Selecting the Data

Drag all the fields you want to use in your chart from the Fields pane in Power BI into the Data bucket of the Visualizations pane as shown in Figure 1-7.

You may feel that putting all your fields into a single bucket is a rather odd thing to do, and certainly this got me puzzled too when I was new to Charticulator. In Power BI chart visuals, shouldn’t there always be a “Values” bucket for numerical fields alongside buckets such as “Axis” and “Legend” for categorical fields? You can see an example of this in Figure 1-8 that shows the Power BI visual that plots the same data.

After all, don’t all Power BI visuals group and then aggregate data? In Charticulator, there is no concept of constraining fields to behave as a “value” or a “category.” However, if this is the case, how does Charticulator know which fields are to be plotted as values and which are to categorize the data? This question will be answered when we look at Charticulator’s Fields pane (see the section on “The Fields Pane” below).

Opening Charticulator

Let’s get back to creating the chart. In the Charticulator placeholder, click the More Options button at the top right of the visual and select Edit as shown in Figure 1-9.

The Charticulator placeholder will expand to fill the Power BI canvas. Click the Create chart button, and this will open Charticulator as shown in Figure 1-10.

Designing the Chart

Now that we’ve got Charticulator open, we can start to construct the chart as shown in Figure 1-6.

Before we start piecing the chart together, just ensure the fields that will categorize your data don’t have a sigma beside their name in the Fields pane (more on this later, see the section on “The Fields Pane” below). For instance, in our data the “Year” field needs to be changed to categorical. To do this, click the sigma and select categorical, as shown in Figure 1-11.

The first step in designing any Charticulator chart is rendering the glyph. The glyph is the visual representation of your data in the chart. In our chart, the glyph will be a simple rectangle shape that represents the columns of the clustered column chart.

From the toolbar at the top, start by clicking the Marks button that shows a rectangle shape. You can then drag and drop the rectangle into the Glyph pane as shown in Figure 1-12. Note how the area into which you can drop the mark is highlighted in orange.

On the chart canvas, you will now see a rectangle for every combination of category; see Figure 1-13.

To categorize the rectangles on the x-axis, drag a categorical field from the Fields pane onto the x-axis in the chart canvas. The x-axis will highlight in orange when you’re ready to drop the field. For example, we’ve dragged the “Year” field onto the x-axis, and the rectangles are categorized into years; see Figure 1-14.

At this point, the rectangles on the chart canvas are all the same height, but their heights should reflect the values in the numerical field. Drag your numerical field, for example, the “Sales” field, from the Fields pane onto the rectangle in the Glyph pane, dropping it where it shows the “HEIGHT” line as shown in Figure 1-15. Notice again that the orange highlight indicates where you need to drop the field. The height of the rectangles now reflects the sales values.

Each rectangle on the canvas represents a subcategory. For example, in our chart, each rectangle represents a salesperson in each year. We need to color the rectangles accordingly. To do this, make sure you have clicked the rectangle in the Glyph pane. In the Attributes pane at the bottom of the screen, you will find a “Fill” attribute, under the Style group (you may need to scroll down the pane). Drag and drop your category, “Salespeople” in our case, into this attribute; see Figure 1-16.

The last step in generating our clustered column chart is to add a “value” axis on the left of the chart so we can understand the numerical values being plotted. To create the y-axis scale, you need to insert a legend. I know it sounds bizarre that a numerical y-axis is referred to as a “legend” but just stick with it for now. We’ll be exploring Charticulator’s legends in more detail in later chapters.

Click the Legend button on the top toolbar; select your numerical field, for example, “Sales”; and click Create Legend as shown in Figure 1-17. Don’t worry if the legend spills off the canvas. We can adjust this when we explore the chart canvas in our tour around the screen (see below).

You can also use this method to create a legend to explain category colors, for example, a legend for the “Salespeople” field, and this will be placed top right of the chart.

Saving the Chart in Power BI

Now click the Save button top left of Charticulator’s screen and click Back to Report at the very top left of the screen.

Congratulations! You have just created your very first Charticulator chart in Power BI. I hope it’s very similar to the one shown in Figure 1-18.

The Chart Canvas

On the left of the screen is the chart itself sitting on the chart canvas. Notice the faint gray lines, known as guides, that define the margin space. We will be looking at using guides in more detail in later chapters, but for now, if you want to change the margin space, drag on one of these guides. Other places where you can drag to manage the canvas are shown in Figure 1-20.

The rectangle zoom button bottom right of the canvas pane can be used as another means to zoom in. To use the rectangle zoom, simply drag over the area of the canvas you want to zoom in on.

You can also use the Attributes pane of the chart to make these adjustments. See the section on “The Attributes Panes” below.

The Fields Pane

This pane lists the fields you are using or want to use in your chart. If you click the ellipsis top right of the pane, a table pops out that shows the data Charticulator will use in the construction of your chart. An example of this table is shown in Figure 1-21, and you can see that it looks very similar to a Table visual in Power BI. In fact, it often helps to imagine that your Charticulator chart is built on top of a Power BI Table visual.

It’s important to understand how Charticulator views the underlying data. Nearly all Power BI chart visuals contain a “Values” bucket where the numerical fields to be aggregated are placed alongside “Axis” and “Legend” buckets that contain fields that group and categorize the data. However, with Charticulator you put all your fields into a single Data bucket. You can see this difference in Figure 1-22.

With this in mind, how is Charticulator going to treat the data? It’s not always the case that you want a numerical column to be the “value” and be summarized. For example, you wouldn’t want to sum a field that contains peoples’ ages or indeed sum the year values of our chart. Charticulator will make assumptions about your data, and you can see this from the symbol that sits beside the field name in the Fields pane. A sigma indicates a numerical field type. This can be either a numerical column in your data model or an explicit measure. These will provide the values that will be associated with numerical “attributes” of the chart and glyph (see the section on “The Attributes Panes” below). Text type fields will usually provide the categories but so do some numerical fields. You may recall that when we were creating our clustered column chart earlier, we needed to change the numerical “Year” field, so it behaved as a category. We did this by clicking the sigma in the Fields list; see Figure 1-11. You may need to make similar changes to your fields.

The thing to note here is that with Charticulator, you don’t start by dictating where the field will be placed in the chart, whether it’s on the axis, in the legend, or comprises the values. Instead, you assign it a behavior through the field type. This means that you have the freedom to choose the role a field will play in the chart, change your mind, and try out different permutations. This is what gives Charticulator its great design flexibility.

There are two more field types: ordinal and temporal. You will meet these if you use a field of a date data type or use a Power BI date hierarchy in the Fields pane. You can see in Figure 1-23 that we have used a date field called “SALEDATE” and that “SALEDATE” is a temporal type field. You can also see that you get the dates categorized by “Year,” “Month,” “Month number,” etc. If you view the underlying data, you’ll notice that you have a row for every date and therefore will have a glyph for every date in the chart. You can use the date categories instead, such as “Month” on the chart axes, but there is no ability to drill down from year to month like you can in Power BI. You will find that you don’t need to change fields to the ordinal field type as fields like “Month” will be sorted correctly on clicking Save.

If you are using a Power BI date hierarchy, all the members of the hierarchy will have a temporal field type which are best changed to categorical field types. Using just the “Year” member from a date hierarchy will be plotted in the same way as the “Year” categorical field in our example data.

One last thing to note regarding the Fields pane is that the order in which the fields are listed in the Fields pane can be important because it determines the categorization of the data. If you don’t put a categorical field on the x-axis, the first field is taken as the main category, and subsequent fields are subcategories. This is the effect of Power BI’s sort order as shown in the Options button top right of the visual. To change the order, you can use the Options button as usual, or you can simply swap the fields in the Data bucket. You can see this difference in Figure 1-24.

However, once you have selected your sort order in the Options button, rearranging the fields in the Data bucket will have no effect because the sorting is now determined by the selection in the Options button.

Glyphs and the Glyph Pane

Next up is the Glyph pane where you design your glyph. The glyph that we’re using in our chart is a rectangle shape. In fact, a glyph can comprise a variety of shapes, symbols, lines, and text marks, and we will look at building a more complex glyph in the next chapter. For the moment however, you can think that the glyph is synonymous with the rectangle shape and that will be fine. You can drag the pane around, zoom in, and use the rectangle zoom just as you can on the chart canvas; see Figure 1-25.

The glyph in the Glyph pane by default represents the values in the first row of the underlying data. In our chart, this would be the sales for salesperson “Abel” in 2017, and so the rectangle mark is colored blue and sized accordingly, as shown in Figure 1-26.

Consequently, you need to be vigilant if the first row of your data contains very small values in relation to other values or even contains zero. In this scenario, the glyph in the Glyph pane will be so small; it may not even show.

However, clicking a glyph in the chart canvas changes the glyph represented in the Glyph pane. For example, clicking the column for salesperson “Charron” in 2017 would change the glyph in the Glyph pane. See Figure 1-27.

On the chart canvas, the glyph is repeated for every row in the underlying data. For example, in our data, we have six salespeople and five years, so we get 30 glyphs in our chart, each representing the sales for each salesperson in each year.

The Layers Pane

You can see an example of elements listed in the Layers pane in Figure 1-28.

You can hide or delete each element by using the “eye” and “eraser” buttons, respectively.

The order of the elements in the pane is important because it determines the stacking or “Z” order of the elements on the canvas or in the Glyph pane. You can change the “Z” order by dragging and dropping an element to change its position in the list. This is synonymous with “send backward” or “bring forward” that you may have met in other applications.

The Attributes Panes

The Attributes panes list all the attributes of the currently selected Layer. For example, to show the attributes of the rectangle shape sitting in the Glyph pane, select “Shape1” in the Layers pane, and the Attributes pane will show the attributes for “Shape1,” as shown in Figure 1-29. You can also just click on a chart element on the canvas or in the glyph pane to show the attributes for that element.

The rectangle shape, for instance, has attributes such as Height, Width, Length, and Fill color. The chart has attributes such as Dimensions, Margins, and Background. You populate and edit these attributes to render the specific visual you require. This is why we populated the Fill attribute of “Shape1” with the “Salespeople” field to color the rectangles according to each salesperson. We will be looking more closely at the attributes of each chart and glyph element in succeeding chapters.

It’s in the Attributes panes that you can rename elements of the chart listed in the Layers pane. For example, a glyph can comprise multiple marks and symbols with different data associated with each mark or symbol. In this scenario, “Shape1” might be better renamed something like “Rectangle for Sales.” In the Attributes pane for “Shape1”, you can click into the Name attribute and rename accordingly; see Figure 1-30.

In fact, you will find that every element of a Charticulator chart can be renamed using the Attributes pane.

The Scales Pane

The Scales pane lists all Charticulator’s scales used by the chart. Scales are usually created for you, and then if required, you will need to create a legend explaining the scale. Scales in Charticulator can be challenging to understand when you’re just starting out, and we will dedicate a whole chapter to learning about them.

The problem is that you may think a scale is something that describes the magnitude of the units being used in a chart. This is not the case with Charticulator’s scales which have a much wider interpretation. In Charticulator, a scale is automatically generated when a field is associated with an attribute of a mark, symbol, or line that comprises the glyph. For example, we have associated the “Sales” field with the Height attribute of the rectangle mark, and this has generated “Scale1” with the “Shape1.Height” property in the Scales pane. We have also associated the “Salespeople” field with the Fill color attribute of the rectangle mark, and this has generated “Scale2” with the “Shape1.Fill” property. Scales would normally have a legend added to the chart to explain the scale. This is why we inserted a legend to show the values associated with the height of the rectangles and a second legend to explain the salespeople’s colors; see Figure 1-31.

We will deep dive into the subject of Charticulator’s scales and legends in Chapter 9.

This completes our tour of the Charticulator screen, and hopefully you’re now conversant with all the different panes and are comfortable finding your way around the user interface. In this chapter, you also created your first Charticulator chart and learned what a glyph is and how the scales in the Scales pane are generated. In the next chapter, we focus on the glyph and take a detailed look at its composition discovering that a glyph can comprise more than just a simple and predictable rectangle shape.