PERF: improve speed of nans in CategoricalIndex

[topper-123]

This is a minor follow-up to #21369.

>>> n = 100_000
>>> ci = pd.CategoricalIndex(['a']*n + ['b']*n + ['c']*n + [np.nan])
>>> np.nan in ci
19.5 us  # master
114 ns  # this PR

Using self.hasnans to check for nans is faster than self.isna().any() because it's cached.

[codecov]

Codecov Report

Merging #21493 into master will increase coverage by <.01%.
The diff coverage is 100%.

@@            Coverage Diff             @@
##           master   #21493      +/-   ##
==========================================
+ Coverage   91.89%   91.89%   +<.01%     
==========================================
  Files         153      153              
  Lines       49604    49604              
==========================================
+ Hits        45584    45586       +2     
+ Misses       4020     4018       -2

Flag	Coverage Δ
#multiple	90.3% <100%> (ø)	⬆️
#single	41.88% <0%> (ø)	⬆️

Impacted Files	Coverage Δ
pandas/core/indexes/category.py	97.09% <100%> (ø)	⬆️
pandas/util/testing.py	84.81% <0%> (+0.2%)	⬆️

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[jreback]

thanks @topper-123