CSV Tools

Convert CSV rows with headers into a clean JSON array.

Convert a JSON array of objects into CSV with generated headers.

Validate CSV syntax and structure — checks column consistency, unclosed quotes, and empty headers.

Normalize CSV by parsing and re-emitting with consistent quoting and proper cell escaping.

Render CSV data as an interactive table for quick visual inspection.

Keep only the columns you need. Specify column names and get a slimmed-down CSV.

Drop unwanted columns from a CSV. Specify which columns to remove and get a cleaned result.

Remove duplicate rows from a CSV, keeping the header and the first occurrence of each unique row.

Trim whitespace and normalize CSV records before conversion.

Convert CSV rows into XML records. Each row becomes a record element inside a records root.

Convert CSV content into a standalone HTML table document for browser-friendly sharing.

Convert CSV rows into YAML arrays of objects.

Sort CSV rows by one or more columns.

Filter CSV rows by column conditions.

Join two CSV datasets on a shared key.

Split CSV content into smaller row chunks.

Transpose CSV rows and columns.

Rename, add, or remove CSV headers.

Convert CSV between comma, semicolon, tab, and pipe delimiters.

Compute row/column stats and numeric summaries for CSV data.

Add computed CSV columns with basic arithmetic formulas.

Convert CSV text between UTF-8, Latin-1, and Windows-1252 encodings.

Convert a base64-encoded XLSX workbook sheet into CSV.

Convert CSV text into an XLSX base64 output envelope.

Profile CSV columns with inferred type, emptiness, uniqueness, top values, and numeric percentiles.

Apply per-column transformation rules to CSV data. Chain operations like trim, uppercase, lowercase, rounding, date conversion, and find-replace.

Create a cross-tabulation (pivot table) from flat CSV data. Specify row key, column key, aggregation field, and function (count, sum, mean).

Generate mock CSV with configurable columns including uuid, email, integer, float, date, boolean, enum, and name.

Plot numeric CSV columns as a bar or line chart. Choose axes and chart type; runs 100% in the browser.

Render CSV as a color-graded table where numeric cells are colored from cool (low) to warm (high) within each column.

Identify data quality issues in CSV: missing values, numeric outliers (IQR), type inconsistencies, and duplicate key rows.