8000 BUG: Adding skipna as an option to groupby cumsum and cumprod by shangyian · Pull Request #19914 · pandas-dev/pandas · GitHub
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BUG: Adding skipna as an option to groupby cumsum and cumprod #19914

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Merged
merged 10 commits into from
Mar 1, 2018
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BUG: Adding skipna as an option to groupby cumsum and cumprod #19914

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90b7978
Adding skipna as an option to groupby cumsum and cumprod
shangyian Feb 26, 2018
84db344
Fixing flake8 flags
shangyian Feb 26, 2018
6182352
Adding whatsnew entry
shangyian Feb 26, 2018
2579eaa
Adding a better test
shangyian Feb 26, 2018
75d2870
Fixing pep8 issues
shangyian Feb 26, 2018
bb740fd
Making some changes based on review and altering tests
shangyian Feb 28, 2018
47fe8d6
Making test changes based on review
shangyian Mar 1, 2018
107bc0b
More changes to tests based on review
shangyian Mar 1, 2018
5aceda9
Merge branch 'master' into PR_TOOL_MERGE_PR_19914
jreback Mar 1, 2018
3072df7
doc
jreback Mar 1, 2018
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Fixing pep8 issues
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@shangyian
shangyian committed Feb 26, 2018
commit 75d2870857c4c67697f236042338389d9750d56d
18 changes: 12 additions & 6 deletions pandas/tests/groupby/test_groupby.py
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Expand Up @@ -2523,16 +2523,22 @@ def test_groupby_cumprod(self):

# make sure that skipna works
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Can you split this into a new test? Make sure to add a reference to the Github issue as a comment.

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I'd find this a bit easier to read as

df = pd.DataFrame({"x": [...], "gp": ['a'] * 6 + ['b'] * 6})

instead of concat.

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And maybe have a group with all-NA to ensure that is handled properly.

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I added a new test (test_groupby_cum_skipna) for all of the skipna-related cases. And added a groupby+cumsum/prod on all-NA values.

df = pd.concat(
[pd.DataFrame({'x': [1.0, 2.0, np.nan, np.nan, 3.0, 2.0], 'gp': 'a'}),
pd.DataFrame({'x': [2.0, 5.0, 6.0, 1.0, np.nan, 1.0], 'gp': 'b'})])
[pd.DataFrame({'x': [1.0, 2.0, np.nan, np.nan, 3.0, 2.0],
'gp': 'a'}),
pd.DataFrame({'x': [2.0, 5.0, 6.0, 1.0, np.nan, 1.0],
'gp': 'b'})])
result = df.groupby('gp')['x'].cumprod(skipna=False)
expected = pd.Series([1.0, 2.0, np.nan, np.nan, np.nan, np.nan, 2.0, 10.0, 60.0, 60.0, np.nan, np.nan],
name='x', index=(0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5))
expected = pd.Series([1.0, 2.0, np.nan, np.nan, np.nan, np.nan,
2.0, 10.0, 60.0, 60.0, np.nan, np.nan],
name='x', index=(0, 1, 2, 3, 4, 5,
0, 1, 2, 3, 4, 5))
tm.assert_series_equal(result, expected)

result = df.groupby('gp')['x'].cumprod()
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Don't think you need this test. skipna=False should be adequately tested as is.

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Yep, removed it.

expected = pd.Series([1.0, 2.0, np.nan, np.nan, 6.0, 12.0, 2.0, 10.0, 60.0, 60.0, np.nan, 60.0],
name='x', index=(0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5))
expected = pd.Series([1.0, 2.0, np.nan, np.nan, 6.0, 12.0,
2.0, 10.0, 60.0, 60.0, np.nan, 60.0],
name='x', index=(0, 1, 2, 3, 4, 5,
0, 1, 2, 3, 4, 5))
tm.assert_series_equal(result, expected)

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Could you add a test for cumsum with skipna=False`?

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That should be covered by test_groupby_cum_skipna now.

def test_ops_general(self):
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