Excited to share a recent data science project where I scraped stock data for companies like Microsoft, Apple, and Tesla and visualized their stock highs over the past 5 years.

I used #Python to scrape company names from Yahoo Finance, download historical stock data using the #yfinance library, and concatenate the dataframes into one.

Then, I used Plotly to create an interactive line plot that allows for date selection and hover text with additional information. I also added annotations to highlight significant events like all-time highs and lows, as well as a shape to highlight a period of interest for my reseach.

Apart from scrapping and visualization, the project involved wrangling and the creation of functions for automation, which made the data analysis much more efficient. You can find the code in my GitHub account, where I shared a Jupyter notebook with the entire project.

Next steps: playing around with PyGWalker —an open-source Python library that allows turning pandas DataFrames into a Tableau-style user interface for visual analysis.