DataFrog

DataFrog lets you work with datasets directly in your browser for inspection, analysis, validation, comparison, cleaning, and visualization. Your files are read into browser memory, with complete privacy: processing happens locally with zero server uploads, no backend, and no account required.

Use interactive tools to explore complex nested data structures (including tree viewers, depth metrics, and JSON path tools) and to inspect spreadsheet content across multiple tabs. You can also run statistical analysis and profiling, including mean/median/min/max/sum, missing value ratios, and data type distributions.

DataFrog supports validation for JSON, XML, CSV, and YAML with precise line and column error pointers, plus JSON Schema verification (Draft-04, Draft-07, 2020-12). For changes and differences, it enables side-by-side and inline structural diffing across formats (including added/deleted row detection and cell modification highlights), along with reporting exports and local dataset cleaning and transformation.

For visual exploration, DataFrog converts supported dataset types into interactive node trees, searchable spreadsheet tables, and chart graphics such as Bar, Line, Pie, and Doughnut—while keeping all work offline-capable once loaded in your browser.

Is DataFrog fully private for my datasets?

Yes—dataset processing runs 100% locally in your browser. Files aren’t uploaded to a server or logged anywhere.

Do I need an account to use DataFrog?

No account is required. You can open and use the tools directly in your browser.

Does DataFrog support offline use?

Once a tool page is loaded in your browser, client-side functionality continues to work offline.

What data formats can I inspect and analyze?

DataFrog supports inspecting and analyzing structured data including JSON, XML, CSV, YAML, and Excel.

Can DataFrog validate data and report syntax errors precisely?

Yes. It validates JSON, XML, CSV, and YAML syntax and provides exact line and column error pointers for easier debugging.

Can I compare two datasets to see structural changes?

Yes. It provides side-by-side and inline structural diffing with key path tracing, added/deleted row detection, and cell value modification highlights, with report exports.