/SnP500-Analysis

Designed a multi-dimensional data model using LucidChart. Developed ELT pipeline using Python/Pandas. S&P 500 data obtained via yfinance, an open-source library. Output normalized data to excel. Performed analysis and generated reports with Power BI.

Primary LanguagePython

S&P 500 Analysis

Table of Contents
  1. About The Project
  2. Roadmap
  3. Reports
  4. Contact
  5. Disclaimer

About The Project

Current Relational Model
'Market' table references other tables via foreign keys

Built With

Python
Pandas
Microsoft Excel
Power Bi

Roadmap

  • Initialize DB
  • Update DB
  • Create automation script
  • Generate BI reports
    • FAANG + MAMAA
      • AAPL spread
      • AMZN spread
      • GOOGL spread
      • GOOG spread
      • MSFT spread
      • META spread

Reports

Historical Pricing Data for 2023
Displays open/close and high/low pricing data for top tech companies
Data can be found HERE
AAPL Pricing Spread for 2023
Displays open/close and high/low pricing data for Apple Inc
Calculated spread can be found HERE

Contact

LinkedIn
GitHub

Disclaimer

Current data source limited to yfinance API. Will look to incorporate more APIs as development advances.