Data visualisations pique readers’ interest and engage their visuospatial mind.
This display, in combination with well-crafted words, is a comprehensive and powerful tool for scientific communication.
Data visualisations are different from technical infographics, which represent a wider range of information and concepts.
Choosing the best graph for your data
Graphs are the most common and recognisable way to visualise data. When you choose the right graph, your readers will easily and accurately understand what your data show. Download our factsheet: What type of graph is best for my data? [994KB] of this information.
Compare groups or categories
Recommended graph type: Horizontal bar graph.
Other graphs: Dot graph.
- Order bars by size to emphasise differences.
- Use clustered bars for groups with subcategories.
Show change over time
Recommended graph types: Line graph for many time points; vertical bar graph for few time points.
Other graphs: Dot graph; dumbbell graph for 2 time points for several groups.
- Only connect consecutive data values with lines.
- Lines always follow a horizontal direction from left to right, with time intervals on the x axis.
Compare parts to whole
Recommended graph types: Horizontal bar graph for a single population (bars represent parts or proportions); stacked bar graph for proportions of a measure across multiple populations.
Other graphs: Vertical stacked bar graph for proportions of a measure across a small number of time points; stacked area graph for proportions of a measure across many time points.
- Parts must add to 100% if they represent percentages, or the total absolute value for other measures.
Show frequency or distribution for 1 measure
Recommended graph types: Vertical bar graph (histogram) for measures with a small range of possible values; line graph (frequency polygon) for measures with a large range of values.
Other graphs: Horizontal strip plots and box plots.
- Strip plots and box plots may be unfamiliar to some readers – consider using a simple line or bar graph instead.
Show distribution across time or categories
- Show the spread of data values on a single measure over time.
- Show how data values are distributed for several categories or groups at a single time point.
Recommended graph types: To show the spread of data values on a single measure over time, use a line graph with shaded lower and upper bounds that represent this spread.
To show how data values are distributed for several groups at a single time point, use vertical strip plots, box plots and trellises (panels) of bar or line graphs.
- Measures of error around data values are often better understood as shaded bounds rather than vertical lines (error bars).
- Strip plots and box plots may be unfamiliar to some readers – consider using a trellis of bar or line graphs instead.
Recommended graph types: Vertical bar graph with a reference line to show differences between values for categories or groups and that reference; line graph with reference line to show differences between data values and that line over time.
- Data values above the reference indicate positive differences; data values below indicate negative differences.
- The y axis can measure absolute differences or percentage change between data values and the reference.
Recommended graph type: Scatter plot.
Other graphs: Side-by-side horizontal bar graphs to show an association between 2 measures when scatter plots are unfamiliar to readers (most effective for linear associations).
- Consider including a trend line on scatter plots to highlight the type and strength of association.
Show a difference across many groups
Recommended graph types: Dumbbell graph or clustered bar graph.
- It is difficult to compare the amount of difference between clustered bars for a large number of groups because of the distance between first and last groups along the x axis.
- Dumbbell graphs may be less familiar than clustered bars to some readers.