The Pymaceuticals challnage examines different cancer treatments and thier efficacy on labratory mice. The study looks at multiple treatemnts and then later focuses on four for further analysis. Observations and Analysis can be found below.
- Python 3.6
- Jupyter Notebook
- Pandas
- MatPlotLib
- Scipy.stats
- Numby
- PyPlot
Repo contains folder whith Jupyter notebook and resources Please use notebood titled:
pymaceuticals.ipynb
Overall Analysis:
- The bar graphs show the Drug Regimen Capomulin has the maximum mice number (230), and Zoniferol has the smaller mice number (182).
- 248 total mice were in the study (after removing dupliates)
- Total count of mice by gender are roughly equal.
- 124 female mice
- 125 male mice.
- The correlation between mouse weight, and average tumor volume is 0.84. There is a strong positive correlation, between mouse weight and tumor volume.
- The regression analysis shows the average tumor volume changes with changes occuring to the weight of mice.
- From the four analyzed treatments Capomulin and Ramicane show reductions in the size of tumors. Two identical bar charts showing the number of treatment counts. The charts were generated by using both Pandas's DataFrame.plot() and Matplotlib's pyplot.
- Capomulin
- Ramicane
- Infubinol
- Ceftamin
Analysis:
Analysis: Approximatly equal number of make and female mice are int ehh study.
Quartiles, IQR, and potential outliers across all the four treatment regimens was quantitatively determined.
Box and Whisker Plot
Mouse weight correlates strongly (R-squared of 0.84) with average tumor volume. Correlating only with the final tumor volume to efficacy of reginment without factorinig in mouse weight may skew the data related to efficacy.
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