NBA-MVP-2020-EDA

Analysis of voting patterns and their correlation to potential candidates' performence over the years to determine his probability of being crowned the NBAs' Most Valuable Player for season 2019-20.

Author: Sankalp Chourasia

Status: Open

Date of Commencement : 20th May

Report Outline: 10 step Foundational Methodology for Data Science by John Rollins

| Files |

Data Set : data_mvp.csv

Report :

      1. Phase 1-2-3 Business Understanding-Analytic Approach-Data Requirements.pdf

Code Base :

        1. Phase 4 Data Collection (Data Scrapping with Beautiful Soup).ipynb
        
        2. Phase 5-6 Data Understanding and Preparation (Feature Selection and Visualization).ipynb
        
        3. Phase 7 Data Modeling

References:

• Python for Data Analysis, 2nd Edition by Wes McKinney
• Github-Repo-for-NBA-Data-Scrapping
• Scikit-Learn-User-Guide
• Beatiful-Soup-User-Guide
• Seaborn-User-Guide