Counter-Strike: Global Offensive is a 2012 multiplayer first-person shooter developed by Valve and Hidden Path Entertainment. It is the fourth game in the Counter-Strike series. It is one of the biggest eSports title out there. In this project we scrape and work on a dataset of all CSGO Athletes.
The entire flow of the project includes:
- Scrape the Dataset from this Website
- Perform Feature Engineering to create insightful columns
- Perform Exploratory Data Analysis to create insights and meaningful dashboards
├── scraping notebook.ipynb Notebook for Scraping the website
├── feature engineering.ipynb Notebook for deriving new features from Raw data
├── CSGO Player Dataset(Raw).csv Original Dataset about CSGO Player Dataset
├── CSGO Player Dataset(FE).csv Dataset with added features 'Kills' and 'Deaths' about CSGO Player Dataset
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A web browser.
OR
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Anaconda software.
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Very basic understanding of git and github:
- What are repositories (local - remote - upstream), issues, pull requests
- How to clone a repository, how to fork a repository, how to set upstreams
- Adding, committing, pulling, pushing changes to remote repositories
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For EDA and Visualisation
- Basic syntax and working of
python
.(This is a must) - Basic knowledge of
pandas
library. Reading this blog might help. - Basic knowledge of
matplotlib
library. Reading this blog might help. - Basic knowledge of
seaborn
library. Reading this blog might help. - Basic knowledge of
scikit learn
library. Reading this blog might help.
However the code is well explained, so anyone knowing the basics of Python can get a idea of what's happenning and contribute to this.
- Basic syntax and working of
Clone the project
git clone https://github.com/DSCKGEC/CS-GO-Professionals.git
Go to the project directory
cd CS-GO-Professionals
To run this:
pip install bs4
pip install pandas
pip install requests
Please read contributing.md for details on our code of conduct, and the process for submitting pull requests to us.
This project is licensed under the MIT License - see the LICENSE file for details.