Surface NumPy FutureWarning about comparisons

[TomAugspurger]

Closes #22698

Specifically, see
#22698 (comment).

I don't think we need to worry about the others in #22698 (comment) datetimearray and integer array. I couldn't reproduce the returning a scalar behavior with those.

[TomAugspurger]

Oh, I was a bit confused... This happens with IntegerArray

In [7]: a = pd.array([1, None], dtype='Int64')

In [8]: a == 'a'
---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-8-3812dba97b6d> in <module>
----> 1 a == 'a'

~/sandbox/pandas/pandas/core/arrays/integer.py in cmp_method(self, other)
    561                 mask = self._mask | mask
    562
--> 563             result[mask] = op_name == 'ne'
    564             return result
    565

TypeError: 'bool' object does not support item assignment

So right now IntegerArray.__eq__(other) is broken when the op is using the deprecated behavior.

I don't think showing a warning here is useful. We could work around it I suppose?

[codecov]

Codecov Report

Merging #26966 into master will decrease coverage by <.01%.
The diff coverage is 100%.

@@            Coverage Diff             @@
##           master   #26966      +/-   ##
==========================================
- Coverage   91.87%   91.87%   -0.01%     
==========================================
  Files         180      180              
  Lines       50746    50744       -2     
==========================================
- Hits        46623    46621       -2     
  Misses       4123     4123

Flag	Coverage Δ
#multiple	90.47% <100%> (ø)	⬆️
#single	41.1% <100%> (-0.09%)	⬇️

Impacted Files	Coverage Δ
pandas/core/indexes/base.py	96.92% <100%> (+0.21%)	⬆️
pandas/io/gbq.py	88.88% <0%> (-11.12%)	⬇️
pandas/core/frame.py	96.89% <0%> (-0.12%)	⬇️

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[codecov]

Codecov Report

Merging #26966 into master will decrease coverage by <.01%.
The diff coverage is 100%.

@@            Coverage Diff             @@
##           master   #26966      +/-   ##
==========================================
- Coverage   91.87%   91.87%   -0.01%     
==========================================
  Files         180      180              
  Lines       50746    50744       -2     
==========================================
- Hits        46623    46621       -2     
  Misses       4123     4123

Flag	Coverage Δ
#multiple	90.47% <100%> (ø)	⬆️
#single	41.1% <100%> (-0.09%)	⬇️

Impacted Files	Coverage Δ
pandas/core/indexes/base.py	96.92% <100%> (+0.21%)	⬆️
pandas/io/gbq.py	88.88% <0%> (-11.12%)	⬇️
pandas/core/frame.py	96.89% <0%> (-0.12%)	⬇️

---

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Δ = absolute <relative> (impact), ø = not affected, ? = missing data
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[jreback]

looks fine. do we need to catch / suppress this in any of our tests?

[TomAugspurger]

I don’t think we hit this anywhere else. If we did the NumPy dev build would be failing.

[jreback]

k thanks @TomAugspurger