That was really cool! So I ended up having to look deeper into matplotlib for some
additional tools; I had some formatting issues on my x-axis for all of the birth data
where I was labeling the axis based on the number of the day (1-365) throughout the year
but I was able to figure out how to use matplotlib.dates to better label the x-axis with
respect to the months where things were occurring for easier readability.
Also, turns out you can use LaTeX to embed formulas into the Jupyter notebook. I kind
of figured that was possible, but I wasn't expecting it to just work, so that made writing
the results and analysis portion of my probability look at the problem way cleaner. My
backup plan was to make the equations elsewhere and have to import them as pictures, so
I'm happy that I was able to keep that portion more dynamic if I ever needed to go back
and make any changes/additions/corrections.
I'm bummed I wasn't able to find a pattern that explained what I was hoping for, but
it was really cool to dive into that data to look for it anyway. Turns out, math wins the
data again, I guess.
I'm going to be using frequency data for births on given dates over the course of
a 10-year period. This will involve a few plots and probably some data tables to
represent patterns in the data and dive into the birthday paradox.
Pat Wick
pwick