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CSV Data Grouper

Group CSV data by specified columns with aggregation options. Perfect for summarizing and analyzing large datasets by categories, dates, or other criteria.

Columns to group data by. Multiple columns will create nested groups.

JSON format: [{"column": "Amount", "function": "sum", "as": "Total_Amount"}] Simple format: Amount:sum,Name:count Default: Count records per group Available functions: count, sum, avg/average, min, max, first, last, join, unique, count_unique

Remove whitespace from beginning and end of cell values

Key Facts

Category
Data Processing
Input Types
textarea, select, text, checkbox
Output Type
text
Sample Coverage
4
API Ready
Yes

Overview

CSV Data Grouper is a powerful utility designed to organize and summarize large datasets by grouping rows based on specific columns and applying mathematical aggregations. It simplifies data analysis by allowing you to quickly calculate totals, averages, or counts across categories, dates, or custom identifiers.

When to Use

  • •When you need to condense large CSV files into meaningful summary reports.
  • •When you want to calculate statistics like sums or averages for specific categories within your data.
  • •When you need to transform raw, granular data into a structured format for easier analysis or reporting.

How It Works

  • •Paste your CSV content into the input area and select the correct delimiter.
  • •Specify the column names you want to group by to organize your data structure.
  • •Define your aggregation rules, such as summing a 'Sales' column or counting occurrences of a 'Product' ID.
  • •Choose your preferred output format (CSV or JSON) and click process to generate your summarized data.

Use Cases

Summarizing monthly sales figures by region and product category.
Calculating the average response time for support tickets grouped by agent.
Counting unique customer interactions per day from raw log files.

Examples

1. Monthly Sales Summary

Sales Analyst
Background
A sales analyst has a raw CSV file containing thousands of individual transactions with columns for 'Date', 'Region', and 'Amount'.
Problem
The analyst needs to know the total revenue generated per region for each month.
How to Use
Set 'Group By Columns' to 'Month,Region' and 'Aggregation Options' to 'Amount:sum'.
Example Config
[{"column": "Amount", "function": "sum", "as": "Total_Revenue"}]
Outcome
A clean, summarized table showing the total revenue for every region, broken down by month.

2. Inventory Count

Warehouse Manager
Background
A warehouse manager has a list of items in stock with their respective 'Category' and 'Status'.
Problem
The manager needs a quick count of how many items are in each category to update the inventory dashboard.
How to Use
Set 'Group By Columns' to 'Category' and use the default aggregation to count records.
Outcome
A concise list showing each category and the total number of items associated with it.

Try with Samples

json, csv, video
CSV Samples
Sample CSV files with various data types, sizes, and complexity levels
title token csv
csv, json
Python Samples
Essential Python code examples and Hello World demonstrations
preferred input family csv,json
csv, json
WebRTC Real-Time Communication Samples
Comprehensive WebRTC samples for peer-to-peer audio/video communication, data channels, screen sharing, and signaling server implementation
preferred input family json
json
Regex Replace Samples
Collection of common and useful regex replacement patterns for text transformation and data cleaning
preferred input family csv
csv

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FAQ

What aggregation functions are supported?

You can use count, sum, avg/average, min, max, first, last, join, unique, and count_unique.

Can I group by multiple columns?

Yes, you can enter multiple column names separated by commas to create nested groups.

Does the tool handle whitespace in my CSV?

Yes, the 'Trim Cell Values' option automatically removes leading and trailing whitespace from your data.

What output formats are available?

The tool supports exporting your summarized data in either CSV or JSON format.

Do I need to include a header row?

It is recommended to include a header row for accurate column identification, which you can toggle using the 'Include Header Row' checkbox.

API Documentation

Request Endpoint

POST /en/api/tools/csv-data-grouper

Request Parameters

Parameter Name Type Required Description
csvInput textarea Yes -
delimiter select Yes -
groupByColumns text Yes Columns to group data by. Multiple columns will create nested groups.
aggregationOptions textarea No JSON format: [{"column": "Amount", "function": "sum", "as": "Total_Amount"}] Simple format: Amount:sum,Name:count Default: Count records per group Available functions: count, sum, avg/average, min, max, first, last, join, unique, count_unique
outputFormat select Yes -
includeHeader checkbox No -
sortGroups checkbox No -
trimValues checkbox No Remove whitespace from beginning and end of cell values

Response Format

{
  "result": "Processed text content",
  "error": "Error message (optional)",
  "message": "Notification message (optional)",
  "metadata": {
    "key": "value"
  }
}
Text: Text

AI MCP Documentation

Add this tool to your MCP server configuration: 

{
  "mcpServers": {
    "elysiatools-csv-data-grouper": {
      "name": "csv-data-grouper",
      "description": "Group CSV data by specified columns with aggregation options. Perfect for summarizing and analyzing large datasets by categories, dates, or other criteria.",
      "baseUrl": "https://elysiatools.com/mcp/sse?toolId=csv-data-grouper",
      "command": "",
      "args": [],
      "env": {},
      "isActive": true,
      "type": "sse"
    }
  }
}

You can chain multiple tools, e.g.: `https://elysiatools.com/mcp/sse?toolId=png-to-webp,jpg-to-webp,gif-to-webp`, max 20 tools.

If you encounter any issues, please contact us at [email protected]