Have DTA._simple_new take dtype instead of tz

[jbrockmendel]

Allows for better code-sharing. I'm pretty sure after this we can get rid of _get_attributes_dict

[codecov]

Codecov Report

Merging #24665 into master will decrease coverage by <.01%.
The diff coverage is 96%.

@@            Coverage Diff             @@
##           master   #24665      +/-   ##
==========================================
- Coverage   92.37%   92.37%   -0.01%     
==========================================
  Files         166      166              
  Lines       52315    52322       +7     
==========================================
+ Hits        48328    48333       +5     
- Misses       3987     3989       +2

Flag	Coverage Δ
#multiple	90.79% <96%> (-0.01%)	⬇️
#single	43.07% <68%> (ø)	⬆️

Impacted Files	Coverage Δ
pandas/core/internals/blocks.py	94.3% <ø> (ø)	⬆️
pandas/core/indexes/datetimes.py	96.27% <100%> (+0.01%)	⬆️
pandas/core/arrays/datetimes.py	97.71% <100%> (+0.03%)	⬆️
pandas/tseries/offsets.py	96.69% <100%> (ø)	⬆️
pandas/core/arrays/datetimelike.py	97.67% <80%> (-0.19%)	⬇️
pandas/util/testing.py	88% <0%> (-0.1%)	⬇️

---

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[codecov]

Codecov Report

Merging #24665 into master will decrease coverage by <.01%.
The diff coverage is 96%.

@@            Coverage Diff             @@
##           master   #24665      +/-   ##
==========================================
- Coverage   92.37%   92.37%   -0.01%     
==========================================
  Files         166      166              
  Lines       52315    52322       +7     
==========================================
+ Hits        48328    48333       +5     
- Misses       3987     3989       +2

Flag	Coverage Δ
#multiple	90.79% <96%> (-0.01%)	⬇️
#single	43.07% <68%> (ø)	⬆️

Impacted Files	Coverage Δ
pandas/core/internals/blocks.py	94.3% <ø> (ø)	⬆️
pandas/core/indexes/datetimes.py	96.27% <100%> (+0.01%)	⬆️
pandas/core/arrays/datetimes.py	97.71% <100%> (+0.03%)	⬆️
pandas/tseries/offsets.py	96.69% <100%> (ø)	⬆️
pandas/core/arrays/datetimelike.py	97.67% <80%> (-0.19%)	⬇️
pandas/util/testing.py	88% <0%> (-0.1%)	⬇️

---

Continue to review full report at Codecov.

Legend - Click here to learn more
Δ = absolute <relative> (impact), ø = not affected, ? = missing data
Powered by Codecov. Last update 1ae466c...bee17cd. Read the comment docs.

[jreback]

thanks @jbrockmendel