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Documentation Index

Fetch the complete documentation index at: https://sourcetable.com/docs/llms.txt

Use this file to discover all available pages before exploring further.

Pivot tables let you summarize, group, and analyze large datasets by reorganizing your data into meaningful cross-tabulations.

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Creating a pivot table

1

Select your data

Click anywhere in your dataset. Sourcetable automatically detects the data range.
2

Insert a pivot table

Go to Insert > Pivot Table. Choose whether to place it on a new sheet or the current sheet.
3

Configure fields

Drag fields into the Rows, Columns, Values, and Filters areas in the pivot table editor.

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Pivot table areas

AreaPurposeExample
RowsCategories displayed as rowsProduct names, regions, dates
ColumnsCategories displayed as columnsMonths, status values
ValuesData to aggregateSum of revenue, count of orders
FiltersCriteria to filter the entire pivotYear = 2024, Region = “West”

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Aggregation functions

Values in pivot tables can be aggregated using:
  • Sum — total of all values
  • Count — number of entries
  • Average — mean value
  • Min / Max — smallest or largest value
  • Standard deviation — measure of variability

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Creating pivot tables with AI

You can also ask the AI assistant to create pivot tables:
  • “Create a pivot table showing total sales by region and product category”
  • “Summarize this data by month with average order value”
  • “Make a pivot table of employee count by department and location”
The AI uses the make_pivot tool to build the pivot table and can modify it with edit_pivot based on follow-up instructions.

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Pivot charts

After creating a pivot table, you can visualize it as a chart. Sourcetable uses Plotly for interactive pivot chart visualizations that update automatically when the pivot data changes.