TST: Add tests for single level indexing with loc(axis=1) #29519
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ryankarlos
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| @@ -492,6 +492,29 @@ def test_loc_axis_arguments(self): | |||
| with pytest.raises(ValueError): | |||
| df.loc(axis="foo")[:, :, ["C1", "C3"]] | |||
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| def test_loc_axis_single_level_indexer(self): | |||
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Could you add the issue number?
| result = df1.loc(axis=1)["a1"] | ||
| expected = df1.iloc[:, :3] | ||
| expected.columns = ["b1", "b2", "b3"] | ||
| tm.assert_frame_equal(result, expected) |
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Could you make 3 different functions for these tests?
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@mroeschke Is it ok if I split it into 2 functions - one for Multindex column df and one for simple df --- and for the Multiindex bit I can comment on the two different tests - i.e one is slicing on multi columns on single level and other is slicing on single col. Otherwise, having concise names for the functions is tricky.
Something like this:
# GH29519
# test with single level multiple columns slice
df1 = pd.DataFrame(
np.arange(27).reshape(3, 9),
columns=pd.MultiIndex.from_product(
[["a1", "a2", "a3"], ["b1", "b2", "b3"]]
),
)
result = df1.loc(axis=1)["a1":"a2"]
expected = df1.iloc[:, :-3]
tm.assert_frame_equal(result, expected)
# GH29519
# test with single level single column slice
result = df1.loc(axis=1)["a1"]
expected = df1.iloc[:, :3]
expected.columns = ["b1", "b2", "b3"]
tm.assert_frame_equal(result, expected)
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Verbose function names are fine. Helps isolate the failing test as separate methods.
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Ok just pushed with changes as you originally suggested
| df2 = pd.DataFrame(np.arange(9).reshape(3, 3), columns=["a", "b", "c"]) | ||
| result = df2.loc(axis=1)["a"] | ||
| expected = pd.Series([0, 3, 6], name="a") | ||
| tm.assert_series_equal(result, expected, check_dtype=False) |
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Why is check_dtype=False set?
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@mroeschke Since CI was failing for some of the 32 bit OS builds because of int32 vs int64 dtype comparison - im having a similar issue in #29522. Don't know if there is any other work around.
================================== FAILURES ===================================
__________ TestMultiIndexSlicers.test_loc_axis_single_level_indexer ___________
[gw0] win32 -- Python 3.6.7 C:\Miniconda\envs\pandas-dev\python.exe
self = <pandas.tests.indexing.multiindex.test_slice.TestMultiIndexSlicers object at 0x00000156C517C898>
def test_loc_axis_single_level_indexer(self):
# test single level indexing on Multindex column dataframe
df1 = pd.DataFrame(
np.arange(27).reshape(3, 9),
columns=pd.MultiIndex.from_product(
[["a1", "a2", "a3"], ["b1", "b2", "b3"]]
),
)
result = df1.loc(axis=1)["a1":"a2"]
expected = df1.iloc[:, :-3]
tm.assert_frame_equal(result, expected)
result = df1.loc(axis=1)["a1"]
expected = df1.iloc[:, :3]
expected.columns = ["b1", "b2", "b3"]
tm.assert_frame_equal(result, expected)
# test single level indexing on single index column data frame
df2 = pd.DataFrame(np.arange(9).reshape(3, 3), columns=["a", "b", "c"])
result = df2.loc(axis=1)["a"]
expected = pd.Series([0, 3, 6], dtype="int64", name="a")
> tm.assert_series_equal(result, expected)
E AssertionError: Attributes of Series are different
E
E Attribute "dtype" are different
E [left]: int32
E [right]: int64
pandas\tests\indexing\multiindex\test_slice.py:516: AssertionError
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I see you're not assigning dtype="int64" anymore. Could you remove check_dtype=False now?
gfyoung
added
DataFrame
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@mroeschke all green now |
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thanks @ryankarlos |
black pandasgit diff upstream/master -u -- "*.py" | flake8 --diff