Reshaping the Polar Chart

Charticulator presents you with a donut-shaped chart when you first apply the polar scaffold. However, you can now easily change the donut shape into a pie shape by dragging inward on the inner radius of the chart. If you want to increase the circumference, drag outward on the circumference, and you can also drag between the glyphs to increase the spacing between them; see Figure 13-4.

If you want to fine-tune these adjustments, you can also use the attributes of the polar plot segment where you can resize the plot segment and change the gap between categories and the spacing between glyphs.

To create an arc layout, where the plot segment starts and ends at specific angles, you can drag on the handles at the top of the chart in a circular direction, for instance, creating an angle of between 270^o and 450^o; see Figure 13-5.

To move the arc shape to the bottom of the canvas, turn on the Automatic Alignment attribute under “Origin” in the plot segment Attributes pane. You can then move the bottom guide of the canvas upward to reposition the chart in the middle of the canvas. Another approach to moving the arc into the middle of the canvas is to drag the bottom guide of the canvas below the canvas.

Creating a Pie Chart

In Figure 13-6, we have styled a very simple pie chart using Charticulator. You will notice the chart only comprises one category, the “Salespeople” field. This is because a conventional pie chart is typically used to show the percentage breakdown of a total value across a single category and works best with fewer sectors. To create this chart, all that is required is to bind a numerical field to the Width attribute of the rectangle shape and close the gap in the plot segment attributes.

The downside of using Charticulator to build standard pie charts is that displaying “detail labels” (e.g., the values or percentages as a callout) is problematic on two accounts.

Firstly, binding the “Salespeople” field to the angular axis (see the section on “Binding Fields to Polar Axes” below) would size the glyphs so they are equally spaced around the axis according to the value of the field bound to the Width attribute; see Figure 13-7.

Secondly, if you were to use a text mark anchored to the rectangle glyph to show the labels, the text mark will retain its alignment irrespective of the angle at which the glyph sits within the chart. The upshot of this is that the text marks may sometimes sit upside down. This wouldn’t happen to the detail labels on a Power BI pie chart. However, to remedy this problem, you could use a polar guide.

Using a Polar Guide

The polar guide allows you to anchor chart elements to positions either inside or outside the circular chart. Select the polar guide from the Guides dropdown on the toolbar and draw the guide onto the canvas, anchoring it to the top, bottom, and side guides of the canvas. To use the guide, anchor your text marks to the anchor points of the guide at the center of the circle. You can then drag your text marks and position them around the outside of the circle; see Figure 13-8.

Unfortunately, these text marks won’t respond to the data changing. We might conclude therefore that if we want to use a simple pie chart, we’d probably be better off building it in Power BI.

What we must do now, therefore, is to see how we can generate circular style charts that are not so easily constructed in Power BI, if at all. If we start to explore the attributes of the polar plot segment and bind fields to these attributes, we will learn how easy it is to morph the pie chart into a host of other designs. The starting point for this is to understand how the axes of the polar plot segment are used to change the design of the chart and control the layout.

Rose Chart (Angular Axis and Stack Angular)

In Figure 13-13, you can see how we can transform the default pie chart into a rose type chart. To do this, with the default stack angular sub-layout applied and the “Year” field on the angular axis, the “Sales” field has then been bound to the Height attribute of the rectangle shape.

The angular axis arranges glyphs around the axis in the same way as an x- or y-axis and that is to arrange them equally around the axis according to the value bound to the Width attribute. The result of this is that a gap will be produced for smaller values (see Figure 13-7).

Peacock Chart (Angular Axis and Stack Angular)

In Figure 13-14, we have set out the steps to create a peacock chart. Starting with the default chart, you will need to drag on the handles at the top of the plot segment to create an arc (i.e., an angle of 270^o to 450^o), and you can then bind a numerical field to the Height attribute of the rectangle. If you then change the shape of the mark to an ellipse, this will produce the peacock shape. In our example, the final step was to use the “Sales” numerical field in the Fill attribute, giving the chart a spectral gradient fill.

You will notice that we have also filtered the “Year” field to show only three years. This type of visual, like pie charts, generally works better when you have fewer categories.

Remember to turn on the Automatic Alignment attribute to move the peacock chart to the bottom of the canvas. You can then adjust the bottom guide of the plot segment to move the chart into the middle.

Nightingale Chart (Angular Axis and Stack Radial)

To create a nightingale chart, you will need to use the default angular axis but change the sub-layout to radial. It’s not until you bind a numerical field to the Height attribute of the rectangle that the chart is transformed into the nightingale chart, seen in Figure 13-15. Reducing the subcategories and closing the gap on the angular axis can result in a less cluttered chart.

Using the stack radial sub-layout, the glyphs are grouped by year and stacked in concentric layers to show values for the salespeople. The real benefit of this chart is that not only can we analyze our salespeople’s performance and see that “Charron” is doing nicely, but we can also easily see that the years 2020 and 2021 were the better years. It’s the binding of a numerical value to the Height attribute of the rectangle that gives this visual its strength.

Radial Chart #1 (Radial Axis and Stack Angular)

To explore sub-layouts that are combined with a radial axis, let’s start by designing a radial style chart that uses a stack angular sub-layout. As soon as we then bind the “Year” field to the radial axis, the glyphs are rearranged accordingly where each year is now represented by a concentric circle and the glyphs are grouped by each salesperson in sectors. If we now apply some techniques that we’ve already learned, the chart can be redesigned into an arc shape radial chart; see Figure 13-16.

In this chart, we bound a numerical field to the Width attribute of the rectangle to plot the data. However, the radial axis for the years by default sits vertically at the top of the chart. If you change the angle of the plot segment (i.e., an angle of 270^o to 450^o), this would move the axis so it sits horizontally.

You will get some more interesting layouts if you experiment with the plot segment’s horizontal and vertical alignment options or the gap and sorting options.

Radial Chart #2 (Radial Axis and Stack Radial)

The last combination of axes and sub-layouts that we will explore is when a categorical field is bound to the radial axis and then a radial sub-layout is applied. This again will generate a radial style chart but with a completely different look and feel. In Figure 13-17, starting with the default chart with a stack angular sub-layout, we can apply the “Year” field to the radial axis and change the sub-layout to stack radial. The glyphs representing each salesperson now sit in concentric circles. To plot data onto the chart, we need to bind the “Sales” field to the Width attribute of the rectangle, but it’s difficult to see what’s what in the chart at this stage. Filtering the number of salespeople showing, increasing the gap on the radial axis, and changing the shape of the glyph to an ellipse renders the chart a little more promising.

Applying the Custom Curve

You are now ready to apply the custom curve scaffold. To do this, from the Scaffolds button on the toolbar, drag the custom curve scaffold into the plot segment; see Figure 13-23.

A default curve is created for you, but you can then use the pencil button top right of the plot segment to draw any shape you want; see Figure 13-24.

The custom curve scaffold creates a custom curve plot segment that you will see in the Layers pane. You can bind data to the tangent and normal axis by using the Attributes pane.

Creating a Spiral

As part of the custom curve scaffold, you can also produce spiral type charts. To do this, start with a very simple chart that comprises a rectangle mark that has a numerical field such as “Sales” bound to the Width attribute and a categorical field such as “Regions” bound to the Fill. Then close the gap to zero in the plot segment attributes to pull the shapes together. It works best if you restrain the Height of the rectangle to a measurement, such as 30, but experiment here to see what works for you.

Now apply a custom curve scaffold, and a wavy chart is generated by default. Click the spiral button top right of the chart, and a spiral is now made; see Figure 13-25.

By default, the spiral will start at the 180^o point (i.e., at the bottom of the spiral), but you can change this in the Start Angle attribute. For instance, start the spiral at the top of the chart with the 360^o angle (Figure 13-26).

You can also specify the Windings which determines the tightness of the spiral. The bigger the number, the tighter the spiral (Figure 13-27).

I think you’ll agree that by using Charticulator’s polar and custom curve scaffolds and by combining angular and radial axes with the sub-layout options, you’ve been able to design some engaging, interesting, and unusual visuals. You now also know how to design a radar chart. It’s true that we need to be cautious in our choice of visual, and you may feel that some polar and custom curve charts are not always the best choice to do the job of reporting on your data. However, now that you know how to create pie, nightingale, and radial charts using Charticulator, at least you can make that choice for yourself.

In the next chapter, we turn our attention away from scaffolds and instead focus on the numerical data that we want to analyze in our visuals. It may not have escaped your notice that up to now, our data has mostly comprised a single numerical value, that is, the “Sales” value. This has been because designing charts that use multiple metrics often requires a completely different approach from plotting just a single numerical value against multiple categories. So let’s move forward and learn how to design visuals that can compare and contrast the metrics that matter to us.