Exploratory Data Analysis on the IPL dataset collected from 2008-2019 as part of the TSF - GRIP July 2021.
Video Explanation Link (on LinkedIn): https://www.linkedin.com/posts/bhavan-naik_task5-gripjuly21-gripjuly2021-activity-6822057102471786496-0T9H
Dataset:
- The dataset is a .zip file (IPL.zip) consisting of 2 .csv files.
- The first .csv file : matches.csv
- It contains details about all the matches played in the IPL.
- It consists of 757 rows and 18 columns.
- The second .csv file : deliveries.csv
- It contains ball-to-ball detail about all the matches played.
- It consists of 179079 rows and 21 columns.
- Link to Dataset: https://bit.ly/34SRn3b
We perform all the basic data analysis on this dataset and complete the following tasks:
- Find out the most successful teams.
- Find out the most successful players.
- Find out the different factors contributing win or loss of a team.
- Suggest teams or players a company should endorse for its products.
- Create a video explaining all these interpretations.
This git repo consists of 4 files:
- Indian Premier League.zip file: Dataset
- IPL_EDA.ipynb file: Google Colab File (Python Notebook)
- ipl_eda.py: Python version of the Google Colab File
- README.md: README File for the Project
Project done by: Bhavan Naik