Tables display data in a structured format consisting of rows and columns, allowing for detailed information presentation.
You can use tables when you want to display multiple metrics and categories at the same time. For example, going back to the top 2019 movies dataset, tables are a good option for viewing the top 10 movies along with their revenue, release date, and main genre. While tables are less visual, they allow you to present more data at once compared to many other chart types, where the information might become too cluttered and difficult to read.

1. Example
Let’s create the table with movies that I just described. First, we need to add a new chart, in this case, a table. You can see how to add charts in Looker Studio in the post about the topic.
Once it’s added, within Set-up, you need to select English Title, Release Date, and Top Genre 1 as the table dimensions, and Revenue as the metric.

2. Specific Customisation Options for the Chart
Tables offer many customisation options. One of these, which is also available in other charts, is choosing how to sort the columns. To do this, go to Sort under Set-up. In this case, we’ll select Revenue and sort in descending order, so the table shows the top movies by revenue from highest to lowest.

You can also limit the number of rows displayed per page. The default is 100, but you can change it to 10 if you are mainly interested in the top 10. It’s recommended to avoid displaying too many rows per page (you can choose up to 50,000) because the more you show, the longer the table will take to load.
If you enable Summary Row, the table will display a row with the totals for each metric.

In Style, you can remove the column showing the row numbers and choose to show or hide pagination. We’ll deactivate the row numbers but leave pagination as it appears by default.

Another customisation option, and one of my favorites, is the ability to add bars or heatmaps to your metric columns. This option is under Style, where you can adjust how the information is presented for each column. For this example, we’ll select a Heat map for the Revenue column and enable Compact numbers.

Now, the Revenue metric is represented as a heat map in our table.

Do you like representing data with tables, or do you usually prefer more visual charts?