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TST: add tests for period resample sum with min_count #29762

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TST: add tests for period resample sum with min_count #29762

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ea8d831
add tests for period/datetime resample sum with min_count
ganevgv Nov 21, 2019
0784c21
remove datetime test
ganevgv Nov 23, 2019
c9e6830
move and generalise test to include DTI, PI and TDI
ganevgv Nov 29, 2019
75c4781
move timedelta test to pandas/tests/resample/test_timedelta.py
ganevgv Dec 6, 2019
4f131aa
restructure test to avoid duplication
ganevgv Dec 6, 2019
3850155
update test
ganevgv Dec 16, 2019
3d6bfa3
update test
ganevgv Dec 16, 2019
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59 changes: 58 additions & 1 deletion pandas/tests/resample/test_base.py
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Original file line number Diff line number Diff line change
Expand Up @@ -7,7 +7,7 @@
from pandas import DataFrame, Series
from pandas.core.groupby.groupby import DataError
from pandas.core.groupby.grouper import Grouper
from pandas.core.indexes.datetimes import date_range
from pandas.core.indexes.datetimes import DatetimeIndex, date_range
from pandas.core.indexes.period import PeriodIndex, period_range
from pandas.core.indexes.timedeltas import TimedeltaIndex, timedelta_range
import pandas.util.testing as tm
Expand Down Expand Up @@ -267,3 +267,60 @@ def test_resample_quantile(series):
result = s.resample(freq).quantile(q)
expected = s.resample(freq).agg(lambda x: x.quantile(q)).rename(s.name)
tm.assert_series_equal(result, expected)


@pytest.mark.parametrize(
"_index_factory,_series_name,_index_start,_index_end", [DATE_RANGE, PERIOD_RANGE]
)
@pytest.mark.parametrize(
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@ganevgv rather than nesting a dict, just make data, index paramters e.g.

@pytest.mark.parameterize('freq, data, index')

otherwise this is very hard to follow.

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@jreback - removed the nested dict and changed the format to:

@pytest.mark.parameterize("freq, result_name, result_data, result_index, result_freq")

"freq, result_name, result_data, result_index, result_freq",
[
(
"D",
"dti",
[1.0] * 5 + [np.nan] * 5,
["2005-01-{}".format(i) for i in range(1, 11)],
"D",
),
(
"D",
"pi",
[1.0] * 5 + [np.nan] * 5,
["2005-01-{}".format(i) for i in range(1, 11)],
"D",
),
(
"W",
"dti",
[2.0, 3.0, np.nan],
["2005-01-02", "2005-01-09", "2005-01-16"],
"W-SUN",
),
(
"W",
"pi",
[2.0, 3.0, np.nan],
["2004-12-27/2005-01-02", "2005-01-03/2005-01-09", "2005-01-10/2005-01-16"],
"W-SUN",
),
("M", "dti", [5.0], ["2005-01-31"], "M"),
("M", "pi", [5.0], ["2005-01"], "M"),
],
)
def test_resample_sum(
series, freq, result_name, result_data, result_index, result_freq
):
# GH 19974
series[:5] = 1
series[5:] = np.nan
result = series.resample(freq).sum(min_count=1)

if isinstance(series.index, PeriodIndex) and result_name == "pi":
index = PeriodIndex(result_index, freq=result_freq)
elif isinstance(series.index, DatetimeIndex) and result_name == "dti":
index = DatetimeIndex(result_index, freq=result_freq)
else:
pytest.skip("unsupported configuration")

expected = Series(result_data, index, name=result_name)
tm.assert_series_equal(result, expected)
14 changes: 13 additions & 1 deletion pandas/tests/resample/test_timedelta.py
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Original file line number Diff line number Diff line change
Expand Up @@ -4,7 +4,7 @@

import pandas as pd
from pandas import DataFrame, Series
from pandas.core.indexes.timedeltas import timedelta_range
from pandas.core.indexes.timedeltas import TimedeltaIndex, timedelta_range
import pandas.util.testing as tm


Expand Down Expand Up @@ -125,3 +125,15 @@ def test_resample_timedelta_values():
tm.assert_series_equal(res, exp)
res = df["time"].resample("2D").first()
tm.assert_series_equal(res, exp)


def test_resample_sum():
# GH 19974
data = [1.0] * 5 + [np.nan] * 5
index = timedelta_range("1 day", "10 day", freq="D")
series = Series(data, index=index)
result = series.resample("D").sum(min_count=1)

index = TimedeltaIndex(["{} days".format(i) for i in range(1, 11)], freq="D")
expected = Series(data, index=index)
tm.assert_series_equal(result, expected)