KelliExMachina / Pymaceuticals

Comparing the performance of Pymaceuticals' drug of interest, Capomulin, versus the other treatment regimens. Generated tables , figures and graphs.

Pymaceuticals Observations and Insights

• In this study, 248 mice identified with SCC tumor growth were treated through a variety of drug regimens. Over the course of 45 days, tumor development was observed and measured.
• The number of data points for each Drug Regimen were all above 100 and the study had a near identical number of male and female mice.
• Out of four drugs of interest (Capomulin, Ramicane, Infubinol, and Ceftamin) only Infubinol had one outlier data point and both Capomulin and Ramicane appeared to be equally effective.
• Mouse weight correlated strongly (0.84) with average tumor volume.

MouseMeta Data

	Mouse ID	Drug Regimen	Sex	Age_months	Weight (g)
0	k403	Ramicane	Male	21	16
1	s185	Capomulin	Female	3	17
2	x401	Capomulin	Female	16	15
3	m601	Capomulin	Male	22	17
4	g791	Ramicane	Male	11	16

Study Result Data

	Mouse ID	Timepoint	Tumor Volume (mm3)	Metastatic Sites
0	b128	0	45.0	0
1	f932	0	45.0	0
2	g107	0	45.0	0
3	a457	0	45.0	0
4	c819	0	45.0	0

Datas Combined

	Mouse ID	Timepoint	Tumor Volume (mm3)	Metastatic Sites	Drug Regimen	Sex	Age_months	Weight (g)
0	b128	0	45.0	0	Capomulin	Female	9	22
1	f932	0	45.0	0	Ketapril	Male	15	29
2	g107	0	45.0	0	Ketapril	Female	2	29
3	a457	0	45.0	0	Ketapril	Female	11	30
4	c819	0	45.0	0	Ketapril	Male	21	25

Checked Duplicate Mouse ID

	Mouse ID	Timepoint	Tumor Volume (mm3)	Metastatic Sites	Drug Regimen	Sex	Age_months	Weight (g)
107	g989	0	45.000000	0	Propriva	Female	21	26
137	g989	0	45.000000	0	Propriva	Female	21	26
329	g989	5	48.786801	0	Propriva	Female	21	26
360	g989	5	47.570392	0	Propriva	Female	21	26
620	g989	10	51.745156	0	Propriva	Female	21	26
681	g989	10	49.880528	0	Propriva	Female	21	26
815	g989	15	51.325852	1	Propriva	Female	21	26
869	g989	15	53.442020	0	Propriva	Female	21	26
950	g989	20	55.326122	1	Propriva	Female	21	26
1111	g989	20	54.657650	1	Propriva	Female	21	26
1195	g989	25	56.045564	1	Propriva	Female	21	26
1380	g989	30	59.082294	1	Propriva	Female	21	26
1592	g989	35	62.570880	2	Propriva	Female	21	26

Removed Duplicates

	Mouse ID	Timepoint	Tumor Volume (mm3)	Metastatic Sites	Drug Regimen	Sex	Age_months	Weight (g)
0	b128	0	45.0	0	Capomulin	Female	9	22
1	f932	0	45.0	0	Ketapril	Male	15	29
2	g107	0	45.0	0	Ketapril	Female	2	29
3	a457	0	45.0	0	Ketapril	Female	11	30
4	c819	0	45.0	0	Ketapril	Male	21	25

Summary Statistics

	Mean	Median	Variance	STD	SEM
Drug Regimen
Capomulin	40.68	41.56	24.95	4.99	0.33
Ceftamin	52.59	51.78	39.29	6.27	0.47
Infubinol	52.88	51.82	43.13	6.57	0.49
Ketapril	55.24	53.70	68.55	8.28	0.60
Naftisol	54.33	52.51	66.17	8.13	0.60
Placebo	54.03	52.29	61.17	7.82	0.58
Propriva	52.38	50.78	43.22	6.57	0.53
Ramicane	40.22	40.67	23.49	4.85	0.32
Stelasyn	54.23	52.43	59.45	7.71	0.57
Zoniferol	53.24	51.82	48.53	6.97	0.52

Summary Statistics (using aggregation method .agg )

	Mean Total Volume	Median Total Volume	Total Volume Variance	Tumor Volume Std. Dev.	Tumor Volume Std. Err.
Drug Regimen
Capomulin	40.68	41.56	24.95	4.99	0.33
Ceftamin	52.59	51.78	39.29	6.27	0.47
Infubinol	52.88	51.82	43.13	6.57	0.49
Ketapril	55.24	53.70	68.55	8.28	0.60
Naftisol	54.33	52.51	66.17	8.13	0.60
Placebo	54.03	52.29	61.17	7.82	0.58
Propriva	52.38	50.78	43.22	6.57	0.53
Ramicane	40.22	40.67	23.49	4.85	0.32
Stelasyn	54.23	52.43	59.45	7.71	0.57
Zoniferol	53.24	51.82	48.53	6.97	0.52

Bar Graph (using Pandas )

Bar Graph (using Pyplot)

Pie Charts

Generate a pie plot using both Pandas's DataFrame.plot() and Matplotlib's pyplot that shows the distribution of female or male mice in the study.

We need to create a DataFrame to group by 'Sex' column

	Sex
Sex
Female	930
Male	958

Pie Graph(using pandas)

Generate a pie plot showing the distribution of female versus male mice using pyplot

Pie Graph (using pyplot)

Generate a pie plot showing the distribution of female versus male mice using pyplot

Quartiles, Outliers and Boxplots

• In this section I need to calculate the final tumor volume of each mouse across four of the most promising treatment regimens: Capomulin, Ramicane, Infubinol, and Ceftamin. Then calculate the quartiles and IQR and quantitatively determine if there are any potential outliers across all four treatment regimens.

	Mouse ID	Timepoint	Tumor Volume (mm3)	Metastatic Sites	Drug Regimen	Sex	Age_months	Weight (g)
0	a203	45	67.973419	2	Infubinol	Female	20	23
1	a251	45	65.525743	1	Infubinol	Female	21	25
2	a262	45	70.717621	4	Placebo	Female	17	29
3	a275	45	62.999356	3	Ceftamin	Female	20	28
4	a366	30	63.440686	1	Stelasyn	Female	16	29
...	...	...	...	...	...	...	...	...
244	z435	10	48.710661	0	Propriva	Female	12	26
245	z578	45	30.638696	0	Ramicane	Male	11	16
246	z581	45	62.754451	3	Infubinol	Female	24	25
247	z795	45	65.741070	3	Naftisol	Female	13	29
248	z969	45	73.867845	4	Naftisol	Male	9	30

Capomulin potential outliers: []
Ramicane potential outliers: []
Infubinol potential outliers: [36.321345799999996]
Ceftamin potential outliers: []

Box Plot

Generate a box plot of the final tumor volume of each mouse across four regimens of interest

Line Plot

• Generate a line plot of tumor volume vs. time point for a mouse treated with 'Capomulin'

Correlation Coefficient & Linear Regression

• Calculate the correlation coefficient and linear regression model between mouse weight and average tumor volume for the Capomulin treatment. Plot the linear regression model on top of the previous scatter plot.

The correlation between mouse weight and the average tumor volume is 0.84

Scatter Plot

• Generate a scatter plot of average tumor volume vs. mouse weight for the Capomulin regimen