With the upcoming 7 day step modification, it might be a good time to get a visual look at the data.

The hard part is knowing what to look for...

Over 7 days of steps, each step brings in 1 new combo into the model, and loses the first combo. This means the numbers have 3 possible actions...

Increase by 1, stay the same, or decrease by 1.

So for a first attempt, I will be looking at using frequency to populate the Y axis, putting a line across the graph at the expectancy, a blue line below by 1 standard deviation and a red line above the expectancy by 1 standard deviation. This will define the neutral range.

For the X axis, it will be the steps.

What we will have is each number being plotted by frequency at each step.

Now, that could get to be a busy graph with 10 different plots on it, so I want to incorporate a list of check boxes, default UNchecked, for each digit 0 through 9.

I am hoping to see what happens with regard to frequency at the draw level, rather than the entire week to week.

I may have to re arrange the output so that the standard deviation and the quartiles appear alongside one column's worth of distribution data.  Such that it looks like 

SD, Q1,Q2,Q3,0 freq, 0 percent, ... 9 freq, 9 percent. Then this data will need to be parsed to either skip rows to ensure column 1 data lines up or create a separate output file for each column so only column A data appears with column A, etc.

So we run, then read column A data, then read column B data and finally read column C data. Once loaded, the graph and check boxes can be generated.

Because the program screen output will be unchanged, I can use the graph to study numbers of interest, see how several numbers compare (deciding between ties in frequency) or even see the whole cluster of a graph with all 10 digits present.

Since frequency is being used, ranging is easy for Y, it is 0 to 30, with 15 being the center (and the expectancy). X is simply 1 to 7 for the steps.

Getting the correct data written should be as easy as properly formatting one writerow() command per column pass.

Visualization will be a clean sheet separate script, so I can cross reference data in the format I have gotten used to reading with the new graphing function. I will keep in mind the flexibility of the original concept by writing the visualizer to accept a variable number of input files so the same program that can process the pick 3 can also process the pick 5.

In retrospect I should have done this BEFORE trying a live test, but ideas evolve... the live test might be over before this idea is functional.

Time will tell...