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REF: smarter NaN handling in remove_unused_levels() #18438

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merged 1 commit into from
Nov 23, 2017

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@toobaz toobaz commented Nov 23, 2017

  • tests passed
  • passes git diff upstream/master -u -- "*.py" | flake8 --diff

Sorry for the bad timing @jreback , only after you merged #18426 this simpler way to proceed came to my mind.

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codecov bot commented Nov 23, 2017

Codecov Report

Merging #18438 into master will decrease coverage by 0.01%.
The diff coverage is 100%.

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@@            Coverage Diff             @@
##           master   #18438      +/-   ##
==========================================
- Coverage   91.35%   91.33%   -0.02%     
==========================================
  Files         163      163              
  Lines       49691    49688       -3     
==========================================
- Hits        45397    45385      -12     
- Misses       4294     4303       +9
Flag Coverage Δ
#multiple 89.14% <100%> (-0.01%) ⬇️
#single 39.67% <0%> (-0.06%) ⬇️
Impacted Files Coverage Δ
pandas/core/indexes/multi.py 96.4% <100%> (-0.01%) ⬇️
pandas/io/gbq.py 25% <0%> (-58.34%) ⬇️
pandas/core/frame.py 97.8% <0%> (-0.1%) ⬇️

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codecov bot commented Nov 23, 2017

Codecov Report

Merging #18438 into master will decrease coverage by 0.01%.
The diff coverage is 100%.

Impacted file tree graph

@@            Coverage Diff             @@
##           master   #18438      +/-   ##
==========================================
- Coverage   91.35%   91.33%   -0.02%     
==========================================
  Files         163      163              
  Lines       49691    49688       -3     
==========================================
- Hits        45397    45385      -12     
- Misses       4294     4303       +9
Flag Coverage Δ
#multiple 89.14% <100%> (-0.01%) ⬇️
#single 39.67% <0%> (-0.06%) ⬇️
Impacted Files Coverage Δ
pandas/core/indexes/multi.py 96.4% <100%> (-0.01%) ⬇️
pandas/io/gbq.py 25% <0%> (-58.34%) ⬇️
pandas/core/frame.py 97.8% <0%> (-0.1%) ⬇️

Continue to review full report at Codecov.

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Δ = absolute <relative> (impact), ø = not affected, ? = missing data
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@jreback jreback added Clean Missing-data np.nan, pd.NaT, pd.NA, dropna, isnull, interpolate labels Nov 23, 2017
@jreback jreback added this to the 0.22.0 milestone Nov 23, 2017
@jreback jreback merged commit e6a0ef8 into pandas-dev:master Nov 23, 2017
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jreback commented Nov 23, 2017

thanks! @toobaz

separately, it might be nice to see (on a bigger MI), how much time this actually takes, if its small then it might be theoretically feasible to actually do this (or at least check whether we need to do this).

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toobaz commented Nov 23, 2017

might be theoretically feasible to actually do this

Do you mean to implicitly do this (e.g. when slicing)?

@toobaz toobaz deleted the ref_unused_nan branch November 23, 2017 16:20
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jreback commented Nov 23, 2017

yep - seeing if this is feasible

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toobaz commented Nov 23, 2017

But do we actually want this? E.g. a categorical does not loose categories when it is sliced.

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jreback commented Nov 23, 2017

it’s actuaiky confusing to users
if it were cheap i think we would (but i don’t think it’s cheap)

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