Curious about uncovering deeper insights through data visualization?

I recently built a tiny Streamlit app designed to make it easy to compare multiple data source and analyzing trends and hidden patterns. I picked the stock market example given the rich data source as input. It’s not financial advice, but rather a fun and simple way to explore data visualization! The line graph approach used here isn't limited to stock data; it can be applied to a variety of fields. For instance, comparing year-over-year (YoY) sales trends, or tracking the effectiveness of different marketing campaigns. Line graphs are powerful for identifying both immediate patterns and long-term shifts.

The key goals for the app:

- Define custom time frames and data input frequencies

- Overlay multiple datasets to identify potential correlations or trends

- Visualize moving averages to compare short-term fluctuations with long-term patterns

Here’s a snapshot of what you can explore: How do different stocks respond to market events? What trends emerge over a week, a month, or even a year? Can layering the data reveal hidden correlations? And what insights can moving averages provide about short-term versus long-term movements?

How do you think data visualization can bring more insight and context to complex datasets? I'd love to hear your thoughts!