Hi Len Stockdale   I hope this might help .....  I am trying to achieve this using python script in the model .

Choose Python from the script options:  Add the following script to the Python node.

import pandas as pd

# Sample DataFrame creation
df = pd.DataFrame({
    'CustomerName': inputDF["CustomerName"]
})

# Define bins and labels based on row index
bins = [-float('inf'), 10, 100, 1000, float('inf')]
labels = ['0-10', '10-100', '100-1000', '1000+']


# Create a new column with the bin labels based on index
df['Row_Index'] = pd.cut(df.index, bins=bins, labels=labels, right=False)

# Display the DataFrame
print(df)

Note: Replace

CustomerName with data warehouse session column in your actual data.Also you need to replace the Row Ranges in script.

Click the "Auto-detect" option.

After detection, check the preview.

Run the model to process the data.
 

Now ..

Go to the "Discover" tab.
Add the Row_Index column to the rows.
Add the distinct count of the data warehouse session column.

For You Scenario you add  Row range as the Filter like the following Image:

Hope I have understood your scenario ...

Thanks ,

Raja Sambasivam