Wrap dropna

[dougbrn]

Change Description

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  Resolves MVP: Wrapping dropna #11.

Solution Description

Wraps dropna and enables hierarchical column names to work within the subset kwarg. Additionally, adds the on_nested kwarg to allow users to specify a nested layer to use dropna on, the motivation being that a user just wants to run on a layer and doesn't want to use a subset of columns within that layer.

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[github-actions]

Before [b822a14]	After [28f018d]	Ratio	Benchmark (Parameter)
1.44±0.6s	3.00±0.8s	~2.08	benchmarks.time_computation
4.08k	1.8k	0.44	benchmarks.mem_list

Click here to view all benchmarks.

[codecov]

Codecov Report

All modified and coverable lines are covered by tests ✅

Project coverage is 94.92%. Comparing base (b822a14) to head (b63a49c).

Additional details and impacted files

@@            Coverage Diff             @@
##             main      #26      +/-   ##
==========================================
+ Coverage   94.49%   94.92%   +0.43%     
==========================================
  Files          13       13              
  Lines         563      611      +48     
==========================================
+ Hits          532      580      +48     
  Misses         31       31              

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[hombit]

Thank you, it is great!

[wilsonbb]

Just some drive-by comments since I was reading the PR to understand the current nested-pandas state.

A more general comment: I would assume as a user I would be interested in trying something like

df.dropna(axis='columns', on_nested=True)

and that it would drop NaNs from all of the base columns as well as all of the columns in each of the nested frames. But it looks like this isn't currently possible with the requirement that that we only target on nested structure though I may be reading incorrectly. Not necessarily a blocker for a MVP, but wanted to comment on my surprise