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TST: add test for ffill/bfill for non unique multilevel #29763

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merged 5 commits into from
Nov 23, 2019
Merged

TST: add test for ffill/bfill for non unique multilevel #29763

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68573d4
add test for ffill for non unique multilevel
ganevgv Nov 21, 2019
bbc8534
move test to tests/groupby/test_transform.py
ganevgv Nov 21, 2019
9040a76
move test to tests/groupby/test_transform.py
ganevgv Nov 21, 2019
56a3c0b
parametrize over ffill, bfill
ganevgv Nov 22, 2019
f48ac9f
change name test
ganevgv Nov 22, 2019
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30 changes: 30 additions & 0 deletions pandas/tests/groupby/test_transform.py
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Original file line number Diff line number Diff line change
Expand Up @@ -911,6 +911,36 @@ def test_pct_change(test_series, freq, periods, fill_method, limit):
tm.assert_frame_equal(result, expected.to_frame("vals"))


def test_ffill_non_unique_multilevel():
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Is there an easy way to parametrize on ffill / bfill? Seems like testing both would be nice

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Agreed - now testing both ffill and bfill.

# GH 19437
date = pd.to_datetime(
[
"2018-01-01",
"2018-01-01",
"2018-01-01",
"2018-01-01",
"2018-01-01",
"2018-01-02",
"2018-01-01",
"2018-01-02",
]
)
symbol = ["MSFT", "MSFT", "MSFT", "AAPL", "AAPL", "AAPL", "TSLA", "TSLA"]
status = ["shrt", "lng", np.nan, "shrt", np.nan, "shrt", "ntrl", np.nan]

df = DataFrame({"date": date, "symbol": symbol, "status": status})
df = df.set_index(["date", "symbol"])
result = df.groupby("symbol")["status"].ffill()

index = MultiIndex.from_tuples(
tuples=list(zip(*[date, symbol])), names=["date", "symbol"]
)
status = ["shrt", "lng", "lng", "shrt", "shrt", "shrt", "ntrl", "ntrl"]
expected = Series(status, index=index, name="status")

tm.assert_series_equal(result, expected)


@pytest.mark.parametrize("func", [np.any, np.all])
def test_any_all_np_func(func):
# GH 20653
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