Create pivot tables with 11 aggregation types including sum, count, avg, median, stddev, first, last, and concatenate
Pivot tables turn flat CSV data into meaningful summaries by grouping rows and aggregating values. Pick your row and column grouping fields, choose an aggregation (sum, count, average, min, max), and the tool builds an interactive pivot table you can explore, rearrange, and export.
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You have raw sales rows and need revenue summarised by region and quarter for a one-slide summary.
Input
rows: sale records · pivot: region × quarter, sum(total)
Pivot
region Q1 Q2 Q3 EU 120.4k 98.1k 134.0k US 210.3k 188.7k 205.5k
The tool groups by your row/column fields and aggregates (sum, count, average) entirely in the browser, producing the cross-tab without a spreadsheet pivot or SQL GROUP BY. The result is itself exportable as CSV for the next step.
Pivot tables turn flat CSV data into meaningful summaries by grouping rows and aggregating values. Pick your row and column grouping fields, choose an aggregation (sum, count, average, min, max), and the tool builds an interactive pivot table you can explore, rearrange, and export.
Summarize revenue by region and product category to see where sales concentrate.
Cross-tabulate survey responses by demographic groups to reveal trends.
Aggregate stock quantities by warehouse and product type for inventory planning.
Group transaction data by month or quarter to spot seasonal patterns.
Quickly rearrange dimensions to answer one-off questions about a dataset.
Set "Region" as rows, "Quarter" as columns, and "Revenue" as the value with SUM aggregation to produce a regional revenue breakdown.
Set "Department" as rows, "Office" as columns, and use COUNT to see staffing distribution.
Pivot tables are the workhorse of data summarization. This tool brings the same concept to raw CSV files without requiring Excel. Drag fields into row, column, and value positions. The value field supports multiple aggregation functions, sum, count, average, min, max, and count distinct, and you can apply more than one at a time to compare metrics side by side.
Filtering is built in: narrow the pivot to a date range, a set of categories, or any condition before aggregation runs. The output table is sortable and exportable as a new CSV, ready for charting or reporting.
Yes. You can aggregate several numeric columns simultaneously, for example, showing both total revenue and average order size in the same pivot.
The tool works efficiently with datasets of up to several hundred thousand rows. Extremely large files may slow down in-browser processing.
Yes. Apply filters on any column to narrow the dataset, then build the pivot on the filtered subset.
Rows and columns are parsed and transformed in memory in your browser. No record ever reaches a server.