Tabulator: custom datetime sorter

[maximlt]

As already pointed out before Tabulator JS defines its own sorters, which can behave differently from df.sort_values. The result of these two sorters was different when applied to datetime columns that contain NaN values (this causes issues with the index of edit/click events returned when the sorters aren't aligned on their result...). Datetime cols are actually serialized as UNIX timestamps by Bokeh, and NaN values to -9223372036854776 (see bokeh/bokeh#10448). Tabulator JS was using its number built-in sorter to sorter this kind of column in the end, the NaN values being first when sorting in an ascending way. The default behavior of df.sort_values is put NaNs at the end (see https://pandas.pydata.org/docs/reference/api/pandas.Series.sort_values.html#pandas.Series.sort_values). This is where the two sorting algorithms were diverging. Pandas' df.sort_values has the na_position parameter that can be set to 'first', except that it applies to all the columns which I didn't want to do that now, as it affects all the dtypes. Instead this PR adds a custom sorter for datetime objects which always puts the NaNs at the end as df.sort_values.

[codecov]

Codecov Report

Merging #3839 (723e9e0) into master (affb9dd) will increase coverage by 0.00%.
The diff coverage is 100.00%.

@@           Coverage Diff           @@
##           master    #3839   +/-   ##
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  Coverage   82.86%   82.87%           
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  Files         222      222           
  Lines       32413    32421    +8     
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+ Hits        26860    26868    +8     
  Misses       5553     5553           

Flag	Coverage Δ
ui-tests	34.20% <0.00%> (-0.01%)	⬇️
unitexamples-tests	75.24% <100.00%> (+<0.01%)	⬆️

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Impacted Files	Coverage Δ
panel/tests/ui/widgets/test_tabulator.py	98.88% <ø> (ø)
panel/tests/widgets/test_tables.py	99.66% <ø> (ø)
panel/widgets/tables.py	88.44% <100.00%> (+0.08%)	⬆️

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[philippjfr]

Ready to merge?

[maximlt]

Yes