CSV to JSON Converter.

Paste your CSV data or upload a .csv file into the input area above, then click Convert. The tool parses the CSV header row as JSON keys and each data row as a JSON object, producing a clean JSON array. All processing is client-side — your data stays on your device.

Drag and drop your .csv file onto the input area, or click to browse. The converter reads the first row as field names and maps each subsequent row to a JSON object. Click Copy to copy the JSON output or Download to save as a .json file.

For quick online conversions, jsontofile.com offers instant client-side CSV-to-JSON conversion with no limits and no signup. For programmatic use, papaparse (JavaScript/Node.js), csv module + json module (Python), or pandas.read_csv().to_json() (Python) are recommended. For large enterprise datasets, ETL tools like Talend or Apache NiFi provide robust pipelines.

Open your CSV in Excel, then use Power Query (Data → From Text/CSV) to load it. Once loaded, go to File → Export → Change File Type and select a JSON-compatible format (Excel doesn't export directly to JSON). For a direct conversion, paste your CSV into the converter above and download the JSON instantly.

See the JSON to CSV converter on this site. The same tool handles both directions — paste JSON for CSV output, or paste CSV for JSON output. The conversion happens in your browser with no data sent to any server.

Use a CSV parsing library like OpenCSV or Apache Commons CSV to read the CSV, then convert the rows to JSON with Jackson or Gson:
CSVReader reader = new CSVReader(new FileReader("data.csv"));
String[] headers = reader.readNext();
List<Map<String,String>> rows = new ArrayList<>();
String[] line;
while ((line = reader.readNext()) != null) {
  Map<String,String> row = new HashMap<>();
  for (int i=0; i < headers.length; i++) row.put(headers[i], line[i]);
  rows.add(row);
}
String json = new ObjectMapper().writeValueAsString(rows);

Use the converter on this page. Paste your JSON array of objects, click Convert, and the tool flattens nested structures into CSV columns with dot-notation headers (e.g., user.name). You can also upload a .json file by dragging it onto the input area.

Several tools are available: jsontofile.com (free, client-side, no limits), conversiontools.io (online, server-processed), pandas (Python: df.to_csv()), papaparse (JavaScript), jq (command-line: jq -r '.[] | [.name,.age] | @csv'), and Excel Power Query (built into Microsoft Excel). Our tool stands out for being completely private — no data ever leaves your browser.