BUG: errors and segfaults in groupby cython transforms (#16771) #26134
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Codecov Report
@@ Coverage Diff @@
## master #26134 +/- ##
==========================================
- Coverage 91.99% 91.98% -0.01%
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Files 175 175
Lines 52387 52387
==========================================
- Hits 48191 48187 -4
- Misses 4196 4200 +4
Continue to review full report at Codecov.
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Codecov Report
@@ Coverage Diff @@
## master #26134 +/- ##
==========================================
- Coverage 92% 91.98% -0.03%
==========================================
Files 175 175
Lines 52371 52383 +12
==========================================
Hits 48184 48184
- Misses 4187 4199 +12
Continue to review full report at Codecov.
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WillAyd
requested changes
Apr 18, 2019
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Hmm so I don't think the behavior here is correct as it kind of defeats the purpose of the In [15]: import pandas as pd
...:
...: x_vals = [1]
...: x_cats = range(2)
...: y = [1]
...: df = pd.DataFrame(dict(x=pd.Categorical(x_vals, x_cats), y=y))Using In [15]: df.groupby('x', observed=True).y.cumsum()
Out[15]:
0 1
Name: y, dtype: int64Definitely the current random number that gets yielded with that being False is incorrect: In [16]: df.groupby('x', observed=False).y.cumsum()
Out[16]:
0 4825136601
Name: y, dtype: int64But at the same time what you have here in this PR I think is forcing For consistency the expectation should be a DataFrame with all of the categories in the index and probably np.nan where the value is not actually observed. Kind of wonky given this is a transform but I think that's the best approach |
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Alternately it may make more sense to just raise when a user tries to run a transform with a categorical in the grouper with unobserved categories and I can't imagine a scenario where running a transform and getting back a differently indexed result would be useful in the scope of pandas usage and this would certainly be simpler to integrate into the code base |
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@jreback @TomAugspurger if you have thoughts on comment above |
WillAyd
added
the
Missing-data
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The above comments seem a little confused? As these are transforms, there's no such thing as observed=True or observed=False behaviour; either way, the output index will be the same as the input index. As observed=False is the default, I think we should continue to support transforms with it set; otherwise you'd have to pass observed=True every time you wanted to call a transform. |
jreback
requested changes
Apr 18, 2019
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@jreback Requested changes made. @WillAyd ASV shows no significant difference. |
jreback
requested changes
Apr 19, 2019
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@jreback Done. |
jreback
requested changes
Apr 19, 2019
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@jreback Done. Some checks are failing, but seems unrelated to this PR? |
jreback
approved these changes
Apr 20, 2019
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thanks @adbull |
yhaque1213
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Apr 22, 2019
ryanreh99
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Apr 22, 2019
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git diff upstream/master -u -- "*.py" | flake8 --diff