Looker Studio Built-In Charts

Data can be visualized using many different types of charts. Depending on the type of data to be represented and the insight to be gained, a specific chart type could be better suited than others. You looked at some common visualization types and their appropriate use in Chapter 3, Visualizing Data Effectively. Looker Studio offers a set of built-in chart types that you can use to create beautiful and meaningful dashboards. This chapter examines each of the built-in chart types using the call center dataset that we have worked with in the previous two chapters and explores how to configure them.

In this chapter, we are going to cover Looker Studio’s built-in chart types grouped under different sections. In the end, we will add some of the relevant charts to the report we have been building since Chapter 4, Google Looker Studio Overview, to create a coherent dashboard. The primary objective is to understand each built-in chart and its configuration...

Technical requirements

To follow the example chart implementations in this chapter, you need to have a Google account so that you can create reports with Looker Studio. It is recommended that you use Chrome, Safari, or Firefox as your browser. Finally, make sure Looker Studio is supported in your country (https://support.google.com/looker-studio/answer/7657679?hl=en#zippy=%2Clist-of-unsupported-countries).

You can access the Looker Studio report that includes all the built-in charts that will be explored in this chapter at https://lookerstudio.google.com/reporting/6d1bddb7-9c1f-4869-bafe-499e4d05d411/preview, which you can copy and make your own. The completed “first Looker Studio report” that presents a simple dashboard depicting key call center metrics and patterns can be found at https://lookerstudio.google.com/reporting/b198dfb0-2b0b-43fc-9da4-19fc1e7362c5/preview.

Charts in Looker Studio – an overview

Looker Studio offers different chart types to visualize data. Built-in charts are components that Looker Studio provides as part of the tool, which you can configure to visualize data. At the time of writing, there are 36 built-in chart types and variations available in Looker Studio under the categories of Table, Scorecard, Time series, Bar, Pie, Google Maps, Geo chart, Line, Area, Scatter, Pivot table, Bullet, Treemap, and Gauge.

Collectively, these chart types address most data visualization needs. If your use case requires a chart type beyond these built-in types, Looker Studio allows you to create custom visualizations using JavaScript libraries. Such custom chart types are called community visualizations. You can also use custom visualizations created by others and made available to all through Looker Studio’s Report Gallery (https://lookerstudio.google.com/gallery?category=visualization). We will explore community visualizations...

Configuring tables and pivot tables

Tables are the most basic form of representing data. They provide flexibility to display any number of data fields together. A table chart is best suited when you want to show the most granular data, a large number of fields, or multiple metrics with very different units and scales aggregated for one or more dimension fields. Table and pivot table charts in Looker Studio allow you to display metrics in three ways:

• Numbers
• Bars
• Heatmap

In this section, you will create a few tables and pivot tables using the Call Center data source and explore various configuration settings.

Table with numbers

The Call Center data source includes details of the calls made by customers from various states of the United States of America. Let’s add a table chart to the report to display multiple metrics for each state, as shown in the following screenshot:

Figure 6.2 – Table chart to visualize detailed...

Configuring bar charts

Bar charts are useful for representing one or a few metrics against one or two dimensions. Looker Studio offers different variations of bar charts, including horizontal bars, vertical bars, clustered bars, stacked bars, and 100% stacked bars. You can start with any specific variation and configure the chart appropriately to transform it into a different variation. In this section, you will learn how to configure various types of bar charts using the Call Center data source.

Columnar bar chart

In a columnar bar chart, the dimensional values are displayed along the X-axis and the metric values are displayed on the Y-axis. The following chart shows the call volume for different call topic categories. The topics are displayed in the decreasing order of corresponding call volumes:

Figure 6.12 – Bar chart showing call topic categories in the decreasing order of call volumes

Showing the states as vertical bars is appropriate here...

Configuring time series, line, and area charts

When you have ordinal data with continuous scales and want to accentuate the relationship of one value to the next, you can use a line chart, a time series chart, or an area chart. However, these three chart types are not always interchangeable. Each chart type has its particular utility and advantages. While a line chart can represent any dimension on the X-axis, a time series chart can only show a date or date and time dimension on its axis. In general, area charts support any dimension on the X-axis. However, in Looker Studio, they can only be plotted with a time-based dimension. Area charts and stacked area charts are usually used with a Breakdown dimension to represent different areas, whereas line and time series charts are effective even with a single line. In this section, we will look into each of these chart types and configure them using the Call Center data source.

Line chart

A line chart plots a line for a variable represented...

Configuring scatter charts

A scatter chart enables you to visualize a large number of data points and understand the relationship between two metrics on the X and Y axes. The points in a scatter plot represent the dimension values chosen. The coordinates of each point in the chart indicate the values of the two metrics on the axes. In this section, we will explore the key configurations of the scatter chart type using the Call Center data source.

The following scatter chart plots customer zip codes against Avg Speed of Answer and Avg Call Duration:

Figure 6.34 – Scatter chart with a trendline

You can add a trendline to the scatter chart to indicate the type and direction of the relationship between the two metrics on the axes. You can add a linear, exponential, or polynomial type of trendline based on your data.

By default, you can plot up to 1,000 points in a scatter chart. You can increase or decrease this number from the STYLE tab as per your...

Configuring pie and donut charts

Pie charts enable you to visualize data as parts of the whole. They are a good choice for depicting a few categories with largely varying proportions. In this section, we will learn how to configure pie charts and donut charts using the Call Center data source.

Looker Studio allows you to visualize up to 20 slices. However, depicting more than five slices usually wouldn’t be very useful or effective. Consider the pie chart on the left in the following figure. It represents the proportion of calls by the top 10 call reasons. The pie chart on the right provides a much better representation with fewer slices:

Figure 6.36 – A pie chart with too many slices (on the left) and a pie chart with an optimal number of slices (on the right)

The slices are automatically sorted by the decreasing order of the chart metric. If the number of dimension values is more than the number of slices configured, Looker Studio automatically...

Configuring geographical charts

Geographical charts are used to visualize location data. In this section, we will learn how to use and configure the two types of charts that Looker Studio offers to represent geographical data – Geo and Google Maps.

The geographic dimensions allowed by Looker Studio include the following:

• Continent (for example, Europe).
• Subcontinent (for example, Eastern Europe).
• Country.
• Country subdivision (1st level): States, provinces, and so on. Available only for a small number of countries (for example, the US, Canada, France, Spain, and Japan).
• Country subdivision (2nd level): US counties, French departments, Italian provinces, and so on. Available only for some countries.
• Designated Market Area: Represents media markets. Only available for the United States (for example, Seattle-Tacoma).
• City.
• Postal Code.
• Address (need to be complete for accuracy).
• Latitude, Longitude.

Note

The Subcontinent...

Configuring scorecards

With scorecard charts, you can show a single metric value as text. They are useful to display key performance metrics. In this section, we will configure a scorecard to display the Call Abandonment Rate metric. The following screenshot shows the metric value for the second quarter of 2022:

Figure 6.42 – Scorecard displaying the Call Abandonment Rate metric

You can build this scorecard as follows:

• Click on Add a chart and select the Scorecard chart type.
• In the SETUP tab, configure the following:
  • Choose Call Center as the data source.
  • Add Call Abandonment Rate as a Metric. Set the display name to Q2 Call Abandonment Rate.
  • Set Default date range to a fixed duration of April 1, 2022, to June 30, 2022. Select the Fixed option from the top drop-down and select a Start Date and End Date. Our dataset only has the data for 6 months of 2022. For any up-to-date data source, you can choose other options such as This Quarter, This...

Configuring other chart types

In this section, we will look at the last three types of built-in charts that Looker Studio offers. These are the Treemap chart, Bullet chart, and Gauge chart. Both the bullet and gauge chart types represent a single metric against an optional target value. On the other hand, a treemap chart depicts hierarchical dimension data using nested rectangles.

Treemap

A treemap chart enables you to represent a single metric for one or more dimensions. It is especially useful for displaying hierarchical data. Each dimension value is a branch represented by a rectangle whose size or area is based on the metric chosen. This rectangle or branch is further divided into multiple rectangles representing the next level dimension values and so on. Only the name of the lowest level dimension is displayed as a label in each rectangle. You can display the name of the parent dimension as the branch header by enabling this option from the STYLE tab.

You can configure...

Building your first Looker Studio report – adding charts

You created the Call Center data source in Chapter 4, Google Looker Studio Overview, and set up a report with a title and a date range control in Chapter 5, Looker Studio Report Designer. Now, it’s time to add visualizations to the report. I’ve composed the dashboard as follows using some of the charts we configured in this chapter:

Figure 6.51–Dashboard using some of the charts we configured in this chapter

Build your report by adding a different set of charts or configurations, if you like, using what you’ve learned from this chapter.

Summary

Looker Studio offers several commonly needed visualization types as built-in charts. In this chapter, we examined each of the built-in charts available in Looker Studio at the time of writing and their key configurations. You understood the purpose and use of different data and style properties to build effective visualizations using a few public datasets.

In the next chapter, we will learn about some advanced features and concepts such as data blending, parameters, creating report templates, using calculated fields, and more.