CSV Statistics

Convert CSV data into JSON format.

Convert JSON arrays into CSV rows.

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 a JSON object or array into well-formed XML with a root element.

Parse XML and convert it to a JSON object, preserving attributes and nested elements.

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.

Convert CSV rows into YAML arrays of objects.

Convert YAML arrays of records into CSV rows.

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.

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

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.

Apply RFC 6902-style patch operations to JSON data.

Analyze JSON size and structural complexity metrics.

Add computed CSV columns with basic arithmetic formulas.

Convert JSON row objects into SQL INSERT statements.

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.

Convert JSON row objects into an XLSX base64 output envelope.

Flatten nested XML into a path-based key representation.

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.

Generate deterministic mock records for JSON/CSV/XML/YAML testing.