data-table-design
Designs presentation tables that read correctly at a glance - numeric alignment, consistent precision, deliberate sort order, unit-labeled headers, and well-placed totals - and delivers a before/after redesign of the reader's table. Use when someone asks "make this table more readable", "how many decimals should I show", "should totals go at the top or bottom", "this report table is a mess", or is preparing tabular data for an exec deck or published report. Do NOT use for designing database tables, keys, and normalization - use database-schema instead; for narrative structure around the numbers - use data-story instead; for assembling the full multi-section document - use formatted-report-writer instead.
- License 许可
- MIT
- 最近更新
- 2026-10-14
- Stars
- ★ 25
- Forks
- 3
01 前言 Front Matter
- name
- data-table-design
- metadata
- { "title": "Data Table Design" }
- description
- Designs presentation tables that read correctly at a glance - numeric alignment, consistent precision, deliberate sort order, unit-labeled headers, and well-placed totals - and delivers a before/after redesign of the reader's table. Use when someone asks "make this table more readable", "how many decimals should I show", "should totals go at the top or bottom", "this report table is a mess", or is preparing tabular data for an exec deck or published report. Do NOT use for designing database tables, keys, and normalization - use database-schema instead; for narrative structure around the numbers - use data-story instead; for assembling the full multi-section document - use formatted-report-writer instead.
03 SKILL.md 正文
Data Table Design
A table is not a spreadsheet dump. Every formatting choice either helps or hinders the reader's ability to compare, rank, and interpret - and a misaligned or falsely precise table gets numbers misread in the meetings that matter. The output of this skill is a table a reader can extract the right conclusion from in under ten seconds.
Operating procedure
Step 1: Gather inputs
- The table as it stands (or the raw data), and where it will live: slide, printed report, dashboard, or scrolling web page - the medium changes the density rules in Step 5.
- The reader's single most likely question. Every subsequent decision serves it. If the owner cannot name the question, that is the first problem to fix.
- The action the reader takes from the table. Columns that inform no comparison or action are candidates for deletion.
- Units and the true precision of the data - what the collection method actually supports, not what the export prints.
Step 2: Set alignment
- Right-align all numeric columns without exception - alignment makes magnitude visible at a glance.
- Left-align text columns.
- Center column headers only when the column is narrow and centering does not visually disconnect the header from its values.
- Never mix alignments within a single column.
- Use tabular (fixed-width) figures where the medium allows; proportional digits break vertical comparison.
Step 3: Fix precision
Consistency within a column matters more than absolute precision:
- Currency: two decimal places for unit prices; zero for large aggregates (1,240,000 not 1,240,000.00).
- Percentages: one decimal place unless the context is scientific.
- Large numbers: use K, M, B suffixes with the unit noted in the header rather than printing eight digits.
- If a column mixes scales (most values in thousands, one in millions), flag the outlier with a footnote rather than changing the column format.
- Never imply false precision - round to the significant figures the data actually supports. Survey-based or estimated figures rarely support more than two significant figures; showing four communicates a certainty that does not exist.
Step 4: Choose sort order
Default to the order that answers the reader's most likely question:
- Rankings: descending by the primary metric.
- Time series: chronological.
- Categories with no natural order: alphabetical, or grouped by a meaningful variable.
- Never present data in database row order unless that order is meaningful.
Step 5: Place totals and control density
- Totals belong at the bottom, separated by a visible rule, bold row, or shading.
- Averages and totals never share an unlabeled row - they are different statistics.
- A percentage column gets a total only when it sums to 100% by design.
- Include only columns the reader needs to act on or compare; every extra column adds load. Beyond 8 columns, consider a chart or two smaller tables.
- Freeze or repeat the label column when a table scrolls horizontally.
- Zebra striping is acceptable above ~15 rows; skip it for short tables. On slides, cap at roughly 10 rows and 6 columns - beyond that the audience reads instead of listening.
Step 6: Write headers
Every header names the metric and the unit. "Revenue" is incomplete; "Revenue (USD K)" is correct. Avoid abbreviations unless universal in the reader's context.
Worked artifact: before/after
Bad - raw export pasted into the deck:
name revenue growth region id
acme co 1240300.5034 0.0521 west 10442
Beta LLC 87200.25 0.31 east 10318
zenith 15800000.00 -0.002 west 10559
delta inc 445100.9 0.0899 south 10201
Failure modes: database row order, mixed capitalization, an ID column no reader acts on, raw floats implying cent-level certainty on estimates, growth as unreadable decimals, no units, left-aligned numbers, the $15.8M outlier formatted identically to $87K.
Good - designed for "who is driving revenue, and is it growing?":
Company Revenue (USD K) YoY Growth (%) Region
Zenith 15,800 -0.2 West
Acme Co 1,240 5.2 West
Delta Inc 445 9.0 South
Beta LLC 87 31.0 East
------------------------------------------------
Total 17,572 -
Sorted descending by the question's metric, numbers right-aligned in thousands with the unit in the header, growth in percent with one decimal, ID column deleted, total at bottom behind a rule, and no total on the growth column because a sum of growth rates is meaningless. The reader sees in three seconds that Zenith dominates revenue but is flat, while the growth is coming from the small accounts.
Deliverable
Produce a redesigned table plus a short change log: the reader question it is optimized for, each formatting change made and the rule behind it, and any columns deleted with the reason.
Do NOT
- Do not left-align or center numbers; magnitude comparison depends on right alignment.
- Do not print export-level precision; false precision misleads more politely than a wrong number, but it misleads.
- Do not ship database row order; unsorted tables force the reader to do the analysis themselves.
- Do not total percentage or ratio columns unless they sum to 100% by design.
- Do not keep a column because the query returned it; keep it because the reader compares or acts on it.
Quality bar
- A cold reader answers the intended question within ten seconds.
- Alignment, precision, and units are consistent within every column, with units in headers.
- Sort order is deliberate and stated; totals sit at the bottom behind a separator.
- No column fails the "does the reader act on this?" test.
- Precision does not exceed what the data collection actually supports.
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