CSV & Excel Data Cleaner | Dedupe & Fix
Pricing
$1.00 / 1,000 cleaned records
Clean CSV, Excel & JSON in bulk: fix encoding, dates, numbers & currency, flag bad emails, remove duplicates (fuzzy too). Full change log. No AI.
Where the data comes from. Fill in the matching field below.
CSV or JSON text (max 5 MB). Used when Source type is 'Pasted text'.
Upload your .csv, .xlsx or .json file here (Console: pick 'Upload' to store it in a key-value store), or paste a public http(s) link. The file is read once; only the location you give is contacted.
ID of the dataset to clean (e.g. output of another Actor). Nested values are converted to JSON text.
Leave empty to use this run's default store. Used with 'Record key'.
Auto-detect from the content, or force a format.
Untick if the file has no header row; columns are then named column_1, column_2, ...
Auto tries UTF-8 first, then Windows-1252. Pick one explicitly if accents look wrong.
Field separator of the CSV input.
Remove leading/trailing spaces from every cell.
Turn runs of spaces/tabs inside a cell into one space ('Ana García' → 'Ana García').
Fix mojibake (e.g. 'Café' → 'Café'), smart quotes, invisible characters and non-breaking spaces.
Headers are always trimmed, de-duplicated and never empty. Choose a casing style, or keep the originals.
Treat empty cells and the null tokens below as one consistent empty value.
Cell texts treated as empty (exact match after trimming). Note '-' and '0' are never treated as null unless you add them.
[ "null", "NULL", "N/A", "n/a", "NA", "#N/A", "nan", "NaN", "none", "None"]Text written into empty cells of CSV/XLSX output (JSON and dataset keep null). Empty = leave blank.
List of {"column": "Name", "case": "title"} (case: lower, upper, title). Use "*" for all columns.
[]List of {"column": "*", "find": "St.", "replace": "Street", "mode": "literal|regex", "caseSensitive": true, "wholeCell": false}. Applied in order.
[]Columns to convert into true numbers: strips currency symbols/codes, % and thousands separators; (1,234) becomes -1234.
[]'Auto' treats '1,234' as 1234 and '1,5' as 1.5. Pick one when your data is consistently European or US.
'10%' becomes 10 (number) or 0.1 (fraction).
Columns to convert into one consistent date format.
[]How to read ambiguous dates like 03/04/2024. Ambiguous values are flagged in the output.
ISO keeps a time part when the input had one; 'ISO date only' removes it.
Columns checked for a valid email format (flags only; no emails are verified or sent).
[]Lowercase values in the email columns.
Columns checked for a plausible phone format (7–15 digits).
[]'E.164' only rewrites numbers that already start with + or 00; other numbers are left unchanged and flagged.
Rows with an empty value here are handled by the error policy.
[]What to do with a row that has an unparseable number/date, a missing required value or too many cells.
Adds an '_original' column with the original values of every cell that was changed in that row.
How duplicates are found.
Key mode only: compare keys case-insensitively and trimmed.
0.5–1.0. Higher = stricter. Keys are lowercased, accent-stripped and punctuation-free before comparing.
The row that stays in the clean output.
Keeps an audit trail of every removed row.
Files saved to the key-value store (CLEAN.csv / CLEAN.json / CLEAN.xlsx). Excel has Clean, Rejected and Summary tabs.
[ "csv"]Field separator used in CLEAN.csv and REJECTED.csv.
Helps older Excel versions open accents correctly.
Prefix text cells starting with = + - @ with an apostrophe (numbers untouched). Changes data, so off by default. XLSX output never stores text as formulas.
Shows validation flags per row when email/phone checks or the 'keep' policy are used.
CHANGE_LOG.csv: every changed cell with the rules that changed it.
Untick to log only row/column/rule (no before/after values) if the log is shared.
Counts stay exact; entries beyond the cap are not written.
Type, % null, unique count and top values per column (COLUMN_PROFILE.json).
Upload or link a JSON file with settings, e.g. {"headerCase":"snake_case","numericColumns":["Price"]}. Values in the file replace the same fields in this form. Source fields cannot be set in it. Same format as the local 'clean_local.py --settings' file.
Name of a profile saved earlier. Its cleaning settings (sections 2–5) replace the ones in this form.
Paste a profile document {"profileVersion":1,"settings":{...}} instead of loading by name. Do not set both.
Letters, digits, . _ - only (max 60). Saved after a successful run.
Process only a small sample, never charge, and mark the result as a preview.
Rows processed in dry run.
Rows processed per chunk. Keeps memory bounded.
Rows beyond this are not processed.
Larger inputs fail before processing.
Processing stops cleanly when exceeded.
Processing stops cleanly when exceeded.