https://github.com/leftcoastnerdgirl/matplotlib_and_numpy

This project applies lessons using Matplotlib and Numpy
https://github.com/leftcoastnerdgirl/matplotlib_and_numpy

bar-charts box-and-whisker-plots correlation-analysis data-analytics data-visualization jupyter-notebook linear-regression numpy pandas-dataframe pandas-python r-value scatter-plot scipy scipy-stats

Last synced: 2 months ago
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This project applies lessons using Matplotlib and Numpy

• Host: GitHub
• URL: https://github.com/leftcoastnerdgirl/matplotlib_and_numpy
• Owner: LeftCoastNerdGirl
• Created: 2023-11-19T00:10:56.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2024-07-19T20:42:33.000Z (10 months ago)
• Last Synced: 2025-02-23T01:14:00.176Z (2 months ago)
• Topics: bar-charts, box-and-whisker-plots, correlation-analysis, data-analytics, data-visualization, jupyter-notebook, linear-regression, numpy, pandas-dataframe, pandas-python, r-value, scatter-plot, scipy, scipy-stats
• Language: Jupyter Notebook
• Homepage: https://extension.berkeley.edu/search/publicCourseSearchDetails.do?method=load&courseId=35106003
• Size: 304 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Using Matplotlib and Numpy for data visualization

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  

![image](https://github.com/user-attachments/assets/34f6d948-e447-44fc-8f32-a1e0eb1f2d88)

![image](https://github.com/user-attachments/assets/50a9cca8-d095-428f-bb6c-0a6dc7f35773)

Scipy is used to calculate the correlation coefficient and linear regression model  

![image](https://github.com/user-attachments/assets/d4ce52c8-e301-46ff-9dab-b35e65f6e37f)

Numpy and Matplotlib are then used to plot the datapoints created  

![image](https://github.com/user-attachments/assets/0b3e364b-1ebc-4021-8951-f7f4889088b7)

![image](https://github.com/user-attachments/assets/c47f990a-e719-4f3c-992b-0d6049113d3c)