     exp = Series(range(len(exp_indx)), index=exp_indx)
 
     tm.assert_series_equal(result, exp)
@@ -1128,8 +1128,8 @@ def test_resample_anchored_multiday():
     #
     # See: https://github.com/pandas-dev/pandas/issues/8683
 
-    index1 = pd.date_range("2014-10-14 23:06:23.206", periods=3, freq="400L")
-    index2 = pd.date_range("2014-10-15 23:00:00", periods=2, freq="2200L")
+    index1 = date_range("2014-10-14 23:06:23.206", periods=3, freq="400L")
+    index2 = date_range("2014-10-15 23:00:00", periods=2, freq="2200L")
     index = index1.union(index2)
 
     s = Series(np.random.randn(5), index=index)
@@ -1174,7 +1174,7 @@ def test_anchored_lowercase_buglet():
 
 def test_upsample_apply_functions():
     # #1596
-    rng = pd.date_range("2012-06-12", periods=4, freq="h")
+    rng = date_range("2012-06-12", periods=4, freq="h")
 
     ts = Series(np.random.randn(len(rng)), index=rng)
 
@@ -1183,7 +1183,7 @@ def test_upsample_apply_functions():
 
 
 def test_resample_not_monotonic():
-    rng = pd.date_range("2012-06-12", periods=200, freq="h")
+    rng = date_range("2012-06-12", periods=200, freq="h")
     ts = Series(np.random.randn(len(rng)), index=rng)
 
     ts = ts.take(np.random.permutation(len(ts)))
@@ -1255,12 +1255,12 @@ def test_resample_consistency():
     # GH 6418
     # resample with bfill / limit / reindex consistency
 
-    i30 = pd.date_range("2002-02-02", periods=4, freq="30T")
+    i30 = date_range("2002-02-02", periods=4, freq="30T")
     s = Series(np.arange(4.0), index=i30)
     s[2] = np.NaN
 
     # Upsample by factor 3 with reindex() and resample() methods:
-    i10 = pd.date_range(i30[0], i30[-1], freq="10T")
+    i10 = date_range(i30[0], i30[-1], freq="10T")
 
     s10 = s.reindex(index=i10, method="bfill")
     s10_2 = s.reindex(index=i10, method="bfill", limit=2)
@@ -1364,8 +1364,8 @@ def test_resample_nunique_preserves_column_level_names():
 
 def test_resample_nunique_with_date_gap():
     # GH 13453
-    index = pd.date_range("1-1-2000", "2-15-2000", freq="h")
-    index2 = pd.date_range("4-15-2000", "5-15-2000", freq="h")
+    index = date_range("1-1-2000", "2-15-2000", freq="h")
+    index2 = date_range("4-15-2000", "5-15-2000", freq="h")
     index3 = index.append(index2)
     s = Series(range(len(index3)), index=index3, dtype="int64")
     r = s.resample("M")
@@ -1462,7 +1462,7 @@ def test_groupby_with_dst_time_change():
 
     df = DataFrame([1, 2], index=index)
     result = df.groupby(Grouper(freq="1d")).last()
-    expected_index_values = pd.date_range(
+    expected_index_values = date_range(
         "2016-11-02", "2016-11-24", freq="d", tz="America/Chicago"
     )
 
@@ -1587,11 +1587,11 @@ def test_downsample_across_dst_weekly():
     )
     tm.assert_frame_equal(result, expected)
 
-    idx = pd.date_range("2013-04-01", "2013-05-01", tz="Europe/London", freq="H")
+    idx = date_range("2013-04-01", "2013-05-01", tz="Europe/London", freq="H")
     s = Series(index=idx, dtype=np.float64)
     result = s.resample("W").mean()
     expected = Series(
-        index=pd.date_range("2013-04-07", freq="W", periods=5, tz="Europe/London"),
+        index=date_range("2013-04-07", freq="W", periods=5, tz="Europe/London"),
         dtype=np.float64,
     )
     tm.assert_series_equal(result, expected)
@@ -1601,7 +1601,7 @@ def test_downsample_dst_at_midnight():
     # GH 25758
     start = datetime(2018, 11, 3, 12)
     end = datetime(2018, 11, 5, 12)
-    index = pd.date_range(start, end, freq="1H")
+    index = date_range(start, end, freq="1H")
     index = index.tz_localize("UTC").tz_convert("America/Havana")
     data = list(range(len(index)))
     dataframe = DataFrame(data, index=index)
@@ -1681,7 +1681,7 @@ def f(data, add_arg):
     tm.assert_series_equal(result, expected)
 
     # Testing dataframe
-    df = DataFrame({"A": 1, "B": 2}, index=pd.date_range("2017", periods=10))
+    df = DataFrame({"A": 1, "B": 2}, index=date_range("2017", periods=10))
     result = df.groupby("A").resample("D").agg(f, multiplier)
     expected = df.groupby("A").resample("D").mean().multiply(multiplier)
     tm.assert_frame_equal(result, expected)
@@ -1707,7 +1707,7 @@ def test_resample_equivalent_offsets(n1, freq1, n2, freq2, k):
     # GH 24127
     n1_ = n1 * k
     n2_ = n2 * k
-    s = Series(0, index=pd.date_range("19910905 13:00", "19911005 07:00", freq=freq1))
+    s = Series(0, index=date_range("19910905 13:00", "19911005 07:00", freq=freq1))
     s = s + range(len(s))
 
     result1 = s.resample(str(n1_) + freq1).mean()
@@ -1797,10 +1797,10 @@ def test_resample_calendar_day_with_dst(
     first: str, last: str, freq_in: str, freq_out: str, exp_last: str
 ):
     # GH 35219
-    ts = Series(1.0, pd.date_range(first, last, freq=freq_in, tz="Europe/Amsterdam"))
+    ts = Series(1.0, date_range(first, last, freq=freq_in, tz="Europe/Amsterdam"))
     result = ts.resample(freq_out).pad()
     expected = Series(
-        1.0, pd.date_range(first, exp_last, freq=freq_out, tz="Europe/Amsterdam")
+        1.0, date_range(first, exp_last, freq=freq_out, tz="Europe/Amsterdam")
     )
     tm.assert_series_equal(result, expected)
 

pandas/tests/resample/test_deprecated.py

@@ -52,7 +52,7 @@ def _create_index(*args, **kwargs):
 def test_deprecating_on_loffset_and_base():
     # GH 31809
 
-    idx = pd.date_range("2001-01-01", periods=4, freq="T")
+    idx = date_range("2001-01-01", periods=4, freq="T")
     df = DataFrame(data=4 * [range(2)], index=idx, columns=["a", "b"])
 
     with tm.assert_produces_warning(FutureWarning):
@@ -243,7 +243,7 @@ def test_loffset_returns_datetimeindex(frame, kind, agg_arg):
 )
 def test_resample_with_non_zero_base(start, end, start_freq, end_freq, base, offset):
     # GH 23882
-    s = Series(0, index=pd.period_range(start, end, freq=start_freq))
+    s = Series(0, index=period_range(start, end, freq=start_freq))
     s = s + np.arange(len(s))
     with tm.assert_produces_warning(FutureWarning):
         result = s.resample(end_freq, base=base).mean()

pandas/tests/resample/test_period_index.py

@@ -224,9 +224,9 @@ def test_resample_basic(self):
     )
     def test_resample_count(self, freq, expected_vals):
         # GH12774
-        series = Series(1, index=pd.period_range(start="2000", periods=100))
+        series = Series(1, index=period_range(start="2000", periods=100))
         result = series.resample(freq).count()
-        expected_index = pd.period_range(
+        expected_index = period_range(
             start="2000", freq=freq, periods=len(expected_vals)
         )
         expected = Series(expected_vals, index=expected_index)
@@ -235,9 +235,7 @@ def test_resample_count(self, freq, expected_vals):
     def test_resample_same_freq(self, resample_method):
 
         # GH12770
-        series = Series(
-            range(3), index=pd.period_range(start="2000", periods=3, freq="M")
-        )
+        series = Series(range(3), index=period_range(start="2000", periods=3, freq="M"))
         expected = series
 
         result = getattr(series.resample("M"), resample_method)()
@@ -250,7 +248,7 @@ def test_resample_incompat_freq(self):
         )
         with pytest.raises(IncompatibleFrequency, match=msg):
             Series(
-                range(3), index=pd.period_range(start="2000", periods=3, freq="M")
+                range(3), index=period_range(start="2000", periods=3, freq="M")
             ).resample("W").mean()
 
     def test_with_local_timezone_pytz(self):
@@ -261,7 +259,7 @@ def test_with_local_timezone_pytz(self):
         # 1 day later
         end = datetime(year=2013, month=11, day=2, hour=0, minute=0, tzinfo=pytz.utc)
 
-        index = pd.date_range(start, end, freq="H")
+        index = date_range(start, end, freq="H")
 
         series = Series(1, index=index)
         series = series.tz_convert(local_timezone)
@@ -270,14 +268,14 @@ def test_with_local_timezone_pytz(self):
         # Create the expected series
         # Index is moved back a day with the timezone conversion from UTC to
         # Pacific
-        expected_index = pd.period_range(start=start, end=end, freq="D") - offsets.Day()
+        expected_index = period_range(start=start, end=end, freq="D") - offsets.Day()
         expected = Series(1, index=expected_index)
         tm.assert_series_equal(result, expected)
 
     def test_resample_with_pytz(self):
         # GH 13238
         s = Series(
-            2, index=pd.date_range("2017-01-01", periods=48, freq="H", tz="US/Eastern")
+            2, index=date_range("2017-01-01", periods=48, freq="H", tz="US/Eastern")
         )
         result = s.resample("D").mean()
         expected = Series(
@@ -302,7 +300,7 @@ def test_with_local_timezone_dateutil(self):
             year=2013, month=11, day=2, hour=0, minute=0, tzinfo=dateutil.tz.tzutc()
         )
 
-        index = pd.date_range(start, end, freq="H", name="idx")
+        index = date_range(start, end, freq="H", name="idx")
 
         series = Series(1, index=index)
         series = series.tz_convert(local_timezone)
@@ -312,7 +310,7 @@ def test_with_local_timezone_dateutil(self):
         # Index is moved back a day with the timezone conversion from UTC to
         # Pacific
         expected_index = (
-            pd.period_range(start=start, end=end, freq="D", name="idx") - offsets.Day()
+            period_range(start=start, end=end, freq="D", name="idx") - offsets.Day()
         )
         expected = Series(1, index=expected_index)
         tm.assert_series_equal(result, expected)
@@ -343,7 +341,7 @@ def test_resample_nonexistent_time_bin_edge(self):
 
     def test_resample_ambiguous_time_bin_edge(self):
         # GH 10117
-        idx = pd.date_range(
+        idx = date_range(
             "2014-10-25 22:00:00", "2014-10-26 00:30:00", freq="30T", tz="Europe/London"
         )
         expected = Series(np.zeros(len(idx)), index=idx)
@@ -827,7 +825,7 @@ def test_resample_with_only_nat(self):
     )
     def test_resample_with_offset(self, start, end, start_freq, end_freq, offset):
         # GH 23882 & 31809
-        s = Series(0, index=pd.period_range(start, end, freq=start_freq))
+        s = Series(0, index=period_range(start, end, freq=start_freq))
         s = s + np.arange(len(s))
         result = s.resample(end_freq, offset=offset).mean()
         result = result.to_timestamp(end_freq)
@@ -869,7 +867,7 @@ def test_get_period_range_edges(self, first, last, freq, exp_first, exp_last):
 
     def test_sum_min_count(self):
         # GH 19974
-        index = pd.date_range(start="2018", freq="M", periods=6)
+        index = date_range(start="2018", freq="M", periods=6)
         data = np.ones(6)
         data[3:6] = np.nan
         s = Series(data, index).to_period()