This map shows the number of confirmed cases of Covid-19
as the disease spread around the world
and brought much of life as we knew it to a complete standstill.
It's just one among dozens of data visualizations that have cropped up
to help convey the pandemic's staggering effects.
These graphs can be powerful tools for communicating data
but they're not always easy to understand.
Some charts present data around the coronavirus that are incomplete or even misleading.
We asked two data viz experts for advice
on how to get the most from these Covid graphics.
Let's start with one of the main graphs on people's minds,
which shows the number of confirmed cases
of Covid-19 over time.
These graphs can be plotted on linear scale
or on what's called log scale.
In the traditional linear scale, markings on the vertical axis
increased linearly from 1,000 to 2,000 to 3,000.
In log scale, markings on the vertical axis increased by tenfold
with equal spacing between 10, 100 and 1000.
In the linear scale, exponential growth is u-shaped.
It's represented by a dotted line that shows if cases increased
1.3 fold every day.
But in log scale it becomes a straight line,
which makes it much easier to see when the data deviates
from this alarming growth.
The difference can be seen in this graphic
from the New York Times which plots the same data
— Covid-19 cases in the US and Italy — in both linear and log scale.
Log scale reveals a slight leveling off of cases in Italy,
while in the US, cases continued to rise,
a distinction that's imperceptible from the linear graph.
A drawback to looking at log scale, however,
is that it can obscure the absolute value.
In this case, the true human toll.
For example, the number of cases
in Massachusetts looks fairly close
to New York in log scale.
But switching to linear view,
we see that New York actually has 6,000 more cases
per million people.
Sean O'Donohue, who works on visualizing biological data at the
University of New South Wales, says both views are useful.
O'Donohue: "The advantage of the low graph is really for looking at trends
and where things are going.
The linear graph is perhaps easier to interpret
as to where we are currently."
Another common format used to represent data related
to the global pandemic are maps.
Susan VanderPlas: "The spatial dimension is nice and familiar,
but you hide the population density that really matters."
For instance, an area might look like it has a particularly
high number of cases compared to the surrounding areas,
but that may just be because it's a city and more people live there,
says Susan VanderPlas.
Maps that represent data by shading in a region
can also bias our perception,
as larger regions capture our attention
simply because they have more pixels devoted to them.
To lessen that effect, VanderPlas recommends maps
like this, that use circle size to represent their value instead.
Other graphics take advantage of movement to get their point across.
Like this devastating chart showing Covid outpacing leading causes of death
or this representation, which shows the number of daily infections
as a function of time spent reading about the spread.
All of these graphs have limitations,
which VanderPlas and O'Donoghue say should be clearly marked.
For example, VanderPlas says any graph that plots
coronavirus cases should come with a huge asterisk
because these are just confirmed cases,
meaning that the numbers are limited by how much testing has been done
which can vary by a lot.
It doesn't tell us the number of actual cases in the population,
which is likely much higher and impossible to know at this point.
VanderPlas: "That's the reality of working in an evolving situation
is that you never have all the data that you want.
And whatever data a graph does use should be credited and linked O'Donoghue says.
O'Donoghue: "The core science of is really reproducibility
and if people don't present the sources for their data,
then we really should be very skeptical of what's being presented.
Ultimately, they say there's no perfect way to show all the data.
To really get a handle on the scope of this crisis,
you need to look at multiple charts.
And at least you'll have no shortage of options