About Data Cleaner
Clean and normalize datasets in seconds. Trim cell whitespace, remove blank rows and columns, normalize text casing (camelCase, snake_case, CONSTANT_CASE, Title Case), search and replace with Regex, and replace missing values.
Key Capabilities & Features
- Trim leading, trailing, and redundant whitespace across all columns
- Automated removal of empty rows and blank columns with priority ordering
- Strip invisible non-printable ASCII control characters
- Extended casing transformations: lowercase, UPPERCASE, Title Case, camelCase, snake_case, and CONSTANT_CASE
- Pattern search and replace with full Regular Expression (Regex) support
- Custom replacement rules for null, N/A, and NaN missing values
- Live Dataset Diff Metrics card tracking row reduction and changes in real time
- Mobile Cards vs Spreadsheet Grid toggle for flawless viewing on any device
How to Use Data Cleaner
Input Dataset
Paste or upload the dataset you want to clean.
Select Cleaning Rules
Check the boxes for whitespace trimming, blank removal, casing, or regex replacements.
Run Cleaner & Export
Click 'Run Data Cleaner' and download your purified dataset in CSV, TSV, or Excel (.xlsx).
Privacy & In-Browser Execution Guarantee
100% client-side privacy. All calculations, parsing, and charting execute locally in your browser with zero server uploads.
Frequently Asked Questions
Does data cleaning alter my column headers?
By default, casing normalization preserves your original header row so your database schema stays intact.
Can I use regular expressions to search and replace values?
Yes! Enable Pattern Search & Replace to use full regex patterns across all cells in your dataset.