Different ways to represent your data, with examples and definitions.
Choose the right visualization for your data story.
Compare categories or groups to highlight differences and similarities.
Compare values across categories
When to Use
The standard way to compare the size of things. Must always start at 0 on the axis. Good when the data are not time series and labels have long category names
Compare multiple series across categories
When to Use
Compare multiple subcategories within each main category. Works best with limited series counts and consistent category ordering so viewers can scan differences quickly.
Clean alternative to bar charts
When to Use
Provide bar-chart style comparisons with reduced visual weight by using lines with dots at values. Particularly effective when comparing many categories with similar values or when labels are long, as the dot emphasizes precise readings while minimizing chart clutter.
Show how data is spread or distributed across different values or ranges.
Show frequency distribution
When to Use
A Histogram visualises the distribution of data over a continuous interval. Each bar in a histogram represents the tabulated frequency at each interval/bin.
Display quartiles and outliers
When to Use
Summarize distributions with median, quartiles, and outliers. Useful for comparing variability across many groups side by side.
Combine box plot with density
When to Use
Combine box plot summaries with a mirrored density curve to show distribution shape. Effective when sample sizes are large enough for smooth density estimates.
Smooth distribution visualization (Bell curve)
When to Use
Depict a smoothed probability distribution to highlight peaks, skew, and spread without binning artifacts.
Explore correlations and connections between two or more variables.
Show correlation between variables
When to Use
Explore relationships between two continuous variables, detect trends, clusters, and outliers. Works best with moderate point counts or added transparency.
Three-dimensional scatter plot
When to Use
Extend scatter plots by encoding a third quantitative variable as bubble size. Limit to moderate point counts (typically under 50 bubbles) to avoid overlap and maintain readability. Always provide a size legend and consider using transparency when bubbles overlap. Most effective when the size variable has meaningful variation.
Multiple variable relationships
When to Use
Provide a compact view of pairwise relationships among many variables using color intensity or annotations. Excellent for exploratory analysis.
Show how individual parts make up the whole or change over time.
Parts of a whole
When to Use
Show few parts of a whole where relative share is the story. Limit slices to five or fewer and keep values normalized to 100 percent.
Pie chart with center space
When to Use
Alternative to pie charts that creates central space for totals or labels. Use sparingly and retain limited slices to keep angles readable.
Hierarchical composition
When to Use
Visualise hierarchical data as nested rectangles sized by value. Best for large category counts where bar charts would be too tall.
Display data with geographic or spatial context and relationships.
Color-coded regions (World maps)
When to Use
Map geographic regions colored by a rate or ratio to reveal spatial patterns. Use standardized metrics and balanced color ramps.
Intensity-based geographic data
When to Use
Encode magnitude with color across a matrix or grid to reveal hotspots and patterns. Keep consistent scales and include legends for interpretation.
Track changes and trends over time periods.
Continuous change over time
When to Use
Show trends and rate of change over ordered categories or time. Ideal for continuous data sampled frequently and when relative movement matters.
Filled line chart
When to Use
Emphasize magnitude plus trend over time by filling under a line. Works best for cumulative totals or when comparing a small number of stacked series.
Discrete time intervals
When to Use
Communicate values that change at distinct intervals, such as tariffs or tiered rates, by drawing horizontal and vertical segments.