PERF: improve perf. of Categorical.searchsorted #28795
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topper-123
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Performance
gfyoung
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Oct 5, 2019
doc/source/whatsnew/v1.0.0.rst
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| @@ -162,6 +162,7 @@ Performance improvements | |||
| - Performance improvement in :meth:`DataFrame.corr` when ``method`` is ``"spearman"`` (:issue:`28139`) | |||
| - Performance improvement in :meth:`DataFrame.replace` when provided a list of values to replace (:issue:`28099`) | |||
| - Performance improvement in :meth:`DataFrame.select_dtypes` by using vectorization instead of iterating over a loop (:issue:`28317`) | |||
| - Performance improvement in :meth:`Categorical.searchsorted` and :meth:`CategoricalIndex.searchsorted` when searching for a single scalar value (:issue:`XXXXX`) | |||
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Just reference the PR as the issue
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jreback
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| codes = codes[0] if is_scalar(value) else codes | ||
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| if is_scalar(value): |
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lgtm, i would add a comment here that this is perf sensitive
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Comments addressed. |
topper-123
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thanks @topper-123 |
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black pandasgit diff upstream/master -u -- "*.py" | flake8 --diffImproves performance of
Categorical.searchsortedby avoiding expensive data convertions.Also,
CategoricalIndex.searchsortednow callsself.values.searchsorteddirectly instead of going throughalgorithms.searchsorted, which always ends up callingself.values.searchsortedanyway. This ends up getting performance to 5.5 µs instead of 12 µs.