BUG: groupby.cummin/cummax nans inf values for int64 #15205
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mroeschke
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jreback
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Jan 24, 2017
| @@ -365,7 +365,7 @@ Performance Improvements | |||
| - Increased performance of ``pd.factorize()`` by releasing the GIL with ``object`` dtype when inferred as strings (:issue:`14859`) | |||
| - Improved performance of timeseries plotting with an irregular DatetimeIndex | |||
| (or with ``compat_x=True``) (:issue:`15073`). | |||
| - Improved performance of ``groupby().cummin()`` and ``groupby().cummax()`` (:issue:`15048`) | |||
| - Improved performance of ``groupby().cummin()`` and ``groupby().cummax()`` (:issue:`15048` & `15109`) | |||
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& `15109` -> , :issue:`151091`
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linting issue showing up & small comment, but otherwise lgtm. ping when pushed and green. |
migrate accum into cython move datetime check into cython mask int64 inf values before entering cython functions Edit whatsnew and alter condition add missing methods edit space Linting & whatsnew edit
Current coverage is 85.97% (diff: 100%)
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Ping all green. |
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thanks @mroeschke |
AnkurDedania
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Mar 21, 2017
closes pandas-dev#15109 Author: Matt Roeschke <[email protected]> Closes pandas-dev#15205 from mroeschke/fix_15109 and squashes the following commits: 717afb4 [Matt Roeschke] BUG: cummin/cummax nans inf values for int64
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git diff upstream/master | flake8 --diffI migrated the
accumportions of the code into cython and attempted to implement your suggested method to fix this issue @jreback. Let me know if this is along the right track.