Unfortunately, you can’t just plop some numbers into your infographic and expect your readers to gain anything from it. You have to put a some thought into the presentation of the data to create clarity and boost understanding.
But I guarantee you, that little bit of extra effort you put into choosing the best chart for your data will be worth it! When used appropriately, charts can:
- Enhance comprehension of complex concepts
- Strengthen the persuasiveness of claims
- Make key insights more memorable
WATCH: How to pick the right types of charts for your data
So how do you go about choosing the best chart templates for your infographic?
Adding data to your charts with CSV Import
Once you’ve selected your chart, you need to upload your data. In Venngage, it’s simple.
In the editor, double-click on the chart to open the widget. Under the DATA tab, click the green button labeled IMPORT and select your CSV file. The chart will instantly visualize your data once it’s imported.
The most common types of charts are:
- Bar charts
- Line charts
- Pie charts
- Bubble charts
- Stacked bar charts
- Word clouds
- Doughnut charts
- Area charts
- Scatter plot charts
- Multi-series charts
Use the ICCOR method to choose the best chart for your infographic
At Venngage, we’ve developed the ICCOR method to help you choose the best charts for your infographic.
There are two steps to making the ICCOR method work for you:
- Determine your visualization goal
- Choose the best chart to achieve that goal
Step 1: Determine your visualization goal
If you try to dive into visualizing your data without any clear goals, you’re never going to produce anything useful.
Garbage in, garbage out, right?
Instead, start by defining a single visualization goal for your chart. That goal should line up with one of our ICCOR categories, either to:
- Inform: convey a single important message or data point that doesn’t require much context to understand
- Compare: show similarities or differences among values or parts of a whole
- Show Change: visualize trends over time or space
- Organize: show groups, patterns, rank or order
- Reveal Relationships: show correlations among variables or values
Not sure what your goal should be? Spend some time getting to know your data. Look for patterns, groupings, trends, outliers, and key data points. The things that stand out to you are the same things that you should emphasize to your readers.
Step 2: Choose the best types of charts to achieve that goal
With your goal in mind, it’s time to choose your chart!
There are a number of charts that can work for each ICCOR goal.
Let’s review each one with some chart design best practices for each.
Best types of charts for informing
So you have a single data point or key message that you want to hit your readers over the head with.
The easiest way to do that in an infographic is to simply use big, bold (colorful) text.
The nice thing about this strategy is it gets right to the point–there’s no room for misinterpretation.
Sometimes a single number, without any context, might not seem very significant.
This problem is easily remedied. Use simple symbols or icons to add a bit more context–like an arrow to emphasize growth or decline:
Or an icon chart (an icon with two fill colors, where the ratio is represented by the height of the main color) to make proportions more tangible.
A more accurate way of representing a proportion is by directly spelling it out in a pictogram, a matrix of icons in which one icon represents a unit or group of units. When making pictograms, try to stick with nice round numbers like 10 or 100 that are easy to grasp:
Best types of charts for comparing
If you want to show similarities or differences among values or parts of a whole, you’ve got a lot of options.
Use a bar or column chart to compare independent values
We, as readers, are particularly good at comparing the length of bars in a bar chart (in contrast to the segments of a pie chart, for example), making bar and column charts the best charts for showing comparisons.
For the most part, bar charts and column charts can be used interchangeably. However, if you want to compare the change in some metric over time, it’s better to stick with a column chart so that time is represented from left to right.
If you happen to have long labels for each data point (like when you’re charting survey results, for example), the horizontal bar chart is a better choice. It allows extra space for each label so that hard to read vertical or angled text can be avoided:
Note the order of the bars here–since the dataset has no inherent order, sorting the bars from greatest to least adds an extra dimension of information. Also note the ratio of bar width to bar spacing. The space between the bars should be about half of the bar width for optimal readability.
While bar and column charts are the best choice in terms of data readability, infographics sometimes call for something a little more unique and engaging.
Enter: the bubble chart.
Use a bubble chart to compare independent values with clear outliers
In a bubble chart, values are represented by circle area instead of bar length. Since we’re not particularly good at making precise judgements of circle area, it’s only a good idea to use bubble charts when there are clear outliers or large gaps between each value. I’d also recommend explicitly labeling each bubble with its value.
Use a pie chart to compare parts of a whole (composition)
The simplest way to visualize simple part-to-whole relationships is with a pie chart. Make your pie charts easy to read by:
- Ordering segments from greatest to least
- Starting the first segment at 12:00 and continuing clockwise
- Limiting the chart to a maximum of 7 segments
While pie charts are ubiquitous and easily understood, they do have their limitations (i.e. when comparing the composition of multiple values). Instead:
Use a stacked bar or stacked column chart to compare the compositions of multiple values
Even stacked bar charts are fairly limited in their uses, though. They only really work when you have very few bars and very few segments, or when differences between bars are very large. If you’ve got lots of data or the differences within your data are subtle, a series of bar charts would be a better choice.
Basically–bar charts are the most reliable method for visualizing comparisons.
Best types of charts for showing change
There’s a little more flexibility when it comes to visualizing trends over time or space.
Use a line chart or an area chart to show changes that are continuous over time.
Line charts are the most effective chart for displaying time series data. They can handle a ton of data points and multiple data series, and everyone knows how to read them. Just make sure your points are ordered such that time runs from left to right, and use consistent time intervals.
Area charts can be more aesthetically pleasing, but require some more finesse. They’re only really appropriate to use with less than four data series, and it’s a good idea to introduce some transparency to make sure each area is visible.
But time series data isn’t always purely numerical!
Use a timeline infographic to visualize events over time
Use a choropleth map to show location data.
A chloropleth map is a map crossed with a heatmap. They’re usually shaded in proportion to the value of some variable, and can be used to show location-based patterns:
Use a map series to show changes in location data over time
Best types of charts for organizing
Charts for organizing data or information in an infographic can take many forms, depending on whether you want to show groups, patterns, rank, or order. I’ll just touch on a few essentials.
The simplest form of infographic organization is a list.
Use a numbered list to show rank or order when you want to provide textual information about each element (for example, when describing a linear process)
Use a table to organize when you want readers to be able to look up specific values
Tables are best when precise values are required, when viewers need access to individual numbers, or when the dataset contains a number of different units (which would be challenging to visualize on a single graph).
To emphasize the most important data in your tables, apply a few unique design touches.
When working with tables in the editor, you have a few options to customize the look of your table. Under the data tab you’ll see options to select fonts and background colors.
Here you can choose different fonts, font sizes, their styles and colors. You can also select specific cells and apply a unique background color to make your information pop.
If you need to align your text, switch over to the settings tab. Under ‘body options’ you can choose the horizontal and vertical alignment of your text within the cell. These simple features help to effectively organize your information.
While tables can provide a lot of detail, they don’t give you a sense of shape of the data, so it’s often a good idea to include a tables as a supplement to a more visual chart.
Use simple boxes, borders, arrows, and lines to visually organize groups (as seen in Venn diagrams, mind maps, and flow charts)
Most of the other methods of organizing information rely on two basic principles:
- Using shapes and borders to create groups
- Using lines and arrows indicate the relationship between groups (i.e. connect groups)
Some popular infographic charts that use these principles are the Venn diagram:
And the mind map:
To find the best organizational chart for your infographic, think about the structure of your information and find a chart that reflects that structure. Our flow chart maker will simplify the design process for you.
Best types of charts for revealing relationships
Two key types of relationships you might want to reveal within a dataset are correlation and distribution.
Use a scatter plot to reveal the correlation and distribution of a two-variable dataset
Scatter plots are the easiest way to explore a potential correlation between two variables, and can also reveal the distribution, clustering, and outliers of a dataset.
Scatter plots are handy because they don’t require the data to be aggregated or pre-processed to reveal the distribution of a dataset.
If you’re willing to do some preprocessing or you already have nicely aggregated data:
Use a histogram to reveal the distribution of a single variable
Histograms are the standard way to display age demographic data, and are great for all kinds of distributions.
Quick tips for infographic chart design
Now that we’ve covered how to choose the best chart for each ICCOR goal, it’s time to talk chart styling.
At best, properly styled charts can make your infographics clearer and more persuasive.
At worst, poorly designed charts can be misleading, create confusion, undermine the credibility of the author. If you’re interested, check out how bad chart design was used in the media to skew data during the 2016 U.S. election.
To make sure you create charts that are clear, accessible, and 100% above board, let’s review some chart design best practices.
Start chart axes at zero, and use consistent intervals for tick marks
One of the biggest data visualization faux pas is axis truncation. Starting the axis of a bar or line chart at some value other than zero is a sure-fire way to distort your data:
In most cases, it’s best to start your axes at zero. If you choose not to, make sure you have a good reason for it. Similarly, make sure the scale of your chart is apparent by labeling your axes with regularly-spaced tick marks at logical intervals (such as every 5, 10, or 100 units).
Reduce non-data ink
Your data should always be the star of the show.
Data visualization guru Edward Tufte coined the term “data-ink ratio” to emphasize the importance of minimalism in chart design. The general idea: a large share of the ink required to print a graph should directly represent data-information.
Basically, things like borders, gridlines, background colors, and other extra decorations should take a backseat to the points, bars, or lines that actually represent the data.
Do your best to lighten labels and gridlines, diminish colors, eliminate backgrounds, avoid borders and outlines, and above all…get rid of any 3D or other “special” effects.
Don’t forget labels, legends, and annotations
Labels are your friends.
Chart labels, headings, and annotations should be used to explicitly state the things you want your readers to take away from your chart, to eliminate the possibility of misinterpretation.
Don’t be afraid to be redundant, either. It’s okay to repeat key takeaways in both a subheading and an annotation.
When labeling lines, bars, or points, try to avoid relying on a separate legend. Place labels as close to their corresponding data points as possible, so that your reader doesn’t have to search to match up labels with data points.
Oh, and don’t forget to include your data sources. Link to your data source at the bottom of your infographic in small type (less than 10 pt size).
Pro Tip: Use a link shortener to make your link easier to access.
Use color for function, not decoration
Color use plays a significant role in how “busy” your infographic will appear.
To make sure things don’t get too messy, don’t use more than six colors in any given chart. When you’ve got more than one chart in an infographic, use those colors consistently across all of your charts.
For more complex chart charts, choose one key color to distinguish more important values from less important values (and use gray to attenuate the data that you want to be less of a focus).
In contrast, don’t rely on color to make your chart legible–your chart should be just as meaningful in black and white as it is in color.
Order data logically
Present your data in an order that your reader will expect.
Have a time series? Order it with the earliest data point on the left and the latest data point on the right.
Have a pie chart? Starting at twelve o’clock, order segments clockwise from largest to smallest.
Representing categories that have no natural order? Consider ranking them from largest to smallest.
Keep it simple!
Finally, when visualizing data in an infographic, I urge you to exercise restraint. Don’t overload your charts with too much data.
Infographic data must be easy to understand at a glance. If there’s too much going on in the chart, your reader is likely to give up and move on.
Some rules of thumb:
- Use less than 6 lines in a line chart
- Use less than 10 bars in a bar chart
- Use less than 7 segments in a pie chart
If this means manipulating your data (by removing points, grouping points, or by looking at shorter spans of time), take time to consider the tradeoff between readability and data accuracy. Try to reduce your dataset down to its most essential pieces without introducing inaccuracy or skewing your data.
If you can’t get around including a ton of data, it’s not the end of the world. Contrasting a single bright color with muted greys can help your readers make sense of even hundreds of data points:
A good way to make sure that your chart is simple enough? Have a friend look it over, and resist the urge to explain it to them. If your friend can’t understand your chart without any verbal explanation, it’s too complex for an infographic.
Alternatively, do a squint test. Squint your eyes until you can’t read any text–do you still get something from the chart? If not, simplify your charts a little more.
So to sum all of this up:
- be diligent with your axes
- use color thoughtfully
- minimize the non-data ink
- don’t forget about labels and annotations
- cite your sources
- order your data logically
- don’t overload your chart with too much data
Luckily for you, the default styling of Venngage’s chart widgets take care of a lot of this chart design stuff for you. Just click the chart you want to use, pop in your data, and you’re good to go!
The power of well-presented data should not be underestimated, and the right chart can make all the difference. Use the ICCOR Method to choose the best charts for your infographic data.