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BUG: unwanted conversions of timedelta dtypes when in a mixed datetimelike frame (GH7778) #7779

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Merged
merged 1 commit into from
Jul 18, 2014

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@jreback jreback commented Jul 17, 2014

closes #7778

TST: tests for internals/as_matrix() for all dtypes (including categoricals)

@jreback jreback added this to the 0.15.0 milestone Jul 17, 2014
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jreback commented Jul 17, 2014

cc @JanSchulz

I fixed up doing something like

df.values when you have a categorical (or 2) as a dtype.

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jreback commented Jul 17, 2014

@cpcloud

should

df = DataFrame({'bool' : [True, False], 'int' : [1, 2] })
df.values

be object or int? (I have it as object now).

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cpcloud commented Jul 17, 2014

hm int more useful, but object more consistent with the fact that numpy separates bool from int, i think int. is this an api breaking change?

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jreback commented Jul 17, 2014

I think it was object before
let me see

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jreback commented Jul 18, 2014

@cpcloud only took the usual 5x iterations for make the 1.6.1 stuff work :<

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cpcloud commented Jul 18, 2014

😡 on 1.6

…elike frame (GH7778)

TST: tests for internals/as_matrix() for all dtypes (including categoricals)
jreback added a commit that referenced this pull request Jul 18, 2014
BUG: unwanted conversions of timedelta dtypes when in a mixed datetimelike frame (GH7778)
@jreback jreback merged commit c8f48a5 into pandas-dev:master Jul 18, 2014
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Bug Dtype Conversions Unexpected or buggy dtype conversions Timedelta Timedelta data type
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BUG: df.apply handles np.timedelta64 as timestamp, should be timedelta
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