Strange error that I am trying to solve. When I put in a diagnostic line to determine the data type of the output, both functions return type as Pandas.series

This was as simple as 

print(type(distribution_list))

Here is the problem... in one function it works, in the other function it tells me the list is unhashable and I should probably change type to a tuple... but that is wrong. Both lists contain similar data from similar calculations...

It SHOULD work, but does not.

One thing I had noticed while looking at the output of the follower numbers that coincided with the neutrals of the other function is that there are more followers considered Cold matching with raw frequency numbers classified as neutral... could that be the correlation? In the raw frequency neutral set AND in the follower frequency cold set?

I will not know until I solve the problem. Been frustrating at times, but this is really the "fun" part of coding, solving problems!

Worst case scenario, post the function to Chat GPT and have it find where I went wrong. You would be surprised at how much better LLMs work at coding well if you give them sample code. However... that is how coders get lazy. I try DIY first. I even try to keep libraries to a minimum if there is a way to code with straight Python. I started using pandas because it solves many problems out of the box with less code and high utility vs. the huge amount of code to do the same thing. For me, I could not imagine NOT putting lottery data into a Pandas data frame.

I thought the conversion would be easy because I am doing the same thing with the same data type... nothing is ever easy...