Check if NPY_NAT is NA for int64 in rank() (#32859) #35533
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Seems reasonable. Can you run the benchmarks for this to make sure it doesn't introduce a regression? |
WillAyd
added
the
NA - MaskedArrays
jbrockmendel
reviewed
Aug 4, 2020
| @@ -840,7 +840,7 @@ def rank_1d( | |||
| elif rank_t is float64_t: | |||
| mask = np.isnan(values) | |||
| elif rank_t is int64_t: | |||
| mask = values == NPY_NAT | |||
| mask = missing.isnaobj(values) | |||
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this is going to be all-False
We probably need to specifically handle datetimelike case in which the existing check is correct
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Hmmm, I think I misunderstood what types should return true. I'll revisit this another time if I get the chance. |
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black pandasgit diff upstream/master -u -- "*.py" | flake8 --diffUsed
missing.isnaobj()to try to handle the suggestion from @jbrockmendel. Lmk if this might cause other issues.