About

Data presentation is the bridge between raw computation and human understanding. However, the syntax required to build structured tables across different environments - Web (HTML), Documentation (Markdown), or Databases (SQL) - is notoriously brittle and repetitive. A single missing delimiter or unclosed tag can corrupt an entire dataset.

This Universal Table Architect is not just a generator; it is a bidirectional transformation engine. It treats table data as a mathematical matrix ijrowscols, decoupled from its visual representation. This allows you to import legacy formats, manipulate the structure using spreadsheet logic, and project the data into any modern syntax.

We address the "n × m complexity" problem. Whether you are migrating a CSV (text) dump into a PostgreSQL database, converting a JSON API response into a Tailwind CSS component, or formatting a scientific dataset for a LaTeX paper, this tool handles the syntax rules, type inference, and alignment calculations automatically.

Formulas

To achieve perfect ASCII alignment in Markdown, we calculate the required padding p for each cell c_i,j based on the maximum grapheme cluster length in its column j:

Width_j = max(len(row_i,j) for all i in rows) + 2

For SQL generation, type inference is performed by checking if a set of values V_j in column j satisfies the condition:

Type_j =

{

INT if ∀v∈V_j, isInteger(v)FLOAT if ∀v∈V_j, isNumber(v)VARCHAR otherwise

Reference Data

Output Format	Syntax Engine	Features & Capabilities	Target Environment
HTML5	DOM/String Builder	Classes, ARIA roles, Theming (Bootstrap/Tailwind)	Web App, Landing Page
Markdown	ASCII Aligner	GFM Compliance, Pretty-print alignment, Whitespace padding	GitHub, Obsidian, Jira
SQL	Schema Inference	Auto-detect types (INT, VARCHAR), Dialects (MySQL/PG)	Database Seeding, Migrations
JSON	Object Mapper	Array of Objects, Key-Value pairing, Minification	REST APIs, NoSQL (Mongo)
CSV / TSV	Delimiter Logic	RFC 4180 compliance, Escaping, Custom delimiters	Excel, Data Science, R/Python
LaTeX	TeX Parser	Booktabs support, Environment wrapping	Academic Papers, PDF
YAML	Indentation Engine	Nested structures, Key mapping	Config files, Frontmatter
XML	Node Builder	Custom root/item tags, Attributes	SOAP, Legacy Systems

Frequently Asked Questions

The heuristic engine analyzes the first few lines of your input. It counts occurrences of potential delimiters (commas, tabs, pipes, semicolons) to statistically determine the format. It also detects enclosing characters like quotes or brackets to distinguish between CSV, JSON, and HTML. Broken HTML is parsed using the browser's native DOM parser to recover valid structure.

Yes. Copy the cells in Excel (Ctrl+C), which puts tab-separated values (TSV) into your clipboard. Paste this directly into the "Import" area. The tool will detect the tabs and generate a clean HTML table, to which you can apply Bootstrap or Tailwind presets instantly.

Yes. It attempts to infer the column data types (Integer, Date, String) based on the content. It generates both the `CREATE TABLE` schema with these types and the `INSERT INTO` statements for the data. You can customize the table name and toggle dialect-specific quoting.

No. This tool operates entirely client-side using JavaScript. Your sensitive data (financials, user lists, API keys) never leaves your browser memory. All processing, parsing, and formatting happens locally on your device.

In the "HTML" export settings, select the "Responsive Wrapper" option. This adds a container div with `overflow-x: auto` (or the framework-equivalent class like `table-responsive` for Bootstrap), ensuring the table allows horizontal scrolling on small screens without breaking the page layout.