Data Generator

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.

Validate JSON syntax and surface parse errors.

Pretty-print JSON with consistent indentation.

Minify JSON by removing unnecessary whitespace.

Compare two JSON documents and highlight differences.

Sort object keys alphabetically for stable JSON output.

Escape JSON into a quoted string literal for embedding.

Unescape a quoted JSON string back into readable JSON or plain text.

Flatten nested JSON objects into single-level key paths.

Rebuild nested JSON from flattened path-based keys.

Generate a draft JSON Schema from sample JSON input.

Validate JSON data against a provided JSON Schema.

Evaluate JSONPath expressions against JSON input.

Run jq-like query expressions to extract or transform JSON data.

Convert JSON objects or arrays into well-formed XML.

Parse XML into a formatted JSON representation, preserving nested elements and attributes.

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 a structured XML document with repeating record elements into CSV rows.

Convert JSON objects and arrays into clean, human-readable YAML.

Parse YAML and convert it to formatted JSON.

Validate YAML syntax and report the parsed type and top-level keys on success.

Normalize YAML by parsing and re-emitting with consistent 2-space indentation and block style.

Check XML well-formedness and report the root element and any parse errors with line numbers.

Pretty-print XML with consistent 2-space indentation for improved readability.

Minify XML by removing whitespace and indentation.

Convert XML structures into readable YAML output.

Convert YAML content into XML format.

Convert CSV rows into YAML arrays of objects.

Convert YAML arrays of records into CSV rows.

Sort YAML mapping keys alphabetically, recursively.

Merge multiple JSON documents into one output object.

Split large JSON arrays into smaller chunks.

Rename one or more keys across JSON objects.

Find and replace values in JSON content.

Filter JSON records using key/value conditions.

Evaluate RFC 6901 JSON Pointer expressions against JSON input.

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.

Compare two XML documents and highlight structural differences.

Evaluate XPath expressions against XML input.

Run a clearly labeled practical XQuery subset for XML exploration: direct XPath, simple for/let expressions, count(), and string().

Validate XML against a provided XSD schema.

Normalize or strip XML namespaces for downstream compatibility.

Compress YAML into a compact representation.

Compare two YAML documents and report differences.

Merge multiple YAML files into one document.

Flatten nested YAML structures into path-based keys.

Rebuild nested YAML from flattened path keys.

Lint YAML style and structure with stricter quality rules.

Evaluate path expressions against YAML input.

Run query expressions to extract or transform YAML data.

Rename keys in YAML mappings.

Find and replace values in YAML content.

Lint JSON syntax and style with stricter practical checks.

Generate RFC 6902-style patch operations from left/right JSON values.

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

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

Split a YAML top-level array into chunked sub-arrays.

Validate YAML content against a JSON Schema.

Apply RFC 6902-style patch operations to JSON data.

Analyze JSON size and structural complexity metrics.

Escape XML special characters for safe embedding.

Decode escaped XML entities back to plain characters.

Split repeated XML child elements into chunked XML documents.

Add computed CSV columns with basic arithmetic formulas.

Convert JSON row objects into SQL INSERT statements.

Generate a starter XSD schema from XML structure.

Merge two XML documents into one combined output.

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

Convert a base64-encoded XLSX workbook sheet into CSV.

Convert record-like XML data into SQL INSERT statements.

Render XML as a structured HTML document for browser-friendly viewing.

Convert CSV text into an XLSX base64 output envelope.

Convert JSON row objects into an XLSX base64 output envelope.

Sort XML element structures for deterministic ordering.

Flatten nested XML into a path-based key representation.

Render JSON as an interactive collapsible tree with type labels and copyable paths.

Render a JSON array of objects as a sortable, searchable table for fast inspection.

Render YAML as an interactive collapsible tree for easier config exploration.

Visualize XML as an interactive tree with attribute-aware node inspection.

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

Profile field-level type consistency for JSON arrays, including null-rate and unique count metrics.

Audit JSON Schema complexity with required/optional coverage, depth, and missing description checks.

Analyze XML structure with element counts, tag frequency, depth, attribute totals, and namespace usage.

Analyze YAML structure for key depth, type distribution, array sizing, and anchor/alias usage.

Auto-detect whether input is JSON, XML, YAML, CSV, or plain text.

Detect, pretty-format, and analyze API responses into a JSON report with HTTP metadata and formatted payload previews.

Run JSONPath, XPath, XQuery-subset, YAMLPath, and JSONata queries through one tool.

Auto-detect sources and convert across supported JSON, XML, YAML, CSV, and Excel pairs, including structured JSON input and Excel base64 envelopes.

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).

Project and rename fields from a JSON array of objects. Select which columns to keep and optionally rename them.

Group a JSON array of objects by a specified field. Output as a keyed object or as an array of groups.

Filter a YAML array of records by field conditions. Supports operators: equals, not-equals, contains, gte, lte.

Convert XML attributes to child elements or vice versa. Specify target tags to transform selectively.

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

Generate a valid JSON template from JSON Schema using defaults, examples, enums, and type placeholders.

Infer a schema from YAML input and emit the inferred schema as YAML.

Generate UUID or sequential IDs in JSON array, newline, or CSV formats.

Generate timestamps in multiple formats for offsets from an anchor date.

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.

Given a regex pattern, generate N example strings that match it. Useful for structured IDs, codes, and format-specific mock values.