## DO NOT MERGE. BUG: Fix .dropna() functionality for categorical indices

[rs2]

• closes Regression in 0.24: TypeError exception when using dropna on dataframe with categorical index #25087
• tests added / passed
• passes git diff upstream/master -u -- "*.py" | flake8 --diff
• whatsnew entry

The last whatsnew is https://github.com/pandas-dev/pandas/blob/master/doc/source/whatsnew/v0.24.0.rst

[codecov]

Codecov Report

Merging #25091 into master will decrease coverage by 49.48%.
The diff coverage is 100%.

@@             Coverage Diff             @@
##           master   #25091       +/-   ##
===========================================
- Coverage   92.37%   42.89%   -49.49%     
===========================================
  Files         166      166               
  Lines       52420    52420               
===========================================
- Hits        48423    22483    -25940     
- Misses       3997    29937    +25940

Flag	Coverage Δ
#multiple	?
#single	42.89% <100%> (ø)	⬆️

Impacted Files	Coverage Δ
pandas/core/frame.py	35.73% <100%> (-61.09%)	⬇️
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%> (-99.35%)	⬇️
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 124 more

---

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[codecov]

Codecov Report

Merging #25091 into master will not change coverage.
The diff coverage is 100%.

@@           Coverage Diff           @@
##           master   #25091   +/-   ##
=======================================
  Coverage   92.37%   92.37%           
=======================================
  Files         166      166           
  Lines       52420    52420           
=======================================
  Hits        48423    48423           
  Misses       3997     3997

Flag	Coverage Δ
#multiple	90.79% <100%> (ø)	⬆️
#single	42.89% <100%> (ø)	⬆️

Impacted Files	Coverage Δ
pandas/core/frame.py	96.82% <100%> (ø)	⬆️

---

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Δ = absolute <relative> (impact), ø = not affected, ? = missing data
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[rs2]

Related unexpected behavior:

# TypeError: Cannot cast array data from dtype('float64') to dtype('<U32') according to the rule 'safe'
'foo' in pd.Categorical(pd.interval_range(0.1, 0.2))

Works as expected for ints:

'foo' in pd.Categorical(pd.interval_range(42, 43))

.get_loc() shuld not be raisin TypeError.

[TomAugspurger]

Do we not need the alignment from the index anymore?

[rs2]

@TomAugspurger It turned out to be a bit wider issue. Kudos to @jorisvandenbossche for an insightful discussion. The behavior of an_index[mask], 'foo' in an_index, an_index.get_loc(mask) is currently inconsistent across various index types, in particular, Categorical(pd.interval_range(0.1, 3.14)), Categorical(pd.interval_range(1, 2)).

Does this require a separate issue, or I could just post repro snippets and outcomes as of 0.23.4 and 0.24.0 into #25087?

[WillAyd]

Closing for now given this hasn't been updated in a few weeks but ping if you'd like to reopen. The first and most important part of any PR is tests, so make sure you have that squared away first