How It Works

The viewer reads your input as rows and columns, calculates the maximum width of each column, then pads every cell so that vertical borders line up from top to bottom. This is the same basic approach used by many CLI table printers, but packaged in a fast, copy-friendly interface.

Because the output is plain text, it is resilient: it survives copy/paste, renders consistently in code blocks, and stays diff-friendly in version control. If you prefer tooling that does not depend on Markdown renderers, HTML tables, or screenshots, ASCII tables are a dependable option.

Step-by-step

• 1) Paste data: Provide rows separated by new lines. Each row contains columns separated by the delimiter you choose.
• 2) Choose delimiter: Select comma (CSV), tab (TSV), pipe (|), semicolon, or whitespace, depending on your source.
• 3) Enable headers (optional): If the first row contains column names, turn on the header option to insert a divider line below it.
• 4) Select alignment: Left alignment works well for names and descriptions, right alignment helps numbers compare cleanly, and center alignment is useful for short labels.
• 5) Generate output: The tool builds the border lines and padded rows and presents the final table for copying or downloading.

Internally, the tool also normalizes uneven rows by padding missing cells with blanks. That means you can paste imperfect data samples and still get a rectangular table instead of a broken layout.

Key Features

Multiple delimiter support

Work with common delimited formats such as CSV (commas) and TSV (tabs), as well as pipe-delimited and semicolon-delimited lists. This flexibility is practical because different tools export data differently: spreadsheets often produce CSV, database clients can produce TSV, and chat-friendly snippets often use the pipe character.

If columns appear merged or split incorrectly, switching the delimiter is usually all you need. A quick regenerate is faster than manually reformatting spacing across multiple lines.

Header divider for readability

When the first row contains column names, a divider line makes scanning dramatically easier. It visually separates metadata (headers) from values (rows), which matters most when your table has many columns or includes both text and numbers.

In technical documentation, headers also reduce ambiguity. Clear column names prevent misinterpretation when tables are forwarded, pasted into tickets, or referenced weeks later during an incident review.

Alignment controls

Alignment is more than aesthetics. Right-aligned numbers are easier to compare because magnitudes line up. Left-aligned text reads naturally. Center alignment can highlight short statuses like “OK”, “WARN”, or “FAIL”. By choosing an alignment that matches your content, you make the table faster to read and less error-prone.

For mixed tables (text + numbers), you can generate one table per perspective—for example, a numeric-focused table with right alignment for a metrics discussion, and a text-focused table with left alignment for a summary.

Handles uneven rows gracefully

Real-world input is often messy: some rows may be missing a value, or an export may contain trailing delimiters. The viewer pads shorter rows with empty cells so borders still line up. If one row has extra columns, the table expands to the widest row so you do not lose data.

This behavior is ideal when you are sampling logs, combining quick lists from multiple sources, or validating a dataset before cleaning it up properly.

Copy and download workflow

Once generated, the output is ready to copy with one click. For longer tables, downloading a .txt file can be more convenient, especially if you plan to attach it to a ticket or commit it to a repository. Both actions are designed to keep formatting intact.

Diff-friendly documentation

ASCII tables are easy to review in pull requests. Changes to values show up as normal text diffs, without noise from HTML tags or renderer-specific formatting. This is helpful for configuration references, feature matrices, and release documentation that evolves over time.

Use Cases

• README and documentation: Present configuration options, environment variables, CLI flags, or feature comparisons in a format that stays readable in any code viewer.
• Terminal output cleanup: Convert quick query results or script output into aligned columns that are easy to scan while debugging.
• Support tickets and incident notes: Paste structured data into tickets without losing alignment, so responders can understand details at a glance.
• Chat collaboration: Share structured information in Slack, Teams, or other chat tools using code blocks, keeping a consistent layout for everyone.
• Data review and QA: Quickly validate small datasets by converting them into a fixed-width view that exposes missing values and inconsistencies.
• Release notes and change logs: Communicate updated limits, defaults, pricing tiers, or compatibility changes in a table that readers can scan quickly.
• Inventory lists: Maintain quick lists of devices, licenses, or assets in a portable format suitable for email and ticketing systems.

ASCII tables shine whenever the destination system might strip formatting or render tables inconsistently. Because the output is plain text, you can store it in version control, paste it into code reviews, or embed it in templates and reports without worrying about formatting drift.

Example: If you have a CSV snippet like “Name,Role,Level” and a few lines of values, the viewer can turn it into an aligned table you can paste into a GitHub issue. Reviewers will see a clean grid instead of uneven spacing, and the table will remain readable even when quoted in email threads.

Another example: If a database client returns tab-separated output, choose the tab delimiter and generate a table that can be pasted into an incident timeline. The fixed-width structure makes it easier to compare timestamps, durations, and statuses quickly.

Optimization Tips

Normalize your input first

If your source data includes inconsistent spacing or stray delimiters, clean it up before generating the table. Removing accidental extra columns and trimming whitespace produces the most predictable output and keeps tables compact.

A quick way to check cleanliness is to look for empty columns. If you see borders that suggest extra blank columns, the data likely contains trailing delimiters or repeated separators.

Pick the delimiter that matches your source

CSV exports typically use commas, while many command-line tools output tabs. Pipe-delimited input is common in hand-crafted notes because it is easy to read. If columns appear merged or split unexpectedly, switch the delimiter and regenerate rather than trying to “fix” the output manually.

When using whitespace separation, make sure your data does not contain multi-word fields unless they are quoted or otherwise protected. For names and descriptions that contain spaces, CSV or pipe is often a better fit.

Use alignment strategically

Right alignment is ideal for numeric comparisons because magnitudes line up. Left alignment works best for names, paths, and descriptive text. Center alignment helps with short labels or categorical statuses. The best choice depends on what readers are trying to compare.

If a table is very wide, consider splitting it into smaller tables by topic, reducing the number of columns, or abbreviating long headers. Narrower tables reduce horizontal scrolling and make copy/paste into tickets more reliable.

FAQ