Public sample Data files
NFL Player Data: Remember Ike Peterson from '35? Neither do we!
The data was scraped using a Python code. The code can be located at Github: https://github.com/kendallgillies/NFL-Statistics-Scrape, the data then became available here. With this dataset, we can look at the characteristics of existing (and past) NFL players to have a better understanding of the sport. With this information, we can also predict the positioning or quality of new players. Lastly, this information could be used for fantasy football, by having a better understanding of how players rank in comparison to other players in the same position.
Turn Price Transparency Data into Actionable Market Intelligence
Healthcare organizations are using machine-readable price transparency data to uncover real market dynamics. Gigasheet's breakthrough analytic platform helps you translate that data into clear, decision-ready insights.
Analyze negotiated rates across payers and providers, identify pricing variation, benchmark against the market, and surface opportunities to improve contracts and reduce costs. This sample dataset is a preview of what’s possible.
Gigasheet scales from high-level aggregates down to row-level detail across billions of records, in a single click. Our analytics are enabling deeper analysis that leads to better decisions, stronger negotiations, and measurable financial impact.
Book A Demo
More Sample Data Files
Engagement Insights: Analyzing the Top 1000 Posts from the Writing Prompts Subreddit
War on the Water: A Comprehensive Review of WWII U-boats and Their Naval Engagements
100,000+ people use Gigasheet.
