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TST: Add tests for single level indexing with loc(axis=1) #29519

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Merged
merged 6 commits into from
Nov 13, 2019
Merged

TST: Add tests for single level indexing with loc(axis=1) #29519

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60c3f9f
Add tests for single level indexing with loc(axis=1)
ryankarlos Nov 10, 2019
e8a27bb
remove dtype check to pass CI
ryankarlos Nov 10, 2019
184169e
Split simple df test into diff function
ryankarlos Nov 10, 2019
ed9075b
Remove check_dtype=False
ryankarlos Nov 10, 2019
bd31841
Split first test into sepaarate funcs
ryankarlos Nov 10, 2019
f47c322
change from list to np.array
ryankarlos Nov 12, 2019
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38 changes: 38 additions & 0 deletions pandas/tests/indexing/multiindex/test_slice.py
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Original file line number Diff line number Diff line change
Expand Up @@ -492,6 +492,44 @@ def test_loc_axis_arguments(self):
with pytest.raises(ValueError):
df.loc(axis="foo")[:, :, ["C1", "C3"]]

def test_loc_axis_single_level_multi_col_indexing_multiindex_col_df(self):

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Could you add the issue number?

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Sure

# GH29519
df = pd.DataFrame(
np.arange(27).reshape(3, 9),
columns=pd.MultiIndex.from_product(
[["a1", "a2", "a3"], ["b1", "b2", "b3"]]
),
)
result = df.loc(axis=1)["a1":"a2"]
expected = df.iloc[:, :-3]

tm.assert_frame_equal(result, expected)

def test_loc_axis_single_level_single_col_indexing_multiindex_col_df(self):

# GH29519
df = pd.DataFrame(
np.arange(27).reshape(3, 9),
columns=pd.MultiIndex.from_product(
[["a1", "a2", "a3"], ["b1", "b2", "b3"]]
),
)
result = df.loc(axis=1)["a1"]
expected = df.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


def test_loc_ax_single_level_indexer_simple_df(self):

# GH29519
# test single level indexing on single index column data frame
df = pd.DataFrame(np.arange(9).reshape(3, 3), columns=["a", "b", "c"])
result = df.loc(axis=1)["a"]
expected = pd.Series(np.array([0, 3, 6]), name="a")
tm.assert_series_equal(result, expected)

def test_per_axis_per_level_setitem(self):

# test index maker
Expand Down