Pymaceuticals was an activity that uses fictional pharmaceutical data to test skills related to analyzing data. It supposed you had joined Pymaceuticals Inc., a burgeoning pharmaceutical company based out of San Diego. Pymaceuticals specializes in anti-cancer pharmaceuticals. In its most recent efforts, it began screening for potential treatments for squamous cell carcinoma (SCC), a commonly occurring form of skin cancer.
The assignment was to analyze data that had been pulled over a 45 day period relating to tumor development observations and measurements and the performance of Pymaceuticals drug of interest, Capomulin, versus the other treatments.
The work was done using Python via Jupyter Notebook along with matplotlib.
Findings at the conclusion of the assignment were that, with the exception of one outlier from the Infubinol trials, the most promising treatment regimens: Capomulin, Ramicane, Infubinol, and Ceftamin had consistent results. There was a strong corrilation between the average tumor volume compared to overall mouse weight and the distribution of female to male mice were nearly equal.
What follows are some examples of the plotted graphs and their meanings...
