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TST: add test for rolling max/min/mean with DatetimeIndex over different frequencies #29932

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merged 6 commits into from
Dec 1, 2019
Merged

TST: add test for rolling max/min/mean with DatetimeIndex over different frequencies #29932

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7852918
add test for rolling max with DatetimeIndex
ganevgv Nov 21, 2019
041df3f
move and simplify test
ganevgv Nov 23, 2019
a4729b2
parametrize over freqs and ops
ganevgv Nov 29, 2019
441f4f2
Merge remote-tracking branch 'upstream/master' into tests/test_rollin…
ganevgv Nov 30, 2019
eb58e54
use f-string
ganevgv Dec 1, 2019
f13216f
passes black
ganevgv Dec 1, 2019
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31 changes: 26 additions & 5 deletions pandas/tests/window/test_timeseries_window.py
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Original file line number Diff line number Diff line change
Expand Up @@ -535,15 +535,36 @@ def test_ragged_max(self):
expected["B"] = [0.0, 1, 2, 3, 4]
tm.assert_frame_equal(result, expected)

def test_minutes_freq_max(self):
@pytest.mark.parametrize(
"freq, op, result_data",
[
("ms", "min", [0.0] * 10),
("ms", "mean", [0.0] * 9 + [2.0 / 9]),
("ms", "max", [0.0] * 9 + [2.0]),
("s", "min", [0.0] * 10),
("s", "mean", [0.0] * 9 + [2.0 / 9]),
("s", "max", [0.0] * 9 + [2.0]),
("min", "min", [0.0] * 10),
("min", "mean", [0.0] * 9 + [2.0 / 9]),
("min", "max", [0.0] * 9 + [2.0]),
("h", "min", [0.0] * 10),
("h", "mean", [0.0] * 9 + [2.0 / 9]),
("h", "max", [0.0] * 9 + [2.0]),
("D", "min", [0.0] * 10),
("D", "mean", [0.0] * 9 + [2.0 / 9]),
("D", "max", [0.0] * 9 + [2.0]),
],
)
def test_freqs_ops(self, freq, op, result_data):
# GH 21096
n = 10
index = date_range(start="2018-1-1 01:00:00", freq="1min", periods=n)
index = date_range(
start="2018-1-1 01:00:00", freq="1{}".format(freq), periods=10
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Can you use f-string instead of .format?

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good note - done

)
s = Series(data=0, index=index)
s.iloc[1] = np.nan
s.iloc[-1] = 2
result = s.rolling(window=f"{n}min").max()
expected = Series(data=[0] * (n - 1) + [2.0], index=index)
result = getattr(s.rolling(window="10{}".format(freq)), op)()
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Same comment

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done

expected = Series(data=result_data, index=index)

tm.assert_series_equal(result, expected)

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