Parallelizable DataFrame/Series mean

[TheNeuralBit]

Fixes #22171

This adds a parallelizable custom implementation of DeferredSeries.mean, which uses sum()/count(). In addition:

• DeferredDataFrame leverages this implementation through _agg_method
• Updates tests which previously verified that mean is not parallelizable. Added new tests for mean(skipna=False).

GitHub Actions Tests Status (on master branch)

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[codecov]

Codecov Report

Merging #22174 (a21bda8) into master (a21bda8) will not change coverage.
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@@           Coverage Diff           @@
##           master   #22174   +/-   ##
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  Coverage   74.21%   74.21%           
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  Files         702      702           
  Lines       92829    92829           
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  Hits        68892    68892           
  Misses      22670    22670           
  Partials     1267     1267           

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[TheNeuralBit]

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[TheNeuralBit]

Run Python PreCommit

[AnandInguva]

Looks good.

[AnandInguva]

Can we make skipna as keyword argument?

Suggested change

	def mean(self, skipna, **kwargs):
	def mean(self, skipna=True, **kwargs):

[AnandInguva]

Following this https://pandas.pydata.org/docs/reference/api/pandas.Series.mean.html#pandas.Series.mean

[TheNeuralBit]

That's actually what the decorators do - populate_defaults pulls the default values from the panda implementation of the function, so we don't have to duplicate them here.