Deviation
Emphasise variations (+/-) from a
fixed reference point. Typically the
reference point is zero but it can also
be a target or a long-term average.
Can also be used to show sentiment
(positive/neutral/negative).
Example FT uses
Trade surplus/deficit, climate change

Diverging bar

Correlation

Ranking

Distribution

Change over Time

Show the relationship between two or
more variables. Be mindful that, unless
you tell them otherwise, many readers
will assume the relationships you
show them to be causal (i.e. one
causes the other).

Use where an item’s position in an
ordered list is more important than its
absolute or relative value. Don’t be
afraid to highlight the points of
interest.

Show values in a dataset and how
often they occur. The shape (or ‘skew’)
of a distribution can be a memorable
way of highlighting the lack of
uniformity or equality in the data.

Give emphasis to changing trends.
These can be short (intra-day)
movements or extended series
traversing decades or centuries:
Choosing the correct time period is
important to provide suitable context
for the reader.

Show how a single entity can be
broken down into its component
elements. If the reader’s interest is
solely in the size of the components,
consider a magnitude-type chart
instead.

Example FT uses
Share price movements, economic
time series

Example FT uses
Fiscal budgets, company structures,
national election results

Example FT uses
Inflation & unemployment, income &
life expectancy

Line + Column

Example FT uses
Wealth, deprivation, league tables,
constituency election results

Ordered column

Example FT uses
Income distribution, population
(age/sex) distribution

Histogram

Column

Part-to-whole

Stacked column

Magnitude
Show size comparisons. These can be
relative (just being able to see
larger/bigger) or absolute (need to
see fine differences). Usually these
show a ‘counted’ number (for example,
barrels, dollars or people) rather than
a calculated rate or per cent.
Example FT uses
Commodity production, market
capitalisation

Spatial
Used only when precise locations or
geographical patterns in data are
more important to the reader than
anything else.
Example FT uses
Locator maps, population density,
natural resource locations, natural
disaster risk/impact, catchment areas,
variation in election results

Flow
Show the reader volumes or intensity
of movement between two or more
states or conditions. These might be
logical sequences or geographical
locations.
Example FT uses
Movement of funds, trade, migrants,
lawsuits, information; relationship
graphs.

Column

Basic choropleth (rate/ratio)

Waterfall

e.g.

Diverging stacked bar

Scatterplot

Ordered bar

Boxplot

Line + column

Pie

Bar

Proportional symbol (count/magnitde)

Sankey

Surplus/deficit filled line

Connected scatterplot

Ordered proportional symbol

Violin plot

Line

Donut

Paired column

Flow map

Chord

Bubble

Dot strip plot

Population pyramid

Stock price

Treemap

Paired bar

Contour map

Network

XY heatmap

Slope

Dot strip plot

Slope

Voronoi

Proportional symbol

Equalised cartogram

Lollipop chart

Dot plot

Area chart

Sunburst

Isotype (pictogram)

Scaled cartogram (value)

Barcode plot

Fan chart (projections)

Arc

Lollipop chart

Cumulative curve

Connected scatter

Gridplot

Radar chart

Calendar heatmap

Venn

Visual
vocabulary

Priestley timeline

Designing with data
Circle timeline

There are so many ways to visualise data - how do we
know which one to pick? Use the categories across the
top to decide which data relationship is most important in
your story, then look at the different types of chart within
the category to form some initial ideas about what might
work best. This list is not meant to be exhaustive, nor a
wizard, but is a useful starting point for making
informative and meaningful data visualisations.
Inspired by the Graphic Continuum by Jon Schwabish and Severino Ribecca

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