As I cleaned up the output to give the needed info in a readable format, I had noticed a few things...

1. Using a percentage of total draws means the digit post script (H1, H2 etc...) is not needed, as the numbers that meet either hot or cold threshold can change. For instance in one column of the evening pick 3, when running with 35 draws for X, there was a column with 0 hots and only one cold. That means the numbers tended to fall within a tight tolerance of their 10% expectations. 12% or greater for Hot and 8% or less for Cold may be too much... I made it so that I could pass those in when calling the function.

2. Running on the pick 5 mid day with 50 for X showed an all Hot draw halfway through the Y draws (10)

3. The most common classifier is Neutral, that is less than 12% or greater than 8% of expectancy. Perhaps a run should be made with 11% and 9%?

4. I wanted a raw count of H N and C for each row, so I wrote a few more lines of code to display that. This is how you can quickly see that the Ns were dominant.

5. Trends change, the H gives way to N and C the larger Y is set... this could be the way to determine ideal X range, however. I am going to run a set with X=50 and Y=50 to see what patterns emerge (if any)

6. This is only an aggregator, like odd/even or high/low... still need a way to narrow down to a single pick.

Although I was thrilled to go from a blank screen to working code in a few hours, I did invest much time over the last week or so thinking about what I wanted the program to do and planning it out.

The addition of follower counting in a shorter term might be the next add in to this... if a recurring pattern is found, it would be nice to cross reference the follower distribution... if a pattern of HHH emerges, the counting script gives the HNC numbers that can be selected from the follower script distribution lists... such that if 2 is a hot number, and 2 is not very high on the follower list, it might be the indicator needed to pick that number.

That follower script is already functional, and probably not worth integrating into this code since I can simply run both and compare the output screens side by side. I just need to use a passable offset parameter to the follower script so it does not look at ALL of the draws... using pandas iloc[] was made for such a task... probably less than 5 lines of code.

Maybe Thursday will be a good day to make an attempt at that theory... a paper play to test the concept...

Happy Coding!