COVID-19 Data Crawler 🦠

Final project for the Huawei ICT Academy Python course.

A minimalist Python web scraper that extracts real-time COVID-19 statistics from Worldometer, processes the data, and visualizes the impact across top countries.

Features

• Web Scraping: Fetches live global COVID-19 data using requests and BeautifulSoup.
• Data Wrangling: Cleans and structures the raw HTML table into a robust pandas DataFrame.
• Data Export: Automatically exports the processed dataset to a local covid19.csv file.
• Data Visualization: Generates a bar chart of the top 10 countries by total cases using matplotlib.

Prerequisites

Ensure you have Python 3 installed. You will need the following libraries:

• requests
• beautifulsoup4
• numpy
• pandas
• matplotlib

Installation & Usage

1. Clone the repository or download the Jupyter Notebook file.
2. Install dependencies (it is recommended to use a virtual environment):

   pip install -r requirements.txt

3. Run the Notebook: The requirements.txt file already includes Jupyter Lab. You can launch the environment directly from your terminal by running:

   jupyter lab

   Once the interface opens in your browser, select the notebook file and execute the cells sequentially to scrape the site, generate the covid19.csv file, and render the bar chart.