Choosing the Right Chart Type

Different data tells different stories. Time-series data needs line charts. Categories need bars. Relationships need scatter plots. Choosing the right chart type makes patterns obvious. Choosing the wrong one obscures them.

Line Charts: The Time-Series Default

Line charts show how values change over time. Stock prices over months. User signups over days. Traffic over hours. Most dashboards use line charts because most interesting metrics change over time.

Line charts are intuitive. People understand trends immediately. A line going up means good. Going down means bad. Multiple lines show comparison.

Bar Charts: Comparing Values Across Categories

Bar charts compare values. Revenue by product, users by country, errors by service. Heights make comparison obvious.

Horizontal bars are better for many categories (countries). Vertical bars work for fewer categories (products). Too many bars and they become unreadable.

Stacked Bar Charts: Composition and Total

Stacked bars show both total and composition. Revenue by product (stacked) shows total revenue and which products contribute. The problem: interior segments are hard to compare. The bottom segment (baseline) is easy to see. Middle segments are hard.

Use stacked bars when the bottom segment is most important. Avoid when interior segments need comparison.

Area Charts: Volume and Trend

Area charts are like line charts but filled. They emphasize volume. Multiple stacked areas show composition over time.

When areas overlap heavily, they become hard to read. Keep to 2-3 series maximum.

Scatter Plots: Correlation and Patterns

Scatter plots show correlation between two numeric variables. Price vs performance. Customer age vs spending. Each dot is a data point.

Scatter plots reveal patterns: positive correlation, negative correlation, clusters, outliers. Less common on dashboards but powerful for analysis.

Heatmaps: Density Across Two Dimensions

Heatmaps show intensity. Time of day vs day of week (when are users most active?). Geographic data (activity by region). Rows and columns with color intensity showing density.

Heatmaps can feel intimidating but are extremely information-dense. They show patterns quickly.

Pie and Donut Charts: Composition as Parts of a Whole

Pie charts show composition as percentages of a whole. Market share (Company A 35%, Company B 25%, Company C 40%). Donut charts are pie charts with a hole in the middle.

Pie charts have issues: they're hard to compare segments. Human brains judge area poorly. If segments are close (30%, 32%), it's hard to see the difference. Only use pie charts for 3-5 categories where one is clearly dominant.

A bar chart showing the same data is usually clearer.

KPI Cards: Single Numbers

The most-read element of any dashboard. A single metric with trend. Revenue: $500k (up 5% from last month). Displayed prominently with color coding (green for up, red for down).

KPI cards are not charts, but they're dashboard elements. Use them for headline metrics.

Tables: When No Chart Is Better

Complex data is often better in tables. Sortable, searchable tables. Operational dashboards (order list, user list, transaction list) use tables.

Charts are good for trends and patterns. Tables are good for detailed data and exact numbers.

When to Use No Chart

Plain numbers or text are sometimes the clearest presentation. "Latest deployment: 2 hours ago." "Active users: 1,234." Simple text, no visualization needed.