JA Technology Solutions
JSON ↔ CSV
Convert between JSON and CSV formats. Paste, upload, or load sample data. Download or copy the result.
JSON ↔ CSV
Convert between JSON arrays and CSV bidirectionally — swap direction with one click and see the output update instantly. Nested JSON objects flatten to dot-notation columns (e.g., address.city); arrays serialize as inline JSON when they can't be represented flat. CSV-to-JSON auto-detects numeric and boolean values so they're typed correctly in the output — no manual casting needed. Drop a .json or .csv file, paste content, or load sample data; copy the output to clipboard or download it as a file. Runs entirely in your browser — your data never leaves your machine.
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JSON and CSV — Two Data Models, One Workflow
JSON is the native format of modern web APIs, application configs, and document databases. CSV is the native format of spreadsheets, BI tools, data warehouses, and nearly every enterprise reporting pipeline. Moving between them is one of the most common data-wrangling tasks in existence — and it is deceptively tricky at the edges. JSON is tree-shaped with nested objects and arrays; CSV is flat with a fixed column set. Flattening nested JSON into CSV requires choosing a path: unwrap arrays into repeated rows, join nested fields with dot notation, or explode-and-pivot. Going the other way, CSV rows need to be typed (numeric? date? boolean?) because everything in CSV is a string until you decide otherwise.
What This Converter Handles
This tool handles the everyday cases cleanly: an array of flat JSON objects becomes a CSV with columns drawn from the union of all keys; a CSV with a header row becomes a JSON array with auto-detected numeric and boolean types; fields containing commas or quotes are properly escaped with RFC 4180 double-quoting; and nested JSON values that cannot be represented as a single cell are serialized as inline JSON strings rather than lost. Paste content, drop in a file, or load a sample to see the round-trip behavior before you commit to a format.
When a Converter Becomes a Pipeline
One-off conversions are fine in the browser. For delimiter-specific issues before your data reaches this tool, the Delimiter Converter handles format normalization. Once converted, the Data Profiler reveals column quality and type distribution, and Data Diff & Compare lets you compare two versions side by side. Recurring conversions — nightly exports from a REST API into a data warehouse, or daily vendor feeds transformed before ERP ingest — need real ETL. I build custom data pipelines that handle schema drift, type coercion, error quarantining, and delivery to downstream systems on a schedule, so the conversion that starts as a one-off never has to be done by hand twice. Learn about ETL and data pipeline development, explore integration services, or get in touch to discuss automating your JSON/CSV workflows.
All tools run entirely in your browser. Your data never leaves your machine. Need help? Ask James.