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Spreadsheet

Overview​

This AI-powered spreadsheet enables data preparation using natural language. Different from getting an answer from asking a question, you can continuously refine the dataset using natural language.

Spreadsheet

Additionally, you can save it for future quick access. For example, you could refine a customer profile dataset with all the joined properties, such as total order count and other relevant metrics.

Saving the spreadsheet will create a view, allowing Wren AI to use the view if a question matches your spreadsheet.

Getting Started​

spreadsheet-start

You can begin with models/views or start with SQL. After importing data, you will see a spreadsheet populated with data.

Save Your Work

At this point, the modifications are not yet saved, and no spreadsheet has been created. You need to save it to access it continuously.

Metadata of Spreadsheet​

spreadsheet-metadata

  • Creator: The user who created the spreadsheet.
  • Last Updated Time: The last time the spreadsheet was updated.
  • Matched Question: The corresponding question used to generate a view, which might be matched during question asking.

AI Assistant Features​

AI Assistant Features

The AI Assistant offers several features to enhance your spreadsheet experience:

Filter​

spreadsheet-filter

Apply filters to focus on specific data subsets.

For example: given a sales dataset, you could:

  • Show me orders where the region is North America.
  • Show me transactions where the date is in the last quarter.
  • Show me sales where the product category is electronics.

Cleaning​

spreadsheet-cleaning

Clean your data by removing duplicates, handling missing values, etc.

For example: given a sales dataset, you could:

  • Remove duplicate orders.
  • Fill in missing values for the product category.
  • Remove orders where the customer name is null.

Grouping​

spreadsheet-grouping Group data based on specific columns to aggregate information.

For example: given a sales dataset, you could:

  • Group by region to see sales by region.
  • Group by date to see sales by day.
  • Group by product category to see sales by product category.

Enrichment​

spreadsheet-enrichment Enrich your data by adding new columns or external data sources.

For example: given a sales dataset, you could:

  • Add a new column for customer age by calculating age from the date of birth.
  • Extract company name from email address
  • Add a new column for customer segment by analyzing purchase frequency and total spending to categorize customers into segments such as "High Value," "Frequent Buyer," or "Occasional Shopper."

Managing Changes​

spreadsheet-changes

  • You can undo and redo changes to revert or reapply recent unsaved modifications.
  • If you do not wish to keep the current modifications, you can discard the changes using the Discard Changes button.

Saving will store the current unsaved modifications as a version. The history feature allows you to rollback to previous versions.

History​

spreadsheet-history

The history panel provides a detailed view of all changes made to the spreadsheet.

In the Unsaved Changes section, you can review all modifications that have not yet been saved. If you wish to undo certain actions, you can rollback to a previous version.

spreadsheet-unsaved-changes

Additionally, you can view all the saved versions of the spreadsheet in the Saved Versions section.

spreadsheet-saved-versions

You can restore to a previous savedversion if needed.