Due to the popularity of 3 Ways to Make Beautiful Bar Charts in Tableau, I’ve decided to follow it up with some ideas for making your line graphs more engaging in Tableau. Line graphs are a close second to bar charts as my favorite fundamental visualization type and are the obvious choice for evaluating trends over time. Like bar charts, the invention of line graphs is generally credited to William Playfair at the end of the 18th century. Also like bar charts, I blame their age and people’s familiarity with line graphs as the reason some data visualization enthusiasts look for “more engaging” choices. Line graphs have stood the test of time and their effectiveness cannot be denied. I’m hoping that these three approaches help cement line graphs as a top choice for your Tableau data visualizations.
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I’m excited to share the launch of my latest project: Playfair Data TV. Playfair Data TV is an online learning platform that includes Tableau video tutorials across eight tracks. At launch, there are 26 videos - totaling over 3 hours of training - spanning fundamentals, chart types, dashboards, technical features, advanced topics, and tips. New videos will be added every month following the beta period (ending 9/30/2018). We’ve invested a lot into making this the best resource it can be. Members receive exclusive access to every full-length, high-quality video tutorial as well as their own dashboard to keep track of their bookmarked lessons. Playfair Data TV offers monthly subscriptions that can be cancelled any time or lifetime memberships that will provide the member access to anything added to the platform in the future. Note that if you plan to attend one of my live training events, a lifetime membership is included with your ticket.
This is the third in a five-part series on getting the most out of text in Tableau. For future updates, subscribe to my mailing list. I’ve explained before that a spreadsheet is not a data visualization because it does not take advantage of any pre-attentive attributes that will help you make sense of the data. Alas, many stakeholders continue to ask for crosstabs (text tables), either so they can do their own manipulation to the data or just because they feel more comfortable seeing the raw numbers. Well, if I have to make crosstabs, I intend to make the best damn crosstabs the world has ever seen! That’s why for the first time, I’m letting the genie out of the bottle and sharing 3 tips for making your text tables more effective and engaging in Tableau. In this post, we’ll cover how to increase the number of columns in a Tableau crosstab, how to make your text tables as flexible as possible, thoughts on maximizing the data-ink ratio, and how to make custom table headers.
To draw a highlight table in Tableau, you need one or more dimensions and exactly one measure. This is the same criteria to draw a raw text table in Tableau, except with highlight tables, you’re limited to one measure instead of one or more measures. This one measure is what encodes the cells in the table by the preattentive attribute of color. It’s essentially a spreadsheet with colored cells. As I shared in my post, Why do you visualize data?, the highlight table is my favorite chart type for introducing the value of data visualization. I think it works well because most companies are still using spreadsheets for most of their reporting, and by converting a text table to a highlight table, the audience is forced to take advantage of the preattentive attribute of color. This kind of becomes a gateway to more complex visualizations. Highlight tables are already more engaging and effective than a text table / crosstab view, but this post aims to provide three more ways to make your highlight tables even better in Tableau.
This is the fifth and final post in a series of important data visualization lessons I learned while in grade school. Other tips include know how you’re being measured, trust your intuition, don’t jump to conclusions, and always add value. Believe it or not, I’ve never lost a game of checkers. I admit that I stopped putting my streak on the line after a couple years of playing, but I’ve never lost a game of checkers! I think the reason I was able to succeed with checkers is that I learned how to play chess first. When I was seven years old, I was lucky to have a babysitter that taught me how to play. I think the only reason I was interested in learning is because they had these one to two-foot chess pieces that I was enamored with. Having learned the game of chess a couple of years earlier, picking up checkers in third grade came very naturally. For a time, checkers was the game of choice in my third grade after-school program, and there was a rule where the “winner stayed” (or got to keep playing). Maybe I didn’t lose because I NEVER MOVED MY BACK ROW. Joking aside, I don’t remember what strategy led to my success, but I do remember that it was pretty great being a master of checkers. This is a theme I’ve attempted to carry on in my career, and I credit most of my biggest successes with a relentless dedication to the fundamentals. This post shares some examples, data that supports why this might be important to your audience, and a few tactics to consider moving forward.
According to Google’s dictionary, a mission statement is “a formal summary of the aims and values of a company, organization, or individual.” Some of these stated missions are quite broad, leaving a lot of runway to innovate while keeping track of the business’ original purpose. Consider Microsoft’s, “Our mission is to empower every person and every organization on the planet to achieve more.” Others are laser-focused on a specific product, such as Honest Tea’s, “to create and promote great-tasting, healthy, organic beverages.” For me, a great mission statement is short, incorporates primary values, and provides some direction. The most important aspect of mission statements is that they help in decision making because they remind stakeholders of the purpose at hand. The idea is that these short statements can scale to keep everybody pulling in the same direction. You’ve likely at least heard of mission statements, if not a few famous examples, but have you considered them in the context of data visualization? This post shares my data visualization mission statement and how it helps me solidify some of my opinions including why I believe data visualization is superior to spreadsheets and why I don’t use pie charts.
Thank you for reading this year. Your support means a great deal to me and keeps me more motivated than you know to keep my commitment of providing a new Tableau tutorial, data visualization strategy, or data visualization every week. I would simply not have my career in data visualization if it were not for community members helping me along the way, and I hope this series has helped in some small way. What a year it has been. The end of the year is always a time of reflection for me and I consistently have two feelings / thoughts: (1) gratefulness and (2) “How could next year possibly be better?”. This year included fifty new posts, fifteen public presentations in the US, and a Zen Master tour in Japan and Singapore. This year will once again be hard to top, but I’ve got some huge news to stay tuned for in 2018. In the meantime, please review my 10 most popular posts of the year. There is a lot of insight in here about how people are using Tableau and hopefully some useful reminders that will help you get the most out of Tableau.
This is the second in a series of five “you are here” Tableau tutorials. These tips will help improve the user experience of your Tableau dashboards by helping guide your end users. Subscribe here to receive new updates. This tutorial will illustrate how to add a highlighter to a custom date range selected by an end user. The highlighter will lay over the data points corresponding with the selected range of dates. This technique will help you and your dashboard’s users see the marks in the selected date range in context of the other marks on the view and is an easy way to enhance the design of a line graph. One of the best parts about the following approach is that it will not require you to use the dual-axis, leaving some flexibility to add even more context or aesthetic improvements to the graph. In order to highlight the data points in a custom date range, we will use a combination of Tableau parameters and reference lines.
Dual-axis combination charts, or combo charts, are named that because they have two axes and they display a combination of different mark types. For example, you can create a visualization that displays a measure with bars on one axis and another measure as lines on the second axis. This is one of my favorite chart types to use in Tableau because the ability to add a second axis, and control the axes independently of each other, unlocks some additional flexibility. This newfound flexibility creates several practical applications that can be used to improve your analysis, user experience, and design. This post will show you how to make a dual-axis combo chart in Tableau as well as three different ways to use them: (1) their traditional use (2) a method for making your end user part of the story and (3) an option for improving the aesthetics of your dashboard.
Tablueprints is a series where I share how to make my Tableau data visualizations. If you would like updates on future posts, be sure to subscribe. I will only email when I have something new to share and I will not share your email with anyone. In this tutorial, we will use my 2½ Minutes to Midnight visualization to create a waterfall chart in Tableau. A waterfall chart shows the progression toward a cumulative result by showing how positive or negative values contribute to the total. In my data visualization, the waterfall chart was an effective choice for showing how we’ve moved closer to and further from “midnight” on the Doomsday Clock since its inception in 1947. We eventually end up at, you guessed it, 2½ minutes to midnight. In a corporate environment, waterfall charts can be a great choice for showing how specific segments are contributing to your end goals and/or the makeup of the final result. In addition to the foundational waterfall chart, I’ll show you how to leverage a dual-axis to add value to this type of data visualization. In my example, the dual-axis is used to display the absolute number of minutes to midnight after each change. In a corporate setting, the second axis can be used as a nice way to show absolute changes, percent changes, or some other metric of choice. I also like that the dual-axis creates a kind of teardrop effect that helps communicate the direction of the change.