CSV Pivot Table

What this tool does

CSV Pivot Table groups every row by a chosen column’s value and aggregates another numeric column within each group (sum, average, count, minimum or maximum), the single-group-and-value-field equivalent of a spreadsheet pivot table, with a CSV download of the result.

Summarising a CSV by category, total sales per region, average score per group, count of orders per status, normally means opening it in a spreadsheet and building a pivot table, a few steps more than a quick summary needs.

This tool does that grouping and aggregation directly from pasted CSV data: pick a column to group by, a column to aggregate, and an aggregation function (sum, average, count, min or max), producing the summary instantly with a CSV download.

How to use CSV Pivot Table

1. Paste your CSV data.
2. Choose the column to group rows by.
3. Choose the column to aggregate, and which aggregation to apply.
4. Review the resulting grouped summary, and download it as CSV.

Tips for better results

• Count ignores the actual values in the aggregate column entirely, it just counts how many rows fall into each group, useful for "how many orders per status" type questions.
• If a group’s aggregated value looks like zero unexpectedly, check that the aggregate column genuinely contains numbers for every row in that group, non-numeric cells are treated as zero.
• This handles a single group-by column and a single value column, like a basic one-dimensional pivot; for grouping by two dimensions simultaneously (rows and columns), a full spreadsheet pivot table offers more structure.
• The "rows" count column in the output shows how many original rows contributed to each group’s aggregated figure, useful context alongside the aggregated value itself.

Common use cases

• Summarising total or average sales by region, product, or category from a CSV export.
• Counting how many records fall into each category or status.
• Finding the minimum or maximum value within each group of a dataset.
• Quickly summarising a CSV without opening spreadsheet software.

Common mistakes to avoid

• Choosing a non-numeric column as the aggregate column for sum/average/min/max, which produces a result based on treating non-numeric cells as zero, not a meaningful calculation; count is the appropriate aggregation for a non-numeric column.
• Expecting two-dimensional pivoting (grouping by two different columns simultaneously); this tool groups by one column and aggregates one value field, a single-dimension pivot, not a full cross-tabulation.
• Not checking the "rows" count alongside the aggregated value, a group with very few rows contributing to an average, for instance, may be less statistically meaningful than one with many.