• Upload large sized data to the local database, or connect to existing databases (mysql or postgres) to work with large data.
  • A subset of sample data will be pulled to the frontend to explore, you can roll the dice 🎲 or sort the data by different columns to view different samples.
  • Manage local database with the Database manager.
• Interaction with Data Formulator as usual:
  • Use drag and drop to specify a chart, and Data Formulator can dynamically generate SQL query to fetch data to instantiate data. This process is quite fast!
  • Specify new visualization fields / provide NL instructions as usual, and the newly introduced NL2SQL agents can generate SQL queries based on your instruction to prepare the data, and create visualizations.
  • Anchor a dataset, followup, join some tables, can you can dive deep pretty fast into insights!
• (Minor feature updates)
  • Updated how derived concept works in Data Formulator -- data transformation is executed in the backend and updated data is appended to the new dataset. New concepts can be applied directly to new dataset in one click.
  • Improved system performance with configurable sandboxing options (main process versus subprocess) for LLM generated code (~3s interaction time reduction).
  • Configurable default visualization size in the main panel.

More explorations on the demo dataset:

• What's your favorite games and how their review change over time?
• What's the franchise that consistently improved reviews?
• What are games that have most different reviews in different platforms?
• What are games with many positive critic reviews but no user bother to play?
• What about reviews trends for the No Man's sky?

Well, it is time to upgrade Data Formulator and play with it! Let us know what you come up with :)