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Output from get_dummies() should default to np.int8 #10708

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johne13 opened this issue Jul 30, 2015 · 3 comments
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Output from get_dummies() should default to np.int8 #10708

johne13 opened this issue Jul 30, 2015 · 3 comments
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Dtype Conversions Unexpected or buggy dtype conversions Duplicate Report Duplicate issue or pull request Enhancement Reshaping Concat, Merge/Join, Stack/Unstack, Explode

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@johne13
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johne13 commented Jul 30, 2015

The output columns from get_dummies() are binary by nature, changing this default from float64 to int8 would save 7 bytes per dummy.

df=pd.DataFrame({ 'x':[1,2,3] })
pd.get_dummies(df.x)
@jreback jreback added Enhancement Reshaping Concat, Merge/Join, Stack/Unstack, Explode Difficulty Novice Dtype Conversions Unexpected or buggy dtype conversions labels Jul 30, 2015
@jreback jreback added this to the Next Major Release milestone Jul 30, 2015
@bwillers
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bwillers commented Aug 8, 2015

Working on this now, hitting up against the fact that SparseDataFrame only supports floating point data... Shall we have it return uint8s for regular frames and float64s for sparse frames?

@Lunran
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Lunran commented Sep 10, 2017

Isn't this a duplicate of the following?

@jreback
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jreback commented Sep 10, 2017

yep looks that way.

@jreback jreback closed this as completed Sep 10, 2017
@jreback jreback added the Duplicate Report Duplicate issue or pull request label Sep 10, 2017
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Dtype Conversions Unexpected or buggy dtype conversions Duplicate Report Duplicate issue or pull request Enhancement Reshaping Concat, Merge/Join, Stack/Unstack, Explode
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@jreback @bwillers @johne13 @Lunran