I made a Data Scraping and Data Visualization about League of Legends champions, answering some data related questions.

The idea:

For several years of my life I played League of Legends, I would like to do some personal project about the game, I didn't find a dataset with the information about champions in the way I wanted, and that also with a code available to the public.

How it works:

Basically we have three files:

Data Analysis.ipynb --> Data Analysis in Jupyter/Colab

Scrapping_Colab.ipynb --> Scraping in Jupyter/Colab version

Scrapping_PC.ipynb --> Scraping in PC version

• You will need the files folder to run both Scraping versions.
• The main Dataset is lol_df.csv, and it is located in files folder.
• You can generate an updated lol_df.csv running any Scraping file.

Requirements for PC:

You will need to install all dependencies to run:

1. Python 3.8.10+
2. git clone https://github.com/gabrielcordeiro2/LOL-Champion-Analysis
3. pip3 install -r requirements.txt
4. python -m spacy download en_core_web_sm

Skills that i learned:

• Data Scraping

  Using: Requests, BeautifulSoup, cURL & Selenium.

• Data Cleansing

  Using: Pandas, Regex, Lambda functions & List comprehension.

• Data Visualization

  Using: Matplotlib, Numpy & Word cloud.