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Merged
jreback merged 1 commit into from
Jan 20, 2019
Merged

PERF: fix some of .clip() performance regression by using numpy arrays where possible #24735

jreback merged 1 commit into from
Jan 20, 2019

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@qwhelan
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@qwhelan qwhelan commented Jan 11, 2019

A recent change to respect dtypes in .clip() (#24458) introduced a decent overhead of ~2ms to the call:

$ asv compare v0.23.4 v0.24.0rc1 --only-changed
       before           after         ratio
     [04095216]       [fdc4db25]
     <v0.23.4^0>       <v0.24.0rc1^0>
+         120±1μs      2.04±0.04ms    17.01  series_methods.Clip.time_clip(1000)
+        936±40μs      3.09±0.02ms     3.31  series_methods.Clip.time_clip(100000)
+         111±3μs      2.05±0.08ms    18.55  series_methods.Clip.time_clip(50)

This PR cuts the overhead from ~2ms to ~0.6ms by keeping subset as a numpy array; it's entirely boolean regardless of underlying dtype, so a DataFrame only adds overhead here:

$ asv compare v0.24.0rc1 HEAD --only-changed -s
       before           after         ratio
     [fdc4db25]       [63c47c58]
     <v0.24.0rc1^0>       <clip>
-     2.04±0.04ms         759±20μs     0.37  series_methods.Clip.time_clip(1000)
-     3.09±0.02ms      1.46±0.04ms     0.47  series_methods.Clip.time_clip(100000)
-     2.05±0.08ms         724±20μs     0.35  series_methods.Clip.time_clip(50)
  • closes #xxxx
  • tests added / passed
  • passes git diff upstream/master -u -- "*.py" | flake8 --diff
  • whatsnew entry

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codecov bot commented Jan 11, 2019

Codecov Report

Merging #24735 into master will increase coverage by <.01%.
The diff coverage is 100%.

Impacted file tree graph

@@            Coverage Diff             @@
##           master   #24735      +/-   ##
==========================================
+ Coverage   92.39%   92.39%   +<.01%     
==========================================
  Files         166      166              
  Lines       52358    52362       +4     
==========================================
+ Hits        48374    48378       +4     
  Misses       3984     3984
Flag Coverage Δ
#multiple 90.81% <100%> (ø) ⬆️
#single 43.06% <0%> (-0.03%) ⬇️
Impacted Files Coverage Δ
pandas/core/generic.py 96.63% <100%> (ø) ⬆️

Continue to review full report at Codecov.

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codecov bot commented Jan 11, 2019 •
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Codecov Report

Merging #24735 into master will increase coverage by <.01%.
The diff coverage is 100%.

Impacted file tree graph

@@            Coverage Diff             @@
##           master   #24735      +/-   ##
==========================================
+ Coverage   92.39%   92.39%   +<.01%     
==========================================
  Files         166      166              
  Lines       52378    52382       +4     
==========================================
+ Hits        48393    48398       +5     
+ Misses       3985     3984       -1
Flag Coverage Δ
#multiple 90.81% <100%> (ø) ⬆️
#single 42.9% <0%> (-0.01%) ⬇️
Impacted Files Coverage Δ
pandas/core/generic.py 96.63% <100%> (ø) ⬆️
pandas/util/testing.py 88.13% <0%> (+0.09%) ⬆️

Continue to review full report at Codecov.

Legend - Click here to learn more
Δ = absolute <relative> (impact), ø = not affected, ? = missing data
Powered by Codecov. Last update f4458c1...f372c9e. Read the comment docs.

@jschendel jschendel added Performance Memory or execution speed performance Dtype Conversions Unexpected or buggy dtype conversions labels Jan 12, 2019
mroeschke
mroeschke reviewed Jan 12, 2019
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pandas/core/generic.py Outdated

with np.errstate(all='ignore'):
if upper is not None:
subset = self.values <= upper
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@mroeschke mroeschke Jan 12, 2019

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Curious, does this place nice when self is the new Int64 dtype?

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@qwhelan qwhelan Jan 17, 2019

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It appears to - let me know if there's a more extensive test you have in mind:

In [2]: s = pd.Series(range(5)).astype('Int64')
In [3]: s.clip(1, 3)
Out[3]: 0    1
        1    1
        2    2
        3    3
        4    3
        dtype: Int64

WillAyd
WillAyd requested changes Jan 12, 2019
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pandas/core/generic.py
result = result.where(subset, lower, axis=None, inplace=False)
mask = isna(self.values)

with np.errstate(all='ignore'):
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@WillAyd WillAyd Jan 12, 2019

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What's the point of this?

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@qwhelan qwhelan Jan 16, 2019

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This is simply reverting back to what this block used to do; it's needed in the event values <= upper would otherwise raise a type error.

pandas/core/generic.py Outdated

with np.errstate(all='ignore'):
if upper is not None:
subset = self.values <= upper
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@WillAyd WillAyd Jan 12, 2019

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Idiomatic approach here would now be to_numpy instead of .values

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@qwhelan qwhelan Jan 17, 2019

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Updated

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jreback commented Jan 16, 2019

@qwhelan can you update

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jreback commented Jan 19, 2019

@qwhelan can you merge master and ping when passing

@jreback jreback added this to the 0.24.0 milestone Jan 20, 2019
@jreback jreback merged commit 2d47349 into pandas-dev:master Jan 20, 2019
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jreback commented Jan 20, 2019

thanks @qwhelan

Pingviinituutti pushed a commit to Pingviinituutti/pandas that referenced this pull request Feb 28, 2019
@qwhelan @Pingviinituutti
PERF: fix some of .clip() performance regression by using numpy array…
7a6306c 
…s where possible (pandas-dev#24735)
Pingviinituutti pushed a commit to Pingviinituutti/pandas that referenced this pull request Feb 28, 2019
@qwhelan @Pingviinituutti
PERF: fix some of .clip() performance regression by using numpy array…
c1e2bc5 
…s where possible (pandas-dev#24735)
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Dtype Conversions Unexpected or buggy dtype conversions Performance Memory or execution speed performance

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@qwhelan @jreback @WillAyd @mroeschke @jschendel