GroupBy: Avoid guessing variable types

[janezd]

Issue

The Group By widget will fail on Pandas 3.0.

Group by currently computes aggregations, puts them into a pandas data frame and then guesses data types - at least in part. In particular, it tries to interpret columns as time and creates a TimeVariable if conversion succeeds. In tests, we have a concatenation of numeric data that results in value "1.0 1.0". Pandas 3.0 now converts this to January 1st 1970 (I think), so the column becomes a time variable and appears among primitive attributes, not metas(!).

Description of changes

I think a proper solution is to define how to construct variables with aggregations. It can be

• a fixed type (e.g. StringVariable for concatenation, ContinuousVariable for Span...)
• a copy of the existing variable (e.g. for Mode, Min value, Random value...)
• a variable of the same type as the existing variable (Mean...)

The difference between the latter two cases is that it resets the number of decimals.

I modified one test. Apparently it assumes that Count and Count Defined for string variables will be metas, but as far as I see, they are attributes. This PR keeps the behaviour, so I don't understand why tests were failing before.

Includes

• Code changes
• Tests

[codecov]

Codecov Report

Attention: Patch coverage is 98.21429% with 1 line in your changes missing coverage. Please review.

Project coverage is 88.21%. Comparing base (60a2f61) to head (c575527).
Report is 5 commits behind head on master.

Additional details and impacted files

@@            Coverage Diff             @@
##           master    #6906      +/-   ##
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+ Coverage   88.19%   88.21%   +0.01%     
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  Files         326      326              
  Lines       71233    71290      +57     
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+ Hits        62827    62887      +60     
+ Misses       8406     8403       -3