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Analyzed the pharmaceutical data for potential treatments to squamous cell carcinoma (SCC), a commonly occurring form of skin cancer. 250 mice were treated through a variety of drug regimes over the course of 45 days.

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Python Matplotlib Project - Pharmaceutical Analysis

Pymaceuticals Inc

Laboratory

In this work, I analyzed the pharmaceutical data for potential treatments to squamous cell carcinoma (SCC), a commonly occurring form of skin cancer. 250 mice were treated through a variety of drug regimes over the course of 45 days. Their physiological responses were then monitored over the course of that time. The objective is to analyze the data to show how four treatments (Capomulin, Infubinol, Ketapril, and Placebo) compare.

Overview

My tasks are to do the following:

  • Creating a scatter plot that shows how the tumor volume changes over time for each treatment.
  • Creating a scatter plot that shows how the number of metastatic (cancer spreading) sites changes over time for each treatment.
  • Creating a scatter plot that shows the number of mice still alive through the course of treatment (Survival Rate)
  • Creating a bar graph that compares the total % tumor volume change for each drug across the full 45 days.

Avg Tumor Volume vs Avg Mouse Weight (Capomulin Regimen)

Final Tumor Volume by Drugs

Demographics Pie

Time Point Capomulin

About

Analyzed the pharmaceutical data for potential treatments to squamous cell carcinoma (SCC), a commonly occurring form of skin cancer. 250 mice were treated through a variety of drug regimes over the course of 45 days.

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