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shifting across blocks results in NaNs if dataframe has multiple blocks (mixed types) #11061

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hhuuggoo opened this issue Sep 11, 2015 · 2 comments
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shifting across blocks results in NaNs if dataframe has multiple blocks (mixed types) #11061

hhuuggoo opened this issue Sep 11, 2015 · 2 comments
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Bug Dtype Conversions Unexpected or buggy dtype conversions Reshaping Concat, Merge/Join, Stack/Unstack, Explode

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@hhuuggoo
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variant of #10907

In [1]: import pandas as pd

In [2]: df = pd.DataFrame({'a' : [1],'b':[2]})

In [3]: df
Out[3]: 
   a  b
0  1  2

In [4]: df['c'] = 3.5

In [5]: df.shift(axis=1)
Out[5]: 
    a  b   c
0 NaN  1 NaN
@hhuuggoo hhuuggoo changed the title shift does not work if dataframe has multiple blocks (mixed types) shifting across blocks results in NaNs if dataframe has multiple blocks (mixed types) Sep 11, 2015
@jreback jreback added Bug Reshaping Concat, Merge/Join, Stack/Unstack, Explode Dtype Conversions Unexpected or buggy dtype conversions labels Sep 11, 2015
@jreback jreback added this to the Next Major Release milestone Sep 11, 2015
@ajcr
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ajcr commented Sep 12, 2015

This bug is also highlighted in issue 10539.

@jreback
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jreback commented Sep 12, 2015

right this is a dupe

@jreback jreback closed this as completed Sep 12, 2015
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Bug Dtype Conversions Unexpected or buggy dtype conversions Reshaping Concat, Merge/Join, Stack/Unstack, Explode
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@hhuuggoo @jreback @ajcr