This respository apply a Python Matplotlib to visualize a real-world pharmaceutical data. The data is sourced from 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.

These analysis used a complete data from their most recent animal study in two datasets in CSV format. Data set one is Mouse_metadata.csv wich includes 249 mice identified data with SCC tumor growth were treated through a variety of drug regimens, and their Sex, Age_months and Weight (g) identified. The other dataset is Study_results.csv file which includes the results of the study in each columns Mouse I,Timepoint,Tumor Volume (mm3), and Metastatic Sites.

The purpose of this study was to compare the performance of Pymaceuticals' drug of interest, Capomulin, versus the other treatment regimens. The analysis also generated all of the table and figures needed for the technical, and top-level summary report of the study. For this analysis both datasets imported, merged,cleaned and the aggregate data diplayed in to Python Pandas dataframes, visualized in Matplotlib, and other libraries used in order to make a stastical analysis.