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When it comes to conveying information to your audience, charts are a simple and effective way to do it. That is, if the charts are done right.
A lot goes into making the perfect visual content, and it’s easy to lose a few elements through the cracks. Charts, when thrown together hastily, are often more harmful than helpful.
To help you avoid this, we've put together a list of helpful do's and don'ts to keep in mind when creating your own data representations, whether in the form of simple bar charts and graphs or more complex interactive visualizations.
As you prepare your graphics, it is important to choose a chart which best suits your data.
Do use the appropriate chart for your data. Know your basic charts and what they are best at so you can create the most effective graphic for your audience. Three of the most popular charts are bar, pie, and line charts. At the same time, there are two types of data, qualitative and quantitative, which can each be divided into two subtypes.
The first kind of information, qualitative data, consists of ordinal and nominal data. The first refers to a scale which is specifically made for its data group. This kind of data often appears in questionnaires when people are asked to rate different aspects on a scale of bad to good, usually represented as one to five. Meanwhile, nominal data is not ordered or measured, but rather sorted into categories. An example of nominal data would be a record of a person’s sex or eye color.
The second kind of information, quantitative data, includes discrete or continuous data. Discrete data is measured in integers that represent a unit in its entirety, such as the number of people in a household. Continuous data, rather than representing a single data point, represents measurements that can vary in value while still falling under the same label, such as a record of people’s weights or heights.
Each type of data can be represented using a variety of popular charts, though certain kinds of charts are better suited for different types of data.
Bar charts work best when used for nominal data, as well as discrete data, and are useful for comparisons. Likewise, pie charts can be used for discrete and ordinal data to display parts of a whole. Line charts are best for continuous data as it connects many variables that all belong to the same category.
When using charts on an x (horizontal) and y (vertical) axis, especially a bar graph, do make use of the full axis. Starting a graph at zero avoids any chance of your graph being misleading with its data and therefore misunderstood by your audience. For example, a bar graph beginning above zero risks exaggerating the differences between the data being compared.
An exception to always starting an axis at zero is found in the case of certain line graphs. When the data tends to vary minimally at a quantity far above zero, it is difficult to read. In this situation, starting a baseline at a quantity closer to the data brings the variations to light. Just be careful you don’t have the data touching the bottom axis. Leave a clear margin between your lowest data point and the axis.
Also, don’t change the style of your graph when making comparisons. For example, both bar and pie charts are styles that can show discrete data. When these styles are put side by side, however, it is difficult to make comparisons between the two. It can be jarring to your audience and make it difficult to understand your information. Instead, keep your styles consistent. When comparing the same data over a course of multiple charts, pick one style or type and keep it the same.
Once you have picked a chart type which best suits your information, be careful to keep your graph easy to understand. Charts, as well as any visual aid, should make it quick, easy, and painless to understand your data.
Do keep your chart simple. Edward Tufte, a statistician, said “Graphical elegance is often found in simplicity of design and complexity of data.” One way to simplify your charts without taking away from your data is through Tufte’s data ink ratio. Remove extra ink in the form of borders, gridlines, and even legends to simplify your graph’s overall look. For example, instead of legends and a y axis, label data directly with its category and quantity.
To increase readability for bar graphs with multiple categories with long names, do use a horizontal bar graph and arrange data from greatest to least in descending order. This keeps your audience from craning their necks in order to read long labels and also clearly defines the relationship between all of your data.
Be careful you don’t overload charts with too much information. Twenty lines, while showing a wide range of data, are difficult to read and take time for your audience to comprehend when really they should understand it at a glance.
Also, for the most ease and readability, don’t use a pie graph. Widely detested amongst statisticians, pie graphs often have questionable data and are difficult to interpret. If a pie chart is your best option, don’t use more than seven wedges or else it will be hard to discern the differences in your data.
After your information has been added to the chart of your choice, it is time to make sure that the data you want your audience to notice is emphasized. With a few specific color selections, it is easy to either make your information stand out or have it get lost amidst the crowd.
Be sure you do use intense color contrasts. The simplest color contrast is black and white. The addition of highly saturated colors such as blue on a white background will really make your data pop. Not all colors play together nicely, however, so be careful. For instance, yellow on white and navy on black are each respectively hard to see.
Do emphasize your most important data through color. For example, on a line graph, have your valuable lines be color while less important information can be gray. In a bar graph, make your largest quantity the brightest color with each subsequent category being less and less saturated. Choices like these can really draw attention to where you want it to be.
Don’t use more than six colors together, though. Too many colors means similar hues will appear, like blue and green, which can be difficult to tell apart. Also, the paler a color is, the harder it is to see. Too many colors is like having too much data. It is confusing and distracting.
Also, don’t use red and green or orange and green to make comparisons on the same chart. About 10% of men are color blind with red/green being the most common form of color blindness. Orange is close to red, making these colors completely indiscernible. In order to make your charts more accessible to your audience, avoid these color combinations at all costs.
With your chart appropriately chosen, data readable, and colors selected, it is time to polish off your chart. An easy way to add some finishing touches is through adding special effects to your charts. Whether it’s animation or text effects, it can really add to your visual content. Done poorly, however, the results can be less than intended.
When dealing with special effects, do use simple animations. A little bit of movement will catch your audience’s attention and draw them to your chart. Animations such as wiping motions that are quick and simple are also a great way to reveal relevant data after the chart has been introduced to the audience.
Special effects can have negative outcomes on your charts though, so don’t overdo it. Constantly having large animations for every new piece of information on a graph will detract attention from your information and instead have focus drawn to bouncing texts and twirling bar graphs. Blow apart effects that are often used on pie charts also decrease their readability even further.
Don’t use 3D effects either, especially in bar graphs. By making the bars look like cubes, the tops become obscured and it is difficult to discern where the top of the data really ends. Is it the front of the cube or the back? Avoid your audience’s confusion by keeping away from 3D effects altogether.
When you have completed your chart, it is important to look at it once more to check for any errors you may have missed. This point of reflection is a great opportunity to be sure you have committed only do’s and avoided all the don’ts. By looking at the big picture, you’ll be able to identify what small parts don’t quite fit. Do all of your elements work together? Is your data readable? Is anything drawing attention away from where you want it?
Do make sure that your chart is effective as a whole by doing a squint test. Looking at you graph, squint your eyes until all of the text and numbers are blurred. Do you still understand the purpose of your graph? For instance, can you tell, based on colors and quantities, that a bar graph is comparing different units or can you see the progression of your line graph through the ups and downs? If not, identify what is getting lost and go back and emphasize it.
Once you feel everything is as it should be do ask others for their opinions. Fellow coworkers and friends can offer insights from a fresh perspective that you may have missed. The best way to make sure your chart is going to be effective in front of an audience who is seeing it for the first time is to show it to a person who has also never seen it.
Whatever changes you make, be sure you don’t sacrifice important data as you do your final edits. So long as it contributes to the overall goal of your chart, keep it. If it is not your most valuable information and you feel it is pulling attention away from where you want it, consider making it a duller color or even gray. This will push it to the background and let your real data shine through.
In brief, the do’s and don’ts to keep in mind when making charts are: