design-a-chart

name	design-a-chart
description	Choose an honest visualization from a user story, metric, comparison, projection, target, or explanatory goal before selecting TanStack Charts marks. Load whenever a user asks to graph, chart, visualize, compare, forecast, project, explain, or communicate data.
metadata	{"type":"core","library":"@tanstack/charts","library_version":"0.16.0"}
sources	["TanStack/charts:docs/guides/choosing-a-chart.md","TanStack/charts:docs/examples/*.md","TanStack/charts:docs/reference/transforms.md"]

Design a Chart From a User Goal

Use this scenario loop: trigger → inspect → decide → build → verify. Do not begin with a chart type, even when the request names one.

Setup

Turn the request into this brief before writing chart code:

interface ChartBrief {
  question: string
  decision: string
  observation: string
  metric: { value: string; unit: string; denominator?: string }
  comparison:
    'time' | 'category' | 'distribution' | 'relationship' | 'composition'
  evidence: readonly string[]
}

export const brief: ChartBrief = {
  question:
    'Which acquisition channel improved conversion without losing volume?',
  decision: 'Choose where to increase next-month spend',
  observation: 'one row per channel and month',
  metric: { value: 'conversionRate', unit: '%', denominator: 'sessions' },
  comparison: 'time',
  evidence: ['conversion rate', 'sessions', 'month', 'channel'],
}

If the question, observation, unit, denominator, or decision is unknown, inspect the data and surrounding product before choosing marks.

Core Patterns

Match the form to the reader's comparison

• Change over ordered time → line; discrete periods → bars.
• Named-category magnitude → sorted horizontal bars or dots.
• Distribution → histogram, ECDF, box, violin, or faceted histograms.
• Relationship → scatterplot; add size only for a meaningful third quantity.
• Composition → stack for totals, normalized stack for proportions, mosaic for two categorical dimensions.
• Flow, hierarchy, network, or spatial questions → use their first-party layouts only when topology is the question.

Read the visual-task matrix for the full routing table.

Separate observed, target, and projected values

import { areaY, defineChart, lineY, ruleY } from '@tanstack/charts'
import { scaleLinear } from '@tanstack/charts/scales/linear'
import { scalePoint } from '@tanstack/charts/scales/point'

const rows = [
  { month: 'Jan', actual: 82, forecast: null, low: null, high: null },
  { month: 'Feb', actual: 91, forecast: null, low: null, high: null },
  { month: 'Mar', actual: null, forecast: 96, low: 88, high: 106 },
  { month: 'Apr', actual: null, forecast: 103, low: 90, high: 119 },
]

export const chart = defineChart({
  marks: [
    areaY(rows, { x: , : , : , :  }),
    (rows, { : , : , :  }),
    (rows, { : , : , :  }),
    ([], { :  }),
  ],
  : {
    : { : scalePoint },
    : { : scaleLinear, : { :  } },
  },
})

Use different channels for status and uncertainty. A continuous unqualified line implies equal epistemic status.

Define proof before polish

For every chart, verify:

• the visual answers the stated question;
• axes, legend, title, or adjacent copy identify units and comparison;
• ordering, aggregation, missing-value policy, and baseline are deliberate;
• exact-value tasks have a table or textual equivalent;
• the smallest supported container preserves the important comparison;
• pointer, keyboard, updates, and empty states tell the same story.

Common Mistakes

CRITICAL Starting with the requested chart type

Wrong: implement “make this a pie chart” before identifying the comparison.

Correct: restate the decision and recommend the form that makes that comparison perceptually direct. If the user retains a weaker form, state its analytical limitation and preserve the underlying semantics.

A familiar chart can answer a different question than the user needs.

Source: docs/guides/choosing-a-chart.md

HIGH Showing a rate without its denominator

Wrong: show conversion rate alone.

Correct: keep sessions or eligible population in the prepared row and expose it beside the rate or in the tooltip.

Normalized values can reverse interpretation when volume changes.

Source: API-FRICTION.md F-217; docs/reference/transforms.md

CRITICAL Rendering projections as observed history

Wrong: connect actuals and forecasts with one undifferentiated line.

Correct: encode the forecast boundary, projected segment, and uncertainty explicitly.

Continuous treatment implies equal certainty.

Source: docs/examples/lines-and-areas.md; docs/reference/marks/difference.md

HIGH Choosing area or angle for precise ranking

Wrong: rank close values with wedges, bubbles, or interior stack layers.

Correct: use aligned position or length when exact ordering is the reader's task.

Area and angle emphasize shape or part-to-whole relationships, not precise rank.

Source: docs/guides/choosing-a-chart.md; docs/examples/bars-and-rankings.md

HIGH Tension: analytical honesty versus visual simplicity

Simplifying aggregation can hide denominators, lineage, uncertainty, or missing-value policy. Preserve the evidence needed to interpret the result before reducing visual detail.

See also: prepare-chart-data/SKILL.md § Common Mistakes

References

• Analytical task and visual-form matrix

See also: prepare-chart-data/SKILL.md and compose-marks-and-views/SKILL.md — the analytical task determines both the transform and mark composition.