/webscraping

Implementing the web scraping technique for data retrieval and tools to exploit them.

Primary LanguageJupyter Notebook

Web scraping

Implementing web scraping techique to retrieve data and tools to exploit it.

This project aims to utilize web scraping techniques to acquire the ability to use data available on the web in another format. The web page used in this project is available on Wikipedia: https://en.wikipedia.org/wiki/List_of_countries_by_income_equality

Included files:

WebScraping_wikipedia_Notebook.ipynb: This is the Jupyter notebook that contains the source code used for web scraping.

README.txt: This file.

Instructions to run the project:

Download the files from this repository to your computer.

Access Google Colab or JupyterLab in your web browser and upload the file WebScraping_wikipedia_Notebook.ipynb.

In your environment, make sure you have access to the necessary Python libraries, such as Pandas, NumPy, Seaborn, and Matplotlib. If you don't have them, you can install them using the following command: !pip install [library name].

Follow the detailed instructions in the Jupyter notebook to perform web scraping and subsequent data analysis.

Credits:

The web page used in this project was taken from Wikipedia: https://en.wikipedia.org/wiki/List_of_countries_by_income_equality

Authors: Xiang Liu - Nerea Martinez - Elisenda Rahola - Natalia Benitez