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Loading, please wait…Detect and remove duplicate rows, prune empty records, strip whitespace, and normalize casing with instant before/after audit.
Drop your dataset to inspect issues and clean in memory.
The CSV cleaner removes exact-duplicate rows, drops fully empty rows, trims leading and trailing whitespace from every cell, and optionally normalizes text casing. Before you apply anything, Datio shows diagnostic counts so you can see how many duplicates, blank rows, and trimmable cells were found.
Useful for analysts, operators, and students preparing spreadsheet exports, mailing lists, or research extracts where extra spaces, blank lines, and repeated rows break sorting, filtering, and charts.
name,email
" Alice ",alice@example.com
"Bob",bob@example.com
"Bob",bob@example.com
→
name,email
"Alice",alice@example.com
"Bob",bob@example.comCleaning works best at the start of the pipeline. Inspect the file first, clean it, then audit the result before charting. CSV Viewer, Data Profiler, Visualizer.
A CSV cleaner fixes the most common spreadsheet mess — duplicate rows, blank lines, stray leading/trailing spaces, and inconsistent capitalization — so the file sorts, filters, and charts correctly. Datio's CSV Cleaner does this entirely in your browser and shows diagnostic counts before you apply anything.
Load the file in Datio's CSV Cleaner, check the duplicate-row count, enable Remove Duplicates, and choose Apply Rules. Deduplication is an exact match on the whole row, so trim whitespace first to also catch near-duplicates that differ only by spacing — then export the cleaned CSV. Guide: Removing duplicates →
No. Case normalization only touches text cells; numeric values are never case-transformed. Trimming removes padding spaces, which can change how a value is typed when you re-profile the file — that is exactly why you clean before profiling.
Clean first when you can already see the mess (extra spaces, repeats, blank lines); profile first when you want an audit of types, missing values, and duplicates. A reliable loop is CSV Viewer → CSV Cleaner → Data Profiler, then re-profile to confirm the duplicate count is zero. Data Profiler →
Deduplication is exact-match on the whole row — near-duplicates with different spacing must be whitespace-trimmed first. Numbers are never case-transformed, and there is no automatic filling of missing values.