JSON Data Cleaner
Tidy up JSON from APIs, exports or forms in one step. The cleaner trims spaces in every string, removes invisible characters such as zero-width spaces, drops null, empty and placeholder values (N/A, NULL, “-”), removes empty objects and arrays, and can convert strings like "42", "true" and "null" into real numbers, booleans and null. Optionally it removes duplicate array items and sorts object keys, then outputs indented or minified JSON with a report of every change.
- Runs in your browser
- No sign-up
- Free to use
Processed entirely in your browser – your data is not uploaded. Files up to 50 MB.
How to use JSON Data Cleaner
- Paste JSON or open a .json file.
- Choose the cleaning rules.
- Click Clean JSON.
- Copy or download the cleaned JSON.
JSON Data Cleaner features
Deep cleaning
Works through nested objects and arrays.
Type conversion
Numbers, booleans and null from strings.
Safe numbers
Leading zeros (postcodes) stay strings.
Change report
Counts of every change.
Indent or minify
2, 4 spaces or one line.
Private
Runs in your browser; nothing is uploaded.
When to use JSON Data Cleaner
- Cleaning API responses.
- Preparing JSON for imports.
- Removing empty fields before storage.
- Normalising form submissions.
JSON Data Cleaner FAQ
Is the order of keys kept?
Yes, unless you choose to sort keys.
Will “007” become 7?
No – values with leading zeros are kept as strings.
Does it validate JSON?
Invalid JSON is reported with the parser’s message; use the JSON validator for details.
Clean data, fewer bugs
Empty strings, “N/A” placeholders and numbers stored as text cause bugs in code and wrong totals in reports. Cleaning once at the boundary keeps downstream systems simple.
Private by design: your data is read and processed entirely in your browser with JavaScript. Nothing is uploaded to our server, so you can work with customer lists, exports and internal reports safely. Files up to 50 MB are supported; very large files depend on your device’s memory.
Input formats: paste or open CSV (comma, semicolon, tab or pipe – detected automatically), TSV or JSON (an array of objects, an object with a data, items or results array, or JSON Lines). The first CSV row is used as the header; JSON keys become columns, and nested values are kept as JSON text.
Missing values are recognised consistently across the data tools: empty cells and common placeholders such as NULL, N/A, NA, NaN, none, “-” and undefined. Types are inferred from the values – integer, decimal, boolean, date, email, URL, JSON or text – and columns with mixed types are flagged.
Related tools on this site cover the rest of a data workflow: the CSV cleaner, viewer, splitter and merger, converters between CSV, JSON, Excel and SQL, the JSON formatter and validator, and the other profiling, validation and statistics tools in this group.
Who it is for: analysts preparing data for a report, developers checking an API export or a database dump, marketers cleaning contact lists before an import, and students learning data quality. No account, no installation and no spreadsheet formulas are needed.