In this challenge, the student will use Matplotlib and Numpy to create visualizations to analyze the results from studies for potential treatments for squamous cell carcinoma (SCC). The student was provided with the complete data from their most recent animal study. In this study, 249 mice who were identified with SCC tumors received treatment with a range of drug regimens. Over the course of 45 days, tumor development was observed and measured. The purpose of this study was to compare the performance of Pymaceuticals’ drug of interest, Capomulin, against the other treatment regimens.
Tools used/imported:
Pandas
Matplotlib
Scipy
Numpy
Pandas is used to:
Load data files and store in dataframes
Merge files based on mouse ID
Clean data by removing duplicates that might skew the analysis
Create statistical calculations based on drug regimens tested
Scipy is used to calculate the correlation coefficient and linear regression model
Numpy and Matplotlib are then used to plot the datapoints created
