(For more resources related to this topic, see here.)
With increasing number of variables, any analysis can become challenging and any observations harder; however, Tableau simplifies the process for the designer and uses effective layouts for the reader even in multivariate analysis. Using various combinations of colors and charts, we can create compelling graphics that generate critical insights from our data. Among the charts covered in this article, facets and area charts are easier to understand and easier to create compared to bullet graphs and dual axes charts.
Facets are one of the powerful features in Tableau. Edward Tufte, a pioneer in the field of information graphics, championed these types of charts, also called grid or panel charts; he called them small multiples. These charts show the same measure(s) across various values of one or two variables for easier comparison.
Let’s use the sample file Sample – Coffee Chain (Access). Open a new worksheet and select Sample – Coffee Chain (Access) as the data source.
Once the data file is loaded on the new worksheet, perform the following steps to create a simple faceted chart:
When there is one dimension on one of the shelves, either Columns or Rows, and one measure on the other shelf, Tableau creates a univariate bar chart, but when we drop additional dimensions along with the measure, Tableau creates small charts or facets and displays univariate charts broken down by a dimension.
A company named Juice Analytics has a great blog article on the topic of small multiples. This article lists the benefits of using small multiples as well as some examples of small multiples in practice. Find this blog at http://www.juiceanalytics.com/writing/better-know-visualization-small-multiples/.
An area chart is an extension of a line chart. The area chart shows the line of the measure but fills the area below the line to emphasize on the value of the measure. A special case of area chart is a stacked area chart, which shows a line per measure and the area between the lines is filled. Tableau’s implementation of area charts uses one date variable and one or more measures.
Let’s use the sample file Sample – Superstore Sales (Excel). Open a new worksheet and select Sample – Superstore Sales (Excel) as the data source.
Once the data is loaded on the new worksheet, perform the following steps to create an area chart:
When we added Order Date for the first time, Tableau, by default, aggregated the date field by year; therefore, we added Order Date again to create aggregation by quarter of the Order Date. We also added Region to create facets on the regions that provide trends of order quantity over time.
A blog post by visually, an information graphics company, discusses the key differences between line charts and area charts. You can find this post at http://blog.visual.ly/line-vs-area-charts/.
Stephen Few, an information visualization consultant and author, designed this chart to solve some of the problems that the gauges and meters type of charts poses. Gauges, although simple to understand, take a lot of space to show only one measure. Bullet graphs are a combination of the bar graph and thermometer types of charts, and they show a measure of interest in the form of a bar graph (which is the bullet) and target variables.
Let’s use the sample file Sample – Coffee Chain (Access). Open a new worksheet and select Sample – Coffee Chain (Access) as the data source.
Once the data is loaded on the sheet, perform the following steps to create a bullet graph:
Although bullet graphs maximize the available space to show relevant information, readers require detailed explanation as to what all the components of the graphic are encoding. In this recipe, since we want to compare the budgeted sales with the actual sales, we had to swap the reference line from Sales to Budget Sales. The black bar on the graphic shows the budgeted sales and the blue bar shows the actual sales. The dark gray background color shows 60 percent of the actual sales and the lighter gray shows 80 percent of the actual sales. As we can see in this chart, blue bars crossed all the black lines, and that tells us that both the coffee types and all market regions exceeded the budgeted sales.
A blog post by Data Pig Technologies discusses some of the problems with the bullet graph. The main problem is intuitive understanding of this chart. You can read about this problem and the reply by Stephen Few at http://datapigtechnologies.com/blog/index.php/the-good-and-bad-of-bullet-graphs/.
Dual axes charts are useful to compare two similar types of measures that may have different types of measurement units, such as pounds and dollars. In this recipe, we will look at the dual axes chart.
Let’s use the same sample file, Sample – Coffee Chain (Access). Open a new worksheet and select Sample – Coffee Chain (Access) as the data source.
Once the data is loaded on the sheet, perform the following steps to create a dual axes chart:
Tableau will create two vertical axes and automatically place Sales on one dual axes charts vertical axis and Budget Sales on the other. The scales on both the vertical axes are different, however. By synchronizing the axes, we get the same scales on both axes for better comparison and accurate representation of the patterns.
Gantt charts are most commonly used in project management as these charts show various activities and tasks with the time required to complete those tasks. Gantt charts are even more useful when they show dependencies among various tasks. This type of chart is very helpful when the number of activities is low (around 20-30), otherwise the chart becomes too big to be understood easily.
Let’s use the sample file Sample – Superstore Sales (Excel). Open a new worksheet and select Sample – Superstore Sales (Excel) as the data source.
Once the data is loaded, perform the following steps to create a Gantt chart:
Representing time this way helps the reader to discern which activity took the longest amount of time. We added the Order Date field two times in the Filters pane to first filter for the year 2012 and then for the month of December. In this recipe, out of all the products shipped in December of 2012, we can easily see the red bars for the West region in the Office Supplies category is longer, suggesting that these products took the longest amount of time to ship.
Andy Kriebel, a Tableau data visualization expert, has a great example of Gantt charts using US presidential data. The following link shows the lengths of terms in office of Presidents from various parties: http://vizwiz.blogspot.com/2010/09/tableau-tip-creating-waterfall-chart.html
A heat map is a visual representation of numbers in a table or a grid such that the bigger numbers are encoded by darker colors or bigger sizes and the smaller numbers by lighter colors or smaller sizes. This type of representation makes the reader’s pattern detection from the data easier.
Let’s use the same sample file, Sample – Superstore Sales (Excel). Open a new worksheet and select Sample – Superstore Sales (Excel) as the data source.
Once the data is loaded, perform the following steps to create a heat map chart:
When we created the chart for the first time, Tableau assigned various sizes to the square boxes, but when we placed Profit as a color mark, red was used for low amounts of profit and green was used for higher amounts of profit. This made spotting of patterns very easy. Binders and Binder Accessories, shipped by Regular Air in the Central region, generated very high amounts of profit and Tables, shipped by Delivery Trucks in the East region, generated very low amounts of profit (it actually created losses for the company).
Further resources on this subject:
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