Choosing the right type of chart or graph visualization can be key to conveying the most important insights in your data—on sight. This paper will help you determine which chart is best for the type of data you're analyzing and the questions you want to answer.
But simply casting your data onto a static graph can at best answer simple questions. We'll go beyond, and teach you about combining graphs on a dashboard, adding filters, and what charts pair well together. From a horizontal bar graph to a box-and-whisker plot, you'll be slinging graphs at the speed of curiosity. The result is business insight and answers to questions at the speed of thought.
We've also pulled out the first several pages of the whitepaper for you to read. Download the PDF on the right to read the rest.
You’ve got data and you’ve got questions. Creating a chart or graph links the two, but sometimes you’re not sure which types of charts and graphs will help you find the answers you need.
This paper answers questions about how to select the best charts for the type of data you’re analyzing and the questions you want to answer. But it won’t stop there.
Stranding your data in isolated, static graphs limits the number of questions you can answer. Let your data become the centerpiece of decision making by using it to tell a story. Combine related charts. Add a map. Provide filters to dig deeper. The impact? Business insight and answers to questions at the speed of thought.
Which types of charts and graphs are right for you?
Transforming data into an effective visualization (any kind of chart or graph) is the first step towards making your data work for you. In this paper you’ll find best practice recommendations for when to create these types of visualizations:
- Scatter plot
- Heat map
- Highlight table
- Box-and-whisker plot
Making one of these visualizations should be a starting point, however, not your end goal.
Interact with your data
Once you see your data in a visualization, it inherently leads to more questions. Your bar graph reveals that sales tanked in the second quarter in the Southeast. A scatter plot shows an unexpected concentration of product defects in one category. Donations from older alumni are significantly down according to a heat map. In each example, your reaction is the same: why?
Equip yourself to answer these questions by making your visualization interactive. Doing so creates the opportunity for you and others to analyze your data visually and in real-time, letting you answer questions about your data at as quickly as you ask them.
Bar charts are one of the most common ways to visualize data. Why? It’s quick to compare information, revealing highs and lows at a glance. Bar charts are especially effective when you have numerical data that splits nicely into different categories so you can quickly see trends within your data.
When to use bar charts:
- Comparing data across categories. Examples: Volume of shirts in different sizes, website traffic by origination site, percent of spending by department.
- Include multiple bar charts on a dashboard. Helps the viewer quickly compare related information instead of flipping through a bunch of spreadsheets or slides to answer a question.
- Add color to bars for more impact. Showing revenue performance with bars is informative, but overlaying color to reveal profitability provides immediate insight.
- Use stacked bars or side-by-side bars. Displaying related data on top of or next to each other gives depth to your analysis and addresses multiple questions at once.
- Combine bar charts with maps. Set the map to act as a “filter” so when you click on different regions the corresponding bar chart is displayed.
- Put bars on both sides of an axis. Plotting both positive and negative data points along a continuous axis is an effective way to spot trends.
Line charts are right up there with bars and pies as one of the most frequently used chart types. Line charts connect individual numeric data points. The result is a simple, straightforward way to visualize a sequence of values. Their primary use is to display trends over a period of time.
When to use line charts:
- Viewing trends in data over time. Examples: stock price change over a five-year period, website page views during a month, revenue growth by quarter.
- Combine a line graph with bar charts.A bar chart indicating the volume sold per day of a given stock combined with the line graph of the corresponding stock price can provide visual queues for further investigation.
- Shade the area under lines.When you have two or more line charts, fill the space under the respective lines to create an area chart. This informs a viewer about the relative contribution that line contributes to the whole.
Pie charts should be used to show relative proportions – or percentages – of information. That’s it. Despite this narrow recommendation for when to use pies, they are made with abandon. As a result, they are the most commonly mis-used chart type.
If you are trying to compare data, leave it to bars or stacked bars. Don’t ask your viewer to translate pie wedges into relevant data or compare one pie to another. Key points from your data will be missed and the viewer has to work too hard.
Want to read more? Download the rest of the whitepaper!
Ross Perez is the Website Marketing Specialist for Tableau Software, a role which encompasses SEO, on-page optimization, analytics and project management. more
Ross Perez is the Website Marketing Specialist for Tableau Software, a role which encompasses SEO, on-page optimization, analytics and project management. A large part of his role involves using Tableau’s business intelligence software to discover and share insights that help to make the Tableau website more efficient and productive. less
Dan leads product marketing for Tableau’s business products, new product experience and online training. He has a certificate in data science and often speaks about how Tableau is advancing the world of data analytics. more
Dan leads product marketing for Tableau’s business products, new product experience and online training. He has a certificate in data science and often speaks about how Tableau is advancing the world of data analytics. Dan has a multimedia journalism background and has worked at the Financial Times and Northwestern University’s Medill News Service, as well as working with Tableau Public to build interactive data visualizations for major news publications including the Wall Street Journal, Fortune, Forbes and more. less
If a viz falls onto the web and no one sees it, did it happen? Lori likes data visualizations, but she likes them best when they get seen and used. She is happiest vizing away on Tableau Public and helping others become killer analysts. more
If a viz falls onto the web and no one sees it, did it happen? Lori likes data visualizations, but she likes them best when they get seen and used. She is happiest vizing away on Tableau Public and helping others become killer analysts. Lori’s visualizations have appeared in the Washington Post, Los Angeles Times, Guardian Data Blog and Mashable. Lori earned a Ph.D. in Epidemiology at the University of Washington, a Master’s in Public Health from the University of Illinois at Chicago, and B.A. in Biology at Northwestern University. @VisualLori less