8. Creating a Ribbon Chart

Overview

The ribbon chart is a variant of the stacked column chart where each column is connected by a series of ribbons, making it useful for time series analysis. This lesson shows you how to create, format, and use a ribbon chart.

To explore more Kubicle data literacy subjects, please refer to our full library.

Summary

  1. Lesson Goal (00:18)

    The goal of this lesson is to learn how to create a ribbon chart.

  2. Building a Ribbon Chart (00:25)

    A ribbon chart is a stacked column chart where each column is connected by a series of ribbons. This makes it easier to track changes over time, and to understand the rankings within each stacked column.

    A ribbon chart is created using three main wells in the visualizations pane. The value field determines the size of the stacked columns. The legend field represents the categories in each stacked column. The axis field, which is usually time-based, represents the values on the horizontal axis.

    Notably, the values in each stacked column are ordered by size. This means that the order of fields can vary from column to column, unlike similar chart types. The ribbon chart also provides detailed tooltips, which provide information on rankings and changes over time.

  3. Formatting a Ribbon Chart (03:00)

    The ribbon chart provides various formatting options that are available in other charts, such as data labels. It also provides some options that are specific to the ribbon chart. For example, we can create space between each category in the chart. We can also adjust the transparency of the ribbons. If we make the ribbons completely transparent, then the chart will simply be a stacked column chart, where each column is ordered by the size of its categories.

  4. Using a Ribbon Chart (04:15)

    Ribbon charts are particularly useful for tracking rankings over time. This is because the ordering of each column makes it easy to understand rankings. However, a ribbon chart does not have a vertical axis, so another chart type may be more useful if you want to know the total size of each stacked column.

Transcript

In the previous lesson, we used a combo chart to combine a line chart and a column chart on a single visualization.

However, the combo chart is not the only chart type that combines a line chart and a column chart.

In this lesson, we'll learn how to create a ribbon chart.

A ribbon chart consists of a stacked column chart, where each column is connected by a series of ribbons.

It's useful when we want to track the growth of a field over time, as well as tracking ranking, within that field.

We're going to create a ribbon chart, tracking the number of companies in each region, over time.

In a previous lesson, we created an area chart of this information. Let's go to that page, select the area chart, and copy with Control + C.

We'll then return to our blank page and paste with Control + V.

We'll now change this to a ribbon chart, by selecting ribbon chart from the visualizations pane.

As we can see, the ribbon chart consists of a stacked column chart for each month in our dataset, linked by ribbons.

If we look at the field section of the visualizations pane, we can see that three fields are used to create this chart.

The value field in this case, count of company name, determines the size of the stacked columns.

The legend field, in this case, region, represents the categories in each stacked column.

Finally, the axis field, in this case, month, represents the values along the horizontal axis.

There are two notable features of the ribbon chart. First, the regions are sorted by their total number of companies at each month.

The largest region is always at the top, and the smallest region, at the bottom.

Regions can move up or down, as they become larger or smaller.

For example, we can see that the south region has the most companies from January to March. However, the northeast region, becomes the largest in April, and moves to the top of the stacked column.

This differs from previous charts we've seen, where the same order is maintained every month.

Second, the ribbon chart has detailed tooltips.

If we mouse over one of the ribbons, we can see the values for the relevant region on either side of the ribbon, the growth between these two months, and the ranking for the two months on either side of the ribbon.

These tooltips can make it easy to understand trends and ranking changes over time.

Let's now consider some of the formatting options for the ribbon chart.

First, we'll open the formatting section of the visualizations pane, and add, data labels.

We'll also increase the font size of these labels to 12.

Next, we'll open the ribbons' menu.

This allows us to change the formatting of the ribbons.

The spacing option allows us to create some space between each region.

If we increase this to 10, we can see this creates a clear gap between each region in the column.

The transparency option, allows us to define how clear or solid, the ribbons can be.

The transparency can range from zero to 100.

If we set the transparency to 100, we see the ribbons become completely clear.

This can be useful if you want to create a stacked column chart, where the columns are always sorted by size.

Let's return the transparency to 30, so we can see the ribbons again.

The ribbon chart is particularly useful, when we want to track rankings over time.

If we return to our area chart from several lessons ago, it's not easy to tell which region has the most customers.

By contrast, if we look at the ribbon chart, it's much easier to see which regions have the most customers, because the column for each month, has the largest regions on top.

However, the area chart can be more useful in some situations.

The ribbon chart has no vertical axis. So it can be difficult to determine the total number of companies in any given month.

By contrast, the area chart does have a vertical axis, which makes it easier to count the total number of companies in a month.

We've now seen all the major Power BI charts, they use bars, columns, or lines.

In the next lesson, we'll look at how to filter data in our charts with slicers.

Dashboards and Visualizations
Introduction to Visualizations in Power BI