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COMPAT: alias .to_numpy() for scalars #24653

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jreback opened this issue Jan 6, 2019 · 4 comments · Fixed by #25142
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COMPAT: alias .to_numpy() for scalars #24653

jreback opened this issue Jan 6, 2019 · 4 comments · Fixed by #25142
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Compat pandas objects compatability with Numpy or Python functions Datetime Datetime data dtype Timedelta Timedelta data type
Milestone
0.25.0

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@jreback
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jreback commented Jan 6, 2019

I think we achieve a bit more consistency in our interfaces if we alias .to_numpy() to .to_datetime64() and .to_timedelta64() for Timedelta and Timestamp respectively.

xref https://github.com/pandas-dev/pandas/pull/24486/files#diff-26a6d2ca7adfca586aabbb1c9dd8bf36L235
@jreback jreback added Datetime Datetime data dtype Timedelta Timedelta data type Compat pandas objects compatability with Numpy or Python functions labels Jan 6, 2019
@jreback jreback added this to the Contributions Welcome milestone Jan 6, 2019
@jreback jreback mentioned this issue Jan 6, 2019
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@jbrockmendel
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Could do the same for to_py, I think arrow does this

@jreback
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jreback commented Jan 6, 2019

yep

@jorisvandenbossche jorisvandenbossche mentioned this issue Jan 27, 2019
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@cbertinato
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What should we do for the to_numpy() keyword arguments? Neither dtype nor copy make sense in the case of a scalar. Just let it raise the TypeError if either is passed, or accept the arguments and do nothing?

@jreback
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jreback commented Jan 27, 2019

i think it’s ok to have them i. the signature for compatibility (default to None); but they will be ignored

@cbertinato cbertinato mentioned this issue Feb 4, 2019
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@jreback jreback modified the milestones: Contributions Welcome, 0.25.0 Feb 4, 2019
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Compat pandas objects compatability with Numpy or Python functions Datetime Datetime data dtype Timedelta Timedelta data type
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0.25.0
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COMPAT: alias .to_numpy() for scalars cbertinato/pandas
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@jreback @jbrockmendel @cbertinato