fin-gal opened a new issue, #34737:
URL: https://github.com/apache/superset/issues/34737

   ### Bug description
   
   I am adding a value range filter to my dashboard.
   The data set I am applying it to is pulled from a postgreSQL query.
   It has a column we'll call `numerical_data`, it is of type `decimal`.
   `numerical_data` currently has values between 0.03 and 1.08 and some NULL 
values. One important detail, it only has one value above 1, which is 1.08, all 
others are below 1.
   
   When i add the value range filter, it only allows me to filter between 0 and 
1, only giving me the option to choose 0 or 1.
   What I expect is to have granular filtering from the minimum of my dataset 
to the maximum. Here it seems to be rounding the decimal to an integer and 
giving me only these options.
   
   I did a bit of tests and I am able to counter this behaviour and have proper 
filtering if I:
   
   - Filter the initial data set to only give me values below 1
   - Add a pre-filter on the filter itself again giving me only values below 1 
(I guess this is the same as the previous option).
   
   I am not sure if this might be correlated to #33206 .
   
   I also modified the data to check some other conditions:
   When my data is spread between 0.03 and 2.16, with multiple values between 1 
and 2, I get:
   - When left as is, integer only filtering with options: 0, 1 and 2
   - When pre filtered for only values below 2: integer filtering with options 
0 and 1
   - When pre filtered for only values below 1: decimal filtering
   
   ### Screenshots/recordings
   
   _No response_
   
   ### Superset version
   
   5.0.0
   
   ### Python version
   
   3.9
   
   ### Node version
   
   16
   
   ### Browser
   
   Chrome
   
   ### Additional context
   
   _No response_
   
   ### Checklist
   
   - [x] I have searched Superset docs and Slack and didn't find a solution to 
my problem.
   - [x] I have searched the GitHub issue tracker and didn't find a similar bug 
report.
   - [ ] I have checked Superset's logs for errors and if I found a relevant 
Python stacktrace, I included it here as text in the "additional context" 
section.


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