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Python script in Jupyter Notebooks to analyze Pandas DataFrames of drug regimen data and generate visualizations in MatPlotLib.

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pymaceuticals-data-viz

Data is imported from two .csv files and run in a Python script through Jupyter Notebook.

Data addresses mouse tumor volume response to treatment under several drug regimines: Capomulin, Ceftamin, Infubinol, Ketapril, Naftisol, Propriva, Ramicane, Stelasyn, Zoniferol, and a placebo control.

The data was cleaned of duplicate mice data. A summary table addresses the mean, median, variance, standard deviation, and standard error of the mean for the tumor volume for all 10 drugs tested.

The output folder holds graph .png files generated by the code that summarize the findings in several ways.

  • Bar charts show the total number of timepoints for all mice tested with each drug regimen.
  • Pie charts show the distribution of female versus male mice tested.
  • A box plot shows the final tumor volumes for all mice tested with four of the 10 drugs: Capomulin, Ramicane, Infubinol, and Ceftamin.
  • A line plot shows the tumor volume change for a mouse treated by Capomulin.
  • A scatter plot shows the average tumor volume by weight for each mouse treated with Capomulin. A line of best fit shows the correlation between these data points.

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Python script in Jupyter Notebooks to analyze Pandas DataFrames of drug regimen data and generate visualizations in MatPlotLib.

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