Welcome to the hands-on lab where I analyzed historical stock and revenue data and build a dashboard to visualize our findings. This README file will guide you through the steps and contents of this lab.

Requirements To complete this lab, you will need: Python 3.x Jupyter Notebook Libraries: yfinance, requests, beautifulsoup4, pandas, matplotlib, plotly Project Structure . ├── data │ └── raw # Raw data files ├── notebooks │ ├── 01_extract_stock_data.ipynb # Notebook for extracting stock data │ ├── 02_scrape_revenue_data.ipynb # Notebook for scraping revenue data │ ├── 03_data_cleaning.ipynb # Notebook for data cleaning │ ├── 04_data_visualization.ipynb # Notebook for data visualization │ └── 05_build_dashboard.ipynb # Notebook for building the dashboard ├── README.md └── requirements.txt

Data Sources Stock Data: Extracted using the yfinance library. Revenue Data: Scraped from webpages using the requests and BeautifulSoup libraries.