Analyzing Stock Prices

In this course, we explored different algorithms and data structures and what scenarios are appropriate to use them. In this guided project, we’ll practice our knowledge of algorithms and data structures to work with stock market data that was downloaded from Yahoo Finance using the yahoo_finance Python package.

Throughout this guided project, we’ll practice working with different memory constraints. Working on guided projects will give you hands-on experience with real-world examples, so we encourage you to not only complete them, but to take the time to really understand the concepts.

These projects are meant to be challenging to better prepare you for the real world, so don’t be discouraged if you have to refer back to previous lessons. If you haven’t worked with Jupyter Notebook before or need a refresher, we recommend completing our Jupyter Notebook Guided Project before continuing.

As with all guided projects, we encourage you to experiment and extend your project, taking it in unique directions to make it a more compelling addition to your portfolio!


  • Use hash tables to compute aggregates
  • Implement search algorithms.

Lesson Outline

  1. Stock Price Data
  2. Computing Aggregates
  3. Finding The Most Traded Stock Each Day
  4. Searching For High Volume Days
  5. Finding Profitable Stocks
  6. Next Steps

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