Data Exploration
Preview and explore CSV datasets with sorting, search, and column filtering. Handle large files with thousands of rows.
Paste or upload CSV data on the left to preview as a sortable table
Online Data Tools CSV Tools is a free, browser-based CSV viewer, formatter, and converter that lets you view, clean, and transform CSV data into JSON, XML, SQL, YAML, and Excel. Whether you're cleaning up datasets, preparing database imports, or converting between formats, our tools make it effortless.
View CSV data in a sortable, filterable table with search, pagination, and column-level filtering. Handles large files with thousands of rows.
Clean and normalize messy CSV data. Proper quoting, consistent delimiters, and standardized formatting for production-ready output.
Convert CSV to JSON arrays with automatic type detection. Supports pretty-print and minified output for API payloads.
Transform CSV data into well-formed XML with customizable root and row element names. Proper escaping and sanitized tag names.
Generate CREATE TABLE and INSERT statements from CSV data. Auto-detects column types. Supports MySQL and PostgreSQL dialects.
Convert CSV to clean YAML for configuration files, DevOps pipelines, and Kubernetes manifests. Human-readable output with proper indentation.
Export CSV data to Excel (.xlsx) format with proper column headers and data types. Download instantly for spreadsheet workflows.
Preview and explore CSV datasets with sorting, search, and column filtering. Handle large files with thousands of rows.
Convert CSV exports to JSON for REST API payloads, or generate YAML for DevOps configuration and Kubernetes manifests.
Generate SQL INSERT and CREATE TABLE statements from CSV data with auto-detected column types for MySQL and PostgreSQL.
Clean messy CSV files from multiple sources, normalize formatting, and export to Excel for stakeholder reporting.
Yes! Online Data Tools CSV Tools are completely free with no sign-up, no ads, and no usage limits.
Absolutely. All processing happens in your browser using PapaParse and SheetJS. No data is ever sent to our servers.
The tools handle files with tens of thousands of rows. The viewer uses pagination to render large datasets efficiently.
Yes. It automatically detects integer, decimal, and text types by scanning your data and generates appropriate column definitions.
Yes. The parser auto-detects delimiters including commas, tabs, semicolons, and pipes, so TSV files work automatically.