zcbot/skills/ppt/references/visual-styles/data-journalism.md

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Visual style: data-journalism

Bloomberg / Economist news-infographic — publication-grade information density: multi-column grids, inline micro-charts, data tables, editorial sidebars, source lines. Cool and restrained, read like a financial long-read rather than a keynote. For finance, market reviews, research, annual data reports, data-driven explainers.


1. Shape & decoration

  • Shape language: a dense multi-column grid carrying many small charts and data tables inline; editorial sidebars and pull-stats; hairline dividers; hero numbers; a running source / footnote line. Information density is the look — kept legible by a rigorous grid.
  • Decoration: minimal beyond the data — a single accent rule, sparing annotation. Charts and numbers are the visual interest, not ornament.
  • Whitespace: tight but structured; the grid earns density without clutter.

2. Typography character

  • Serif headline / hero-number for authority × a clean sans or monospace for numeric precision in tables and chart labels. Small captions and source lines; tight, deliberate hierarchy.

Families are chosen at confirmation g; this style asks for a serif-headline × precise-sans/mono-data character.

3. Using the deck's colors

  • A restrained field — light publication paper or dark graphite both fit (Economist vs Bloomberg-terminal); the deck's accent marks risk / key figures, an optional secondary distinguishes a second series; charts use tints of the same family, never a rainbow.
  • Numbers are colored to mean (up / down / risk / focus), not to decorate.

HEX values come from confirmation e; this style only governs the restrained-field, meaning-coded-data discipline — it names no colors. (Dark-field legibility, if dark: shared-standards.md §6.)

4. Texture / elevation

  • Flat, publication-grade — hairline rules over heavy cards; optional scrim on any image; no glow, no decorative shadow.

5. Paired image-rendering

editorial — magazine-style infographic imagery sharing the data-publication aesthetic.