Learn how to extract valuable insights from API-sourced stock data by identifying Apple's highest and lowest stock prices and their corresponding dates. Enhance skills in working with data frames for effective data analysis.
Key Insights
- The article demonstrates practical techniques for retrieving API-generated stock market data and emphasizes the flexibility of working with such data to derive meaningful insights.
- Readers are challenged to pinpoint Apple's highest stock price and the date it occurred by analyzing a structured data frame, highlighting analytical skills in data manipulation.
- As an additional learning exercise, the article suggests identifying the lowest stock price and its corresponding date, illustrating hands-on approaches to data frame utilization.
Note: These materials offer prospective students a preview of how our classes are structured. Students enrolled in this course will receive access to the full set of materials, including video lectures, project-based assignments, and instructor feedback.
Now, obviously, there's a lot more we could do with this data than what we’ll cover in this short video, because working with stock data is not the focus of this course. But as a demonstration of just the start of showing how we can work with this API data—we can do whatever we want with it.
It's our data now. Considering that, let's do a little challenge. We want to use this data frame we made to find the highest price and its date.
When did Apple hit its high, and what was that price? That's our challenge. As a bonus, you could also find the lowest price and the date it occurred in the data frame. We'll take a look at how we could do both of these in just a moment.
But take a moment—see if you can solve it on your own.