Multiindex support for pack_df

[hombit]

This PR brings support of pandas multiindex, and hopefully, for other different index types

Change Description

• My PR includes a link to the issue that I am addressing

Solution Description

Code Quality

• I have read the Contribution Guide
• My code follows the code style of this project
• My code builds (or compiles) cleanly without any errors or warnings
• My code contains relevant comments and necessary documentation

Project-Specific Pull Request Checklists

Bug Fix Checklist

• My fix includes a new test that breaks as a result of the bug (if possible)
• My change includes a breaking change
  • My change includes backwards compatibility and deprecation warnings (if possible)

New Feature Checklist

• I have added or updated the docstrings associated with my feature using the NumPy docstring format
• I have updated the tutorial to highlight my new feature (if appropriate)
• I have added unit/End-to-End (E2E) test cases to cover my new feature
• My change includes a breaking change
  • My change includes backwards compatibility and deprecation warnings (if possible)

Documentation Change Checklist

• Any updated docstrings use the NumPy docstring format

Build/CI Change Checklist

• If required or optional dependencies have changed (including version numbers), I have updated the README to reflect this
• If this is a new CI setup, I have added the associated badge to the README

Other Change Checklist

• Any new or updated docstrings use the NumPy docstring format.
• I have updated the tutorial to highlight my new feature (if appropriate)
• I have added unit/End-to-End (E2E) test cases to cover any changes
• My change includes a breaking change
  • My change includes backwards compatibility and deprecation warnings (if possible)

[codecov]

Codecov Report

All modified and coverable lines are covered by tests ✅

Project coverage is 98.65%. Comparing base (631787f) to head (9b7554b).
Report is 6 commits behind head on main.

Additional details and impacted files

@@            Coverage Diff             @@
##             main      #78      +/-   ##
==========================================
+ Coverage   98.52%   98.65%   +0.12%     
==========================================
  Files          15       15              
  Lines         816      816              
==========================================
+ Hits          804      805       +1     
+ Misses         12       11       -1     

☔ View full report in Codecov by Sentry.
📢 Have feedback on the report? Share it here.

[github-actions]

Before [92b422d]	After [2220bd7]	Ratio	Benchmark (Parameter)
32.9±0.9ms	36.3±3ms	~1.10	benchmarks.AssignSingleDfToNestedSeries.time_run
8.23±0.1ms	8.88±0.02ms	1.08	benchmarks.NestedFrameAddNested.time_run
57.4±2ms	59.7±3ms	1.04	benchmarks.ReassignHalfOfNestedSeries.time_run
88.4M	90.9M	1.03	benchmarks.NestedFrameQuery.peakmem_run
6.32±0.1ms	6.46±0.07ms	1.02	benchmarks.NestedFrameQuery.time_run
88.4M	89.1M	1.01	benchmarks.NestedFrameReduce.peakmem_run
5.12±0.04ms	5.19±0.06ms	1.01	benchmarks.NestedFrameReduce.time_run
257M	257M	1.00	benchmarks.AssignSingleDfToNestedSeries.peakmem_run
86M	86.1M	1.00	benchmarks.NestedFrameAddNested.peakmem_run
276M	269M	0.97	benchmarks.ReassignHalfOfNestedSeries.peakmem_run

Click here to view all benchmarks.

[hombit]

@dougbrn I think benchmarks.AssignSingleDfToNestedSeries.time_run performance regression is real, but I see no simple way to do it fast and correct for different index types...

[dougbrn]

Looks good!