rumbin opened a new issue, #26034:
URL: https://github.com/apache/superset/issues/26034

   When using a _numeric_ column as the generic x-axis, the x-axis values 
aren't linearly distributed along the x-axis but they are evenly distributed, 
just as if they were categorical values
   
   #### How to reproduce the bug
   
   0. Have the `GENERIC_CHART_AXES` feature flag enabled
   1. Create a dataset or a SQLLab query with numerical columns, e.g.
   
   ```sql
   select
     *
   from (values
     (1,1)
     , (2,2)
     , (5,5)
     , (10,10)
   ) as v(x,y)
   ```
   
   2. Visualize the query/dataset as bar chart (or line chart)
   3. Use `x` as x-axis and, e.g., `max(y)` as y-axis
   4. See that the x-axis values are shown with equal spacing instead of the 
expected linear distribution of the x values
   
   ### Expected results
   
   This is what it should look like and what it did correctly in Superset 2.0.1:
   
   
![image](https://github.com/apache/superset/assets/1220356/baaa44e9-b397-4f77-bb74-ff545d81e853)
   
   
   ### Actual results
   
   X-axis values are seemingly treated as categorical values:
   
   
![image](https://github.com/apache/superset/assets/1220356/2d3aa5b5-9345-4da1-9390-44d8e02c0304)
   
   
   Any distribution/scatter/histogram plots based on this functionality are 
actually unusable due to this bug.
   
   ### Environment
   
   (please complete the following information):
   
   - browser type and version:
   - superset version: 3.0.2rc1
   - python version: `python --version`
   - node.js version: `node -v`
   - any feature flags active:
   
   ### Checklist
   
   Make sure to follow these steps before submitting your issue - thank you!
   
   - [ ] I have checked the superset logs for python stacktraces and included 
it here as text if there are any.
   - [ ] I have reproduced the issue with at least the latest released version 
of superset.
   - [ ] I have checked the issue tracker for the same issue and I haven't 
found one similar.
   
   ### Additional context
   
   Add any other context about the problem here.
   


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