dosubot[bot] commented on issue #30301:
URL: https://github.com/apache/superset/issues/30301#issuecomment-2354199490

   <!-- Answer -->
   I found a similar closed issue that might be relevant to your problem: 
[[Table Viz] "unsupported operant type errors" in percentage 
metrics](https://github.com/apache/superset/issues/15440) 
<sup>[[1]](https://github.com/apache/superset/issues/15440)</sup>.
   
   The error "The column 'start_rate' must be numeric" occurs because the 
Histogram chart in Superset requires the specified column to be numeric. The 
`histogram` function in the `superset/utils/pandas_postprocessing/histogram.py` 
file checks if the column is numeric and raises a `ValueError` if it is not.
   
   To ensure that the `start_rate` column is treated as numeric, you should 
verify that its datatype in the Postgres database is correctly set to a numeric 
type (e.g., `decimal`, `float`, `integer`). Additionally, ensure that the 
column is included in the `numeric_columns` list in the form data for the 
Histogram chart.
   
   Here is the relevant part of the `histogram` function:
   
   ```python
   def histogram(
       df: DataFrame,
       column: str,
       groupby: list[str] | None,
       bins: int = 5,
       cumulative: bool = False,
       normalize: bool = False,
   ) -> DataFrame:
       """
       Generate a histogram DataFrame from a given DataFrame.
   
       Parameters:
       df (DataFrame): The input DataFrame.
       column (str): The column of the DataFrame to calculate the histogram on.
       groupby (list[str]): The columns to group by. If empty, no grouping is 
performed.
       bins (int): The number of bins to use for the histogram. Default is 5.
       cumulative (bool): Whether to calculate a cumulative histogram. Default 
is False.
       normalize (bool): Whether to normalize the histogram. Default is False.
   
       Returns:
       DataFrame: A DataFrame where each row corresponds to a group (or the 
entire DataFrame if no grouping is performed),
                  and each column corresponds to a histogram bin. The values 
are the counts in each bin.
       """
   
       if groupby is None:
           groupby = []
   
       # check if the column is numeric
       if not np.issubdtype(df[column].dtype, np.number):
           raise ValueError(f"The column '{column}' must be numeric.")
   ```
   
   Ensure that the `start_rate` column is included in the `numeric_columns` 
list in the form data. If it is not, you will need to update the form data to 
include it. Additionally, verify that the column's datatype in the Postgres 
database is correctly set to a numeric type 
<sup>[[2]](https://github.com/apache/superset/blob/master/superset/viz.py)</sup><sup>[[3]](https://github.com/apache/superset/blob/master/superset/utils/pandas_postprocessing/histogram.py)</sup>.
   
   
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