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TST: Add tests for fixed issues #30444

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Dec 26, 2019
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26 changes: 26 additions & 0 deletions pandas/tests/indexing/multiindex/test_loc.py
Original file line number Diff line number Diff line change
Expand Up @@ -411,3 +411,29 @@ def test_loc_setitem_single_column_slice():
df.loc[:, "B"] = np.arange(4)
expected.iloc[:, 2] = np.arange(4)
tm.assert_frame_equal(df, expected)


def test_loc_nan_multiindex():
# GH 5286
tups = [
("Good Things", "C", np.nan),
("Good Things", "R", np.nan),
("Bad Things", "C", np.nan),
("Bad Things", "T", np.nan),
("Okay Things", "N", "B"),
("Okay Things", "N", "D"),
("Okay Things", "B", np.nan),
("Okay Things", "D", np.nan),
]
df = DataFrame(
np.ones((8, 4)),
columns=Index(["d1", "d2", "d3", "d4"]),
index=MultiIndex.from_tuples(tups, names=["u1", "u2", "u3"]),
)
result = df.loc["Good Things"].loc["C"]
expected = DataFrame(
np.ones((1, 4)),
index=Index([np.nan], dtype="object", name="u3"),
columns=Index(["d1", "d2", "d3", "d4"], dtype="object"),
)
tm.assert_frame_equal(result, expected)
8 changes: 8 additions & 0 deletions pandas/tests/indexing/test_loc.py
Original file line number Diff line number Diff line change
Expand Up @@ -968,3 +968,11 @@ def test_loc_getitem_label_list_integer_labels(
expected = df.iloc[:, expected_columns]
result = df.loc[["A", "B", "C"], column_key]
tm.assert_frame_equal(result, expected, check_column_type=check_column_type)


def test_loc_upcast_int():
# GH 6485
result = DataFrame({"a": range(10)}, dtype="i4")
result.loc[10] = 99
expected = DataFrame({"a": list(range(10)) + [99]})
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can you specify the expected dtype here? im actually not clear on why this is "fixed". casting to int64 is better than casting to float64 like it did in the OP in #6485, but dont we want the dtype to stay int32?

Also, there is mention in that issue of an empty case that is still broken. should that issue stay open or new issue for the still-broken case?

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Good point. Ideally we should maintain int32 here. I guess that issue is not totally solved and it leave it open for both cases

tm.assert_frame_equal(result, expected)
17 changes: 17 additions & 0 deletions pandas/tests/resample/test_datetime_index.py
Original file line number Diff line number Diff line change
Expand Up @@ -1564,3 +1564,20 @@ def test_get_timestamp_range_edges(first, last, offset, exp_first, exp_last):
result = _get_timestamp_range_edges(first, last, offset)
expected = (exp_first, exp_last)
assert result == expected


def test_resample_apply_product():
# GH 5586
index = date_range(start="2012-01-31", freq="M", periods=12)

ts = Series(range(12), index=index)
df = DataFrame(dict(A=ts, B=ts + 2))
result = df.resample("Q").apply(np.product)
expected = DataFrame(
np.array([[0, 24], [60, 210], [336, 720], [990, 1716]], dtype=np.int64),
index=DatetimeIndex(
["2012-03-31", "2012-06-30", "2012-09-30", "2012-12-31"], freq="Q-DEC"
),
columns=["A", "B"],
)
tm.assert_frame_equal(result, expected)
29 changes: 29 additions & 0 deletions pandas/tests/reshape/merge/test_join.py
Original file line number Diff line number Diff line change
Expand Up @@ -770,6 +770,35 @@ def test_join_on_tz_aware_datetimeindex(self):
expected["vals_2"] = pd.Series([np.nan] * 2 + list("tuv"), dtype=object)
tm.assert_frame_equal(result, expected)

def test_join_datetime_string(self):
# GH 5647
dfa = DataFrame(
[
["2012-08-02", "L", 10],
["2012-08-02", "J", 15],
["2013-04-06", "L", 20],
["2013-04-06", "J", 25],
],
columns=["x", "y", "a"],
)
dfa["x"] = pd.to_datetime(dfa["x"])
dfb = DataFrame(
[["2012-08-02", "J", 1], ["2013-04-06", "L", 2]],
columns=["x", "y", "z"],
index=[2, 4],
)
dfb["x"] = pd.to_datetime(dfb["x"])
result = dfb.join(dfa.set_index(["x", "y"]), on=["x", "y"])
expected = DataFrame(
[
[pd.Timestamp("2012-08-02 00:00:00"), "J", 1, 15],
[pd.Timestamp("2013-04-06 00:00:00"), "L", 2, 20],
],
index=[2, 4],
columns=["x", "y", "z", "a"],
)
tm.assert_frame_equal(result, expected)


def _check_join(left, right, result, join_col, how="left", lsuffix="_x", rsuffix="_y"):

Expand Down