The script itself is nothing I have not used in other scripts, so I don't expect any protracted length of time in coding. Following the similar format of reading from a csv file... the planned work flow...

Add x and y as passed in to determine how many draws to use.

Read csv input into a pandas data frame because it is incredibly powerful to calculate offsets.

Take the last Y draws and put them into a list, in order. 

Jump x +y draws (a variable I will label "depth") back and count the frequency distribution of all digits 0 to 9 for X draws.

Assign rank by requesting the distribution from the default pandas statistics functions, adding the labels to the output (H1 through C3)

Using that distribution construct, assign the Hx/Nx/Cx patterns to the last Y draws.

Perform this as a funcrion that can loop through any pick n game, like I made for followers... one script can run on pick2 to pick 5...

Print the results to the display...

The trick here will be to find out how many draws to collect the X data from, as the most likely starting candidate for Y will be 7, as it is the max advanced play on daily games.

If 30 draws is the right amount, then a simple run with x=30 and Y=7 should hopefully explain how hot and cold numbers tend to distribute in the short term... but the program.will only need a weekly run, unlike the daily requirement of the follower script.