It looks like the neutrals in the raw frequency do not necessarily line up with the neutrals in follower frequency.

I am specifically looking at the case where the raw frequency of a draw is classified as NNN. Sometimes the follower frequency is classified as NNN, but also there can be colds and hots mixed in for the same classified draw.

I already count the number of followers for each column, so the simple add will be getting the percentage of the number of followers to the number of follower samples. If I have 1500 samples and the followers of the last draw first position was 150, then that would be the expected 10%. Maybe the variance in this number might help to decide which classification of follower might end up matching the neutral classification in the raw frequency...

Trying to build guidelines so that there is less guesswork in making a pick.

I am wondering if there is some other way to apply a frequency count so that a third function can be written to sort of "triangulate" the whole thing. Free styling at this point.

Also, I have to cook up a back test routine and capture the data to get a read on long term trends with the follower frequencies matching up to raw frequency data. I have the rough outline... 

1. Set the offset to 7, capture that classifier data to a .csv file. In this way, I have something that exactly matches the draw history

2. Increment the offset by 7, repeat, but only capture the first 7 in the classifier data.

3. Repeat this until the 1500 draws in the follower frequency run out of room at the start of draw history.

4. Isolate the classifiers in each and put into a spreadsheet where the classifier combo for each draw can be concatenated... such as NNN and NCH would be written as NNNNCH.

5. Find the most frequent combined overall classifier in the resultant list.

The hope is to have a fair chance at making one good guess by picking from the neutral list of raw frequency and matching it to the right set from the followers. Hopefully this time I am asking the right questions...

Getting bored of not playing anything so I am probably going back to a QP on the PA match 6 until I am ready for live tests. Cost is the same at $14/week.

I will be making a new version for writing output, because V3 works and I don't intend on losing it... so V4 will be the back test version. Important that I kept V2, because it allowed me to verify the process in V3.

Before the Chat GPT era existed, we used to troubleshoot with stack overflow, that is where I found my issue with Pandas series and how to resolve it. Old school!