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TST: groupby of idxmax/min with mixed types #40795

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Merged
merged 10 commits into from
Apr 14, 2021
Merged

TST: groupby of idxmax/min with mixed types #40795

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5169f5c
Includes the reading from Excel example as suggested via #38990
bsun94 Jan 17, 2021
7037920
Updated Comparison to Excel documentation with examples of reading Ex…
bsun94 Jan 17, 2021
d8df1fc
Update doc/source/getting_started/comparison/comparison_with_spreadsh…
jreback Jan 21, 2021
45f5221
Resyncing local fork to pandas remote in order to start on new issue
bsun94 Mar 21, 2021
3192a16
Refreshing main branch of local repo to take on #40346
bsun94 Mar 31, 2021
51b4353
TST: added new test to test_reductions.py::TestDataFrameAnalytics::te…
bsun94 Apr 3, 2021
e5056af
BUG: included new testcase to ensure resolution of bug highlighted in…
bsun94 Apr 6, 2021
9314476
wrote new parametrized tests for #40346
bsun94 Apr 6, 2021
f5eb1bb
TST adjusted parametrization of test as discussed for #40346
bsun94 Apr 8, 2021
1403c58
TST adjustment made to replace convert_dtypes in test #40346
bsun94 Apr 14, 2021
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40 changes: 40 additions & 0 deletions pandas/tests/frame/test_reductions.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1025,6 +1025,46 @@ def test_idxmax_mixed_dtype(self):
expected = Series([0, 2, 1, 2], index=[1, 2, 3, 4])
tm.assert_series_equal(result, expected)

@pytest.mark.parametrize(
"ID, value, expected_index, expected_value",
[([100, 100, 100, 200, 200, 200], [0, 0, 0, 1, 2, 0], [100, 200], [0, 4])],
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@phofl phofl Apr 7, 2021 •
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Please parametrize over ecpected values and the applied function only, you will need only one test then

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thanks @phofl , will redo and push

)
def test_idxmax_convert_dtypes(self, ID, value, expected_index, expected_value):
df2 = DataFrame(
{
"ID": ID,
"value": value,
}
)
df2 = df2.convert_dtypes()

result = df2.groupby("ID").idxmax()
expected = DataFrame(
{"value": expected_value},
index=Index(expected_index, dtype="object", name="ID"),
)
tm.assert_frame_equal(result, expected)

@pytest.mark.parametrize(
"ID, value, expected_index, expected_value",
[([100, 100, 100, 200, 200, 200], [0, 0, 0, 1, 2, 0], [100, 200], [0, 5])],
)
def test_idxmin_convert_dtypes(self, ID, value, expected_index, expected_value):
df2 = DataFrame(
{
"ID": ID,
"value": value,
}
)
df2 = df2.convert_dtypes()

result = df2.groupby("ID").idxmin()
expected = DataFrame(
{"value": expected_value},
index=Index(expected_index, dtype="object", name="ID"),
)
tm.assert_frame_equal(result, expected)

def test_idxmax_dt64_multicolumn_axis1(self):
dti = date_range("2016-01-01", periods=3)
df = DataFrame({3: dti, 4: dti[::-1]})
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