chart-chooserlisted

# Chart Chooser ## Overview This skill turns a dataset plus an analytical question into the *right* chart, and ensures the result is clean, accurate, and not misleading. It covers two jobs: 1. **Choose** — map the question intent and data shape to a chart type. 2. **Polish** — apply encoding, labeling, axis, color, and honesty rules so the chart reads correctly at a glance. Keywords: data visualization, chart type, graph selection, bar chart, line chart, scatter plot, histogram, heatmap, pie chart, dashboard, axis truncation, misleading charts, color accessibility, data-ink, encoding. Use this skill whenever someone needs to decide *how* to show data, or wants an existing visual critiqued. ## Workflow Follow these steps in order. Do not jump to a chart type before clarifying intent and data shape. 1. **Identify the question intent.** Pick the dominant one (a chart should answer one question well): - Comparison (which is bigger/smaller across categories) - Trend / change over time - Distribution (shape, spread, outliers of one variable) - Relationship / correlation (two+ numeric variables) - Part-to-whole (composition of a total) - Ranking (ordered comparison) - Geospatial (values across places) - Flow / part-to-whole over stages 2. **Profile the data shape.** Note for each variable: type (categorical / ordinal / quantitative / temporal / geographic), cardinality (number of distinct values), and whether values can be summed to a meaningful total