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Data Cleaner

Not sure which cleaner to use? Drop a file or paste content, and this tool auto-detects CSV, TSV, Excel, JSON, JSONL, XML or YAML, applies safe cleanup, shows you a before/after preview and a change report, then exports it back in the same format - with links to the right dedicated workspace for anything more advanced.

Drop a data file here

or

CSV, TSV, XLSX, XLS, JSON, JSONL, XML, YAML

How to clean data with Data Cleaner

Use the file drop area for a saved dataset, or paste content into the Table data field when the source is already open. Data Cleaner detects the format, applies the selected cleanup options, and puts the result beside the original before export.

Clean data from a file or pasted text

  1. Drop a data file here, choose browse files, or paste content into the Table data field.
  2. Select Trim whitespace (cells / values / lines), Remove empty rows / blank lines, or Remove empty columns (tabular formats).
  3. Wait for automatic processing, then inspect Detected format, Change report, and Before / after preview.
  4. Click Export (same format), or choose a dedicated workspace when a routing card appears.

Empty input keeps the cleanup options hidden and shows a waiting status. Unknown pasted content reports that the format could not be detected. A file extension takes priority over content detection. A file treated as JSON reports a parse error when parsing fails; pasted text can fall through to another detection rule.

What cleanup changes by format

CSV and TSV cleanup trims surrounding whitespace from cells when Trim whitespace (cells / values / lines) is selected. Remove empty rows / blank lines drops rows whose cells are blank after trimming. Remove empty columns (tabular formats) drops a column when every cell in it is blank.

name,age
 Alice, 42 

Bob, 18

With Trim whitespace (cells / values / lines) and Remove empty rows / blank lines selected, the CSV output is:

name,age
Alice,42
Bob,18

JSON trims string values inside objects and arrays, then writes two-space indentation. JSONL removes blank lines and its byte-order mark, normalizes line endings, and trims parsed string values when the whitespace option is selected. Lines that fail JSON parsing stay unchanged and appear in the Change report.

XML and YAML receive text-level cleanup for byte-order marks, line endings, trailing spaces, and consecutive blank lines. Data Cleaner does not rewrite their structure or repair a malformed document.

What the preview and export leave unchanged

The Change report lists detected actions and some counts. CSV and TSV show table previews; JSON, JSONL, XML, and YAML show text previews. Excel shows a note before processing and only its first worksheet after processing. Display previews are truncated, while export uses the full input.

When a loaded text file exceeds 200,000 characters, the text box shows a truncated copy and processing still uses the full content. Excel cleanup runs across every worksheet, rebuilds cells from string values, and exports .xls or .xlsx as .xlsx. The rebuilt workbook does not carry over original formatting or formulas. Other normalized extensions are .ndjson to .jsonl, .yml to .yaml, and .txt to .csv.

What to check before export

  • Read Detected format to see the detected format, confidence, and whether detection came from the file extension or content.
  • Compare Before and After. The preview shows a limited portion of the input, and Excel's Before panel does not re-render the original workbook.
  • Read the Change report for cleanup actions and unparsed JSONL records, then use a routing card when the data needs a dedicated workspace.

When another clean tool fits better

Data Cleaner covers shared cleanup across several formats. For the wider Dataset Clean Tools category, use Email List Cleaner for email normalization, duplicate removal, and malformed-value review. Choose Phone Number List Cleaner for country rules, phone normalization, and flagged records.

Use Remove Duplicate Rows from CSV, Excel, JSON & Tables to match full rows or selected columns. Data Cleaner does not compare records for duplicates.

Frequently asked questions

How does Data Cleaner detect CSV, JSON, and other formats?

Uploaded files use their extension first. Pasted text is checked for a leading XML angle bracket, valid JSON, JSONL records, tab or comma separators, then YAML key-value or list patterns. Content that matches none of these rules is reported as unknown.

How do I clean a CSV or TSV file?

Drop a data file here or choose browse files, select the cleanup checkboxes, review the table preview, and click Export (same format). CSV and TSV output keeps its delimiter and applies the selected whitespace and blank-content cleanup.

Why did my Excel file export as XLSX?

Excel input exports as .xlsx because the page rebuilds each worksheet from string cell values. The Before preview does not re-render the original workbook, and the rebuilt output does not preserve its original formulas or formatting.

Does Data Cleaner validate JSON or repair XML?

Data Cleaner parses valid JSON and reports a parse error for JSON input that fails. It does not repair XML structure; use the XML Validator & Formatter routing card for structural validation and formatting.

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