ENH: Add dropna argument to DataFrame.value_counts() #41334
Conversation
connesy
commented
May 5, 2021
connesy
commented
- closes ENH: Add dropna argument to pd.DataFrame.value_counts() #41325
- tests added / passed
- Ensure all linting tests pass, see here for how to run them
- whatsnew entry
lithomas1
added
Algos
| @@ -100,3 +100,47 @@ def test_data_frame_value_counts_empty_normalize(): | |||
| expected = pd.Series([], dtype=np.float64) | |||
|
|
|||
| tm.assert_series_equal(result, expected) | |||
|
|
|||
|
|
|||
| def test_data_frame_value_counts_dropna_true(nulls_fixture): | |||
There was a problem hiding this comment.
Is it possible to parameterize this test with dropna instead of 2 separate tests?
There was a problem hiding this comment.
I am not sure how to do that while using the nulls_fixture. Any suggestion is welcome!
There was a problem hiding this comment.
You can simply add another parametrization:
@pytest.mark.parametrize("x", [1, 2])
def test_data_frame_value_counts_dropna_true(nulls_fixture, x):
pass
But I don't know if this wouldn't make it more complicated here.
There was a problem hiding this comment.
The issue is that the input and expected dataframes are quite different in the two tests, so they would need to be defined as part of the parametrization. But both are also defined using the values from the nulls_fixture, so I would somehow need to use the fixture values in the parametrization, and I'm not sure how I can do both.
There was a problem hiding this comment.
Ah now I get it. if else is the only way here, but I think this would make it more complicated than is worth
|
Two of the builds failed due to tests that I have not touched. It seems like those tests fail quite often? |
|
thanks @connesy very nice That CI build fails occasionaly and is unrelated here, so all good. |
