There are multiple ways to visualize your data, but sometimes you’re not sure which chart is the right one to use. We’ll give you an overview of the different types of charts and graphs available to you for communicating data effectively and how to select the right one.
Data is only valuable if you know how to visualize and tell a good story with it.
Before creating a chart it is important to identify the reasons why you need one. From understanding information quickly, to finding patterns or presenting insights and trends to others there are different goals for your data visualization. If you’re getting started creating charts think first about the message you want to share with your audience.
According with Dr. Andre Abella, charts can be grouped in four main types based on what you want to highlight with your data:
Comparison charts are used to compare one or value sets and easily highlight the lowest and highest values in the data. An example would be the product sales by region or over time.
Composition charts are used to show the relative value of a part to the whole or how a total value can be divided into small parts, like how many visitors came to your website via search engines, social media or direct traffic.
Relationship charts are used to show a connection or correlation between two or more variables like a correlation between advertising spending and sales.
Distribution charts are used to show how variables are distributed over time and help you identify outliers and trends like number of users by age group.
While your data might technically work with multiple chart types, you need to pick the one that ensures your message is clear, accurate, and concise. Ask yourself how many variables do you want to show in a single chart, how many data points you want to display and if you want to show it over a period of time or among items / categories.
Line chart, bar, and column charts can represent change over time, pyramids and pie charts show parts-of-a-whole, and scatter plots and treemaps are nice if you have a lot of data.
Tables displays data in rows and columns. Tables make it easy to compare pairs of related values or to display qualitative information (e.g. quarterly sales over several years).
There are multiple reasons you might select a table over a graph, as the right way to visualize your data.
A line chart reveals trends or change over time. Line charts can be used to show relationships within a continuous data set, and can be applied to a wide variety of categories, including daily number of visitors to a site or variations in stock prices.
Best practices for creating line charts:
Clearly label your axes - Make sure the viewer knows what they are evaluating.
Remove distracting chart elements - Grids, varying colors, and bulky legends can distract the viewer from quickly seeing the overall trend.
The pie chart is one of the most used and hated chart types of all times. Pie charts are used to show parts of a whole. A pie chart represents numbers in percentages, and the total sum of all the divided segments equals 100 percent.
Best practices for creating pie charts:
Make sure your segments add up to 100 - Sounds obvious, but this is a common mistake.
Column charts and bar charts are used to compare different items, or show a comparison of items over time. Bars on a column chart are vertical while bars on a bar chart are horizontal. Bar charts are generally used to help avoid clutter when one data label is long or if you have more than 10 items to compare. They are mostly used to display and compare discrete categories of data and are easy to understand and to create.
Best practices for creating bar and column charts:
Treemaps show parts of a whole. They display hierarchical information as a cluster of rectangles varying in size and color, depending on their data value. The size of each rectangle represents a quantity, while the color can represent a number value or a category.
Treemaps allow you to view trends and make comparisons quickly – especially if one color is particularly prominent. While spreadsheets can show multiple rows of data, treemaps can accommodate hundreds of thousands of items in one organized display, making it easy to spot patterns in seconds. Plus, if made correctly, they make very efficient use of space.
Best practices for creating a Treemap
With a dual axis chart you are essentially combining multiple charts and adding a second y-axis for comparison. Some members of the data visualization community are skeptical about the use of dual axis charts because they can often be confusing, poorly designed, and misleading to the viewer.
Let’s go over the different types of dual axis charts and the best ways to use them:
Column and Line Chart– This dual axis chart combines a column chart with a line chart.
Dual Line Chart – This dual axis chart compares two line charts. There can be more than two lines if need be.
Dual Column Chart– This dual axis column chart shows two sets of data displayed side by side.
Multiple Axes Chart – This displays the most complex version of the dual axis chart. Here you see three sets of data – with three y-axes.
Area charts are a lot like line charts, with a few subtle differences. They can both show change over time, overall trends, and continuity across a dataset. But, while area charts may function the same way as line charts, the space between the line and axis is filled in, indicating volume.
Best practices for creating Area charts
Make it easy to read - Avoid occlusion. This happens when one or more layers covers important information on the chart.
Use a stacked area chart - If you have multiple data sets and want to emphasize part-to-whole relationships.
Use area charts to look at the bigger picture - Take population for example: Line charts are good for showing net change in population over time, while area charts are good for showing the total population over time.
Avoid comparing too many datasets. Use instead a line chart, its cleaner.
Give the proper context with appropriate labels and legends.
Pyramid charts (triangle chart or triangle diagram) are a fun way to visualize foundation based relationships. ey appear in the form of a triangle that has been divided into horizontal sections with categories labeled according to their hierarchy. They can be oriented up or down depending on the relationships they represent. The stacked layers can also show the order of steps in a particular process.
Best practices for creating Pyramid Charts
Pick a topic and clearly label your subcategories - Decide what information you want to convey with your pyramid and clearly label your layers.
Organize your subcategories - Decide the order and value of each section on your pyramid.
Organize the subcategories based on their hierarchy.
Be consistent - Keep the spacing of your sections even and pick a pleasing color palette.
Keep subcategories to a minimum. Adding many layers and colors can make your pyramid hard to read.
Word clouds (also known as tag clouds) are a type of weighted list. Word clouds display text in varying font sizes, weight, or colors to show frequencies or categories. They can be arranged alphabetically or at random. They help people identify trends and patterns that might have been difficult to see otherwise.
Best practices for creating a Word Cloud
Provide context - Word clouds are visually eye-catching and provide information about frequency but they often don't give the viewer any context.
Use word clouds to show frequency - Avoid using them to display complex topics like the budget or healthcare crisis.
Watch your word length - Longer words take up more space and can be misleading.
Word clouds are great for filtering and analyzing data.
Avoid making your words too similar in size or color.