2. Bar and Column Charts

Overview

Bar and column charts are found in almost every Power BI report. In this lesson, we’ll look at the variants of these charts, including stacked, clustered and 100% stacked bar and column charts.

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Summary

  1. Lesson Goal (00:10)

    The goal of this lesson is to learn about the different types of bar and column chart available in Power BI.

  2. Bar and Column Charts (00:16)

    Bar and column charts are among the most common chart types in Power BI. They are generally used to display numeric data, such as sales revenue for various regions. A bar chart displays data in a series of horizontal bars, while a column chart displays data using a series of vertical columns. The length of each bar or column is based on the value of the relevant field, such as sales revenue.

  3. Stacked and Clustered Charts (01:09)

    Stacked and clustered bar charts are used when you want to divide each bar using a field in the data set. We create these charts by adding a field to the legend well of a bar chart. Here we divide our sales revenue by sales person. A stacked bar chart divides the bar for each region into segments for each sales person, stacking the segments on top of each other. By contrast, a clustered bar chart creates a separate bar for each sales person, and clusters all the bars for each region together.

    Stacked column charts and clustered column charts are also available, and work according to the same principles as the stacked and clustered bar charts.

    A stacked bar chart is generally useful when you are interested in the total value of each bar, while a clustered bar chart is better if you want to compare the different values of the legend field. However, both charts can be difficult to read if there are too many legend values.

  4. 100% Stacked Charts (02:30)

    A 100% stacked bar chart is a type of bar chart that can be used when you add a legend to a bar chart. This chart is similar to the stacked bar chart, except the length of each bar is identical. As a result, this chart lets us analyze the proportion of each bar that is accounted for by each legend value. The 100% stacked bar chart is of interest when we are interested in the proportion of data falling in a specific legend value, and less interested in specific numbers.

    A 100% stacked column chart is also available, which works according to the same principles as the 100% stacked bar chart.

Transcript

Bar and column charts are among the simplest and most common charts you'll use in your reports. In this lesson, we'll explore the various types of bar and column charts available in Power BI. Our data set includes detailed address information for each company and assigns each company to a region and sub-region. Let's say we want to compare revenue by region.

We'll drag the revenue field to the canvas.

Then drag region on top to create a column chart. We can see that the Northwest and South regions have the highest revenue followed by Midwest with a West region some way behind.

This chart displays our data as a series of vertical columns.

Let's switch from a column to a bar chart by clicking the clustered bar chart icon in the visualizations pane. The chart now displays our data as a series of horizontal bars. The various types of bar and column charts can be found at the top row of the visualizations pane.

If we hover the mouse over the chart types, we can see that we've been using a clustered bar chart and column chart. We also have the option of a stacked bar or column chart. If we select a stacked bar chart, we see that the visual does not actually change. To illustrate the difference between the cluster and stack charts, we'll add the 'Sales Person' field to our chart as a legend.

The legend separates our value, in this case revenue, by the specified field. We can see that each bar has been split into segments for each sales person.

The segments are stacked together to form the bar we saw previously hence the name stacked bar chart.

This specific stack chart allows us to see how much each sales person is selling in each region. If we switched to a clustered bar chart, we see that each sales person has their own individual bar and each of these bars is clustered together for each region.

The stacked bar chart is more useful if you want to compare total sales for each region while the clustered chart is better if your aim is to compare the performance of individual sales people. However, since we have 15 sales people both of these charts are a little bit too difficult to read.

Let's remove the 'Sales Person' legend by selecting the X in the legend well. The final bar and column chart option is the 100% stacked chart. Let's imagine we now want to see which sub-regions provide the most revenue in each region. We'll create a new chart dragging revenue and region to the canvas.

This time, we'll change our chart type to 100% stacked bar chart. We'll also add 'Sub-region' as a legend.

In this chart, each region is a constant length while each sub-region shows the revenue generated as a percentage of the larger region category.

For example, about 75% of the revenue in the Northeast region comes from the Mid-Atlantic sub-region with the remainder coming from the New England sub-region. The 100% stacked bar chart is useful when we're interested in the proportion of data falling into a specific category rather than the top line number.

Note that a smaller number of categories in each bar makes it easier to read and derive insight from this chart. These clustered, stacked, and 100% stacked charts cover the full range of bar and column charts in Power BI.

In the next lesson, we'll move forward and examine the formatting options available for our charts.

Dashboards and Visualizations
Introduction to Visualizations in Power BI