Edit a Pizza Chart

This article is intended to walk a user through the process of editing a Pizza chart. If you have not done so already, please read through:

Create a New Chart

to create the blank Pizza chart which we’ll learn how to customize and alter in this article.

The menu on the left gives a series of drop-down menus to begin segmenting your data in the visualization. The choices in the drop-down menus correspond to the columns in your spreadsheet.

For example, when using this spreadsheet:

Here are the options available in the drop-down menus:

Now we can start manipulating our visualization!

The first two drop-down menus are titled SLICE and RING. These are your two options to manipulate the arrangement of data points on the pizza:

You might have noticed the pizza actually moved a bit to the left in the image above, compared to the prior two. This was done by click-and-dragging on the slice or ring lines. You can also click-and-drag the data points, the slice labels, and the legend.

Once you make a selection of a spreadsheet column from a drop-down menu, the different values in that column appear, with selected blue check-boxes. You can move these around by simply click-and-dragging the word, which alters the order of the regions in the chart. You can also uncheck certain boxes to filter out certain data.

Next up are the COLOR and TOPPING options. Both of these alter the appearance of your data points, but not their arrangement on the chart.

The COLOR option comes with default values for the colors. However, these can either be altered two different ways. One is by clicking on the color square, bringing up the color selector tool:

The other is by manually entering a comma separated list of hex color codes:

The last thing we’ll add to our visualization is data labels. There are two options: LABEL and SUBLABEL.

Note these can be manually manipulated by the displace, rotate, and size options.

There is one remaining option at our disposal: FILTER. Filtering our data won’t change the relative placement or appearance of any data points, but instead will remove data we’d like to filter out.