# CSV Transformer

Transform and process CSV data with column operations, calculations, and data type conversions. Supports renaming columns, adding calculated columns, removing columns, converting data types, calculating values, and filtering rows.

Operation examples:
• Rename column: [{"type": "rename", "column": "old_name", "new_name": "new_name"}]
• Add calculated column: [{"type": "add_column", "new_column": "total", "formula": "price * quantity"}]
• Remove column: [{"type": "remove_column", "remove_column": "column_to_remove"}]
• Convert data type: [{"type": "convert_type", "convert_column": "age", "target_type": "number"}]
• Calculate values: [{"type": "calculate", "target_column": "total", "expression": "price * tax + shipping"}]
• Filter rows: [{"type": "filter_values", "filter_column": "status", "operator": "equals", "value": "active"}]

> Canonical page: https://elysiatools.com/en/tools/csv-transformer

- **Category:** Data Processing

- **Keywords:** csv, transform, convert, calculate, columns, data processing, manipulate

## Overview

The CSV Transformer is a powerful utility designed to clean, restructure, and analyze your CSV data through precise column operations, mathematical calculations, and automated data type conversions.

## Inputs

- **CSV File** (file)
- **Transformations (JSON)** (textarea): Enter transformation operations in JSON format
- **Output Format** (select)
- **Include Header Row** (checkbox)
- **Error Handling** (select)
- **Error Reporting** (select)

## When to use

- When you need to clean or restructure large CSV datasets by removing unnecessary columns or renaming headers.
- When you must perform bulk calculations across rows, such as computing totals or applying tax rates to existing data.
- When you need to filter specific rows based on criteria or convert data types to ensure consistency for downstream analysis.

## How it works

- Upload your CSV file and define your desired operations using the JSON configuration field.
- Specify transformation rules such as renaming columns, adding calculated fields, or filtering rows based on specific values.
- Select your preferred output format and error handling strategy to ensure the processed data meets your requirements.
- Execute the transformation to generate your cleaned and structured data file.

## Use cases

- Standardizing inconsistent column names across multiple exported datasets for unified reporting.
- Automating the calculation of financial metrics like tax, shipping, or total price directly within the data file.
- Filtering large raw datasets to extract only relevant records, such as active users or completed transactions.

## Frequently asked questions

### What types of operations can I perform on my CSV?

You can rename columns, add new calculated columns, remove columns, convert data types, perform complex calculations, and filter rows based on specific conditions.

### How do I define the transformation rules?

Transformation rules are defined using a JSON array format in the 'Transformations' field, where each object specifies the operation type and relevant parameters.

### Can I output the result in a format other than CSV?

Yes, the tool supports exporting your processed data as CSV, JSON, or a summary report.

### How does the tool handle errors during processing?

You can configure error handling to either skip the problematic row, keep the original value, set it to empty, or throw an error to stop the process.

### Is there a limit to the number of transformations I can apply?

You can chain multiple operations within the JSON array to perform complex data manipulation in a single pass.

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## Samples

- [CSV Samples](https://elysiatools.com/en/samples/csv-samples): Sample CSV files with various data types, sizes, and complexity levels
- [Python Samples](https://elysiatools.com/en/samples/python): Essential Python code examples and Hello World demonstrations
- [WebRTC Real-Time Communication Samples](https://elysiatools.com/en/samples/webrtc-samples): Comprehensive WebRTC samples for peer-to-peer audio/video communication, data channels, screen sharing, and signaling server implementation
- [Apache Arrow Samples](https://elysiatools.com/en/samples/arrow): Apache Arrow in-memory columnar format examples for high-performance data processing and analytics

## Related content

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