Added Datetime & Timedelta inference to array

[TomAugspurger]

Closes #24568

[codecov]

Codecov Report

Merging #24571 into master will decrease coverage by 49.24%.
The diff coverage is 0%.

@@             Coverage Diff             @@
##           master   #24571       +/-   ##
===========================================
- Coverage   92.31%   43.07%   -49.25%     
===========================================
  Files         166      166               
  Lines       52556    52563        +7     
===========================================
- Hits        48518    22640    -25878     
- Misses       4038    29923    +25885

Flag	Coverage Δ
#multiple	?
#single	43.07% <0%> (ø)	⬆️

Impacted Files	Coverage Δ
pandas/core/arrays/array_.py	12.82% <0%> (-87.18%)	⬇️
pandas/io/formats/latex.py	0% <0%> (-100%)	⬇️
pandas/core/categorical.py	0% <0%> (-100%)	⬇️
pandas/io/sas/sas_constants.py	0% <0%> (-100%)	⬇️
pandas/tseries/plotting.py	0% <0%> (-100%)	⬇️
pandas/tseries/converter.py	0% <0%> (-100%)	⬇️
pandas/io/formats/html.py	0% <0%> (-99.04%)	⬇️
pandas/core/groupby/categorical.py	0% <0%> (-95.46%)	⬇️
pandas/io/sas/sas7bdat.py	0% <0%> (-91.17%)	⬇️
pandas/io/sas/sas_xport.py	0% <0%> (-90.15%)	⬇️
... and 125 more

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[codecov]

Codecov Report

Merging #24571 into master will increase coverage by <.01%.
The diff coverage is 100%.

@@            Coverage Diff             @@
##           master   #24571      +/-   ##
==========================================
+ Coverage   92.31%   92.31%   +<.01%     
==========================================
  Files         166      166              
  Lines       52556    52563       +7     
==========================================
+ Hits        48518    48526       +8     
+ Misses       4038     4037       -1

Flag	Coverage Δ
#multiple	90.74% <100%> (ø)	⬆️
#single	43.06% <0%> (-0.01%)	⬇️

Impacted Files	Coverage Δ
pandas/core/arrays/array_.py	100% <100%> (ø)	⬆️
pandas/util/testing.py	87.71% <0%> (+0.09%)	⬆️

---

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[jreback]

lgtm. let's waiting on things though till we have fixed windows CI.

[jbrockmendel]

Can tm.to_array be replaced with pd.array then?

[TomAugspurger]

Replacing that turned up an issue with non-ns datetime64 / timedelta64 values. Pushing a fix for that in a bit.

…

On Wed, Jan 2, 2019 at 3:24 PM jbrockmendel ***@***.***> wrote: Can tm.to_array be replaced with pd.array then? — You are receiving this because you authored the thread. Reply to this email directly, view it on GitHub <#24571 (comment)>, or mute the thread <https://github.com/notifications/unsubscribe-auth/ABQHIoLf1SAvahB-3lBlaUcmz80qCt5Aks5u_SN2gaJpZM4ZnKb5> .

[TomAugspurger]

3d9cebe fixes the datetime / timedelta issue. pd.array isn't a drop-in replacement for tm.to_array, since to_array returns an ndarray for non-special cased dtypes. On Wed, Jan 2, 2019 at 3:43 PM Tom Augspurger <[email protected]> wrote:

…

Replacing that turned up an issue with non-ns datetime64 / timedelta64 values. Pushing a fix for that in a bit. On Wed, Jan 2, 2019 at 3:24 PM jbrockmendel ***@***.***> wrote: > Can tm.to_array be replaced with pd.array then? > > — > You are receiving this because you authored the thread. > Reply to this email directly, view it on GitHub > <#24571 (comment)>, > or mute the thread > <https://github.com/notifications/unsubscribe-auth/ABQHIoLf1SAvahB-3lBlaUcmz80qCt5Aks5u_SN2gaJpZM4ZnKb5> > . >

[jreback]

@jbrockmendel but maybe should use its as much as possible (e.g. hit the special cases, else hit pd.array)

[TomAugspurger]

Agreed. I tried that briefly, and things failed (haven't looked deeply yet). Not sure if it's a bug in pd.array or different semantics for tm.to_array.

[jreback]

thanks @TomAugspurger