For this personal project, I developed a webscraper that meaningfully synthesizes data from various websites & generates statistical & visual output, tailored to my investment strategy. The output statistics provide a high-level overview of
the input companies and their performance over the past few years. The scraped & computed data is then visually represented to the end user, highlighting trends in efficiency & growth factors. The output is ripe for growth comparison & analysis.
Development/Tooling:
- Python Virtual Environments
- Web Scraping
- Data Cleaning, Transformation & Formatting
- Data Visualization
Domain Knowledge/Research:
- For investment consideration, what numbers are important, when evaluating a company/stock?
- What statistics do I personally find significant? Are they commonly available when viewing stocks online?
- How do I maximize significant, derived insights from each dataset?
It was an excellent experience. I am happy to report that I have learned a lot from it.
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