Make sample argument uniform for normalize and feature_select

[gwaybio]

Description

Currently, the samples argument in the normalize function expects a string to be used in a pandas.DataFrame().query() call. However ,the samples argument in feature_select() (and all associated operations) expects the samples argument to be a list to be used in a pandas.DataFrame().loc[] call.

Here, I update all feature_select() operations to expect the pandas.DataFrame.query() call. I also update the documentation and tests.

What is the nature of your change?

• Bug fix (fixes an issue).
• Enhancement (adds functionality).
• Breaking change (fix or feature that would cause existing functionality to not work as expected).
• This change requires a documentation update.

Checklist

Please ensure that all boxes are checked before indicating that a pull request is ready for review.

• I have read the CONTRIBUTING.md guidelines.
• My code follows the style guidelines of this project.
• I have performed a self-review of my own code.
• I have commented my code, particularly in hard-to-understand areas.
• I have made corresponding changes to the documentation.
• My changes generate no new warnings.
• New and existing unit tests pass locally with my changes.
• I have added tests that prove my fix is effective or that my feature works.
• I have deleted all non-relevant text in this pull request template.

[codecov-commenter]

Codecov Report

Merging #311 (d9b06fe) into master (8e3c28d) will increase coverage by 0.08%.
The diff coverage is 100.00%.

@@            Coverage Diff             @@
##           master     #311      +/-   ##
==========================================
+ Coverage   95.25%   95.34%   +0.08%     
==========================================
  Files          57       57              
  Lines        3120     3134      +14     
==========================================
+ Hits         2972     2988      +16     
+ Misses        148      146       -2     

Flag	Coverage Δ
unittests	95.34% <100.00%> (+0.08%)	⬆️

Flags with carried forward coverage won't be shown. Click here to find out more.

Impacted Files	Coverage Δ
pycytominer/cyto_utils/features.py	89.79% <100.00%> (ø)
pycytominer/operations/correlation_threshold.py	100.00% <100.00%> (ø)
pycytominer/operations/get_na_columns.py	100.00% <100.00%> (ø)
pycytominer/operations/noise_removal.py	95.00% <100.00%> (+5.00%)	⬆️
pycytominer/operations/variance_threshold.py	100.00% <100.00%> (+2.94%)	⬆️
...tests/test_cyto_utils/test_feature_drop_outlier.py	100.00% <100.00%> (ø)
pycytominer/tests/test_feature_select.py	100.00% <100.00%> (ø)
...ests/test_operations/test_correlation_threshold.py	100.00% <100.00%> (ø)
...miner/tests/test_operations/test_get_na_columns.py	100.00% <100.00%> (ø)
...r/tests/test_operations/test_variance_threshold.py	100.00% <100.00%> (ø)

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[d33bs]

Nice work! Kudos also on the increased test coverage percentage. I thought things looked good with this PR and only had suggestions for enhancements. Generally I left comments in pycytominer/cyto_utils/features.py which apply to multiple files with the pd.DataFrame.query() repeated blocks. Please don't hesitate to let me know if you have any questions.