CSV cleaning
CSV cleaner with a plan you can review before running
Choose a CSV below to preview a basic cleaning plan without signing up. The local demo checks exact duplicate rows and fully blank rows. For broader profiling and AI-proposed rules, continue to the full TidyX workflow.
By the TidyX team · Updated
Preview a basic CSV cleaning plan
Rule-based and computed in your browser. This is not an AI-generated plan. Your file is not uploaded; this preview checks exact duplicate rows and fully blank rows without changing any data.
Loading the local CSV preview…
Profile the file before choosing transformations
The first step is deterministic profiling rather than immediate modification. The product reads the file within the published size, row, and column limits, detects its encoding, and summarizes the structure. You can see column types, missing percentages, distinct counts, duplicate rows, and warnings before requesting AI suggestions.
This separation matters because profiling and cleaning answer different questions. A profile tells you what appears to be wrong; a cleaning plan defines an explicit response. Keeping them separate makes it easier to reject an assumption before it reaches the output.
Use controlled rules for common CSV problems
The real execution path accepts only the operations already supported by the validated rule DSL. These include trimming whitespace, normalizing case and missing tokens, replacing known values, parsing numbers and dates, casting types, renaming columns, removing empty structures or exact duplicates, and flagging outliers.
Supported advanced rules include fixed or statistical missing-value filling, groupwise filling and bounded outlier treatments. These are high-risk decisions that require explicit acknowledgement. The engine rejects operations and parameters outside its validated rule set.
- Review affected columns and rule rationale
- Edit only validated parameters
- Treat pre-run estimates as suggestions, not measured results
- Choose CSV or XLSX for the cleaned output
Free browser tools for duplicate and fully blank rows:
Download a cleaned copy and real audit artifacts
A successful run exposes the selected cleaned-file format, a PDF report, and a JSON audit. The original upload remains separate. Run history and provenance values come from stored run records rather than sample dashboard data.
You can also download the data dictionary as JSON or CSV and save a successful run as a versioned recipe. Recipe reuse requires a compatibility check and another review; it does not execute automatically. Python and R downloads are not currently available.