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Mar 4, 2021
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STYLE: Inconsistent namespace - resample #39992 #40220

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f29c969
Fix styling
thomasyu888 Mar 4, 2021
ee5ed79
Fix other linting issues
thomasyu888 Mar 4, 2021
ecb4d51
Revert
thomasyu888 Mar 4, 2021
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62 changes: 31 additions & 31 deletions pandas/tests/resample/test_datetime_index.py
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Original file line number Diff line number Diff line change
Expand Up @@ -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)
Expand Down Expand Up @@ -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()
Expand Down Expand Up @@ -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")
Expand Down Expand Up @@ -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)

Expand All @@ -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()
Expand All @@ -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"])
Expand All @@ -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"]
Expand Down Expand Up @@ -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",
)

Expand Down Expand Up @@ -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"),
}
Expand All @@ -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")

Expand Down Expand Up @@ -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)
Expand Down Expand Up @@ -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)
Expand Down Expand Up @@ -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)

Expand All @@ -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)))
Expand Down Expand Up @@ -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)
Expand Down Expand Up @@ -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")
Expand Down Expand Up @@ -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"
)

Expand Down Expand Up @@ -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)
Expand All @@ -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)
Expand Down Expand Up @@ -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)
Expand All @@ -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()
Expand Down Expand Up @@ -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)

Expand Down
4 changes: 2 additions & 2 deletions pandas/tests/resample/test_deprecated.py
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Original file line number Diff line number Diff line change
Expand Up @@ -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):
Expand Down Expand Up @@ -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()
Expand Down
26 changes: 12 additions & 14 deletions pandas/tests/resample/test_period_index.py
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Original file line number Diff line number Diff line change
Expand Up @@ -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)
Expand All @@ -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)()
Expand All @@ -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):
Expand All @@ -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)
Expand All @@ -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(
Expand All @@ -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)
Expand All @@ -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)
Expand Down Expand Up @@ -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)
Expand Down Expand Up @@ -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)
Expand Down Expand Up @@ -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()
Expand Down
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