Boxplot visualization
This article applies to the following Customer Insights roles: Developer
The boxplot visualization (also known as a “box-and-whiskers” chart) is typically used to illustrate the distribution of data within a group. In turn, this is usually done by dividing that group into quartiles. For example, an ecommerce site might look at customer orders by dividing customers into four groups:
- Customers in the bottom 25% quartile (based on the combined dollar amount of all their orders).
- Customers in the 50% quartile.
- Customers in the 75% quartile.
- Customers in the top quartile.
Considering that standard approach, and considering the type of data most-commonly found in Customer Insights, the boxplot visualization might not be your “go-to” visualization for Identity Cloud reporting. However, the visualization is available to you, and could potentially have its uses. For example, the following visualization compares the number of new user accounts created in a quarter (the top line of each box) with the number of user accounts deleted in that same quarter:
As you can see, in quarter 1 there were many more accounts created than deleted (over 450,000 accounts created and less than 200,000 deleted). That contrasts sharply with the data for quarter 4, which shows almost as many accounts deleted as accounts created.
In this article:
- Customizing the Visualization
- The Series Tab
- The Style Tab
- The X Tab
- The Y Tab
Customizing the visualization
To customize the boxplot visualization, click Edit to display the parameters menu:
Each of the tabs on this menu, and each configuration option found on those tabs, is detailed in the next few sections of this documentation.
The Series tab
Configuration options that apply to the entire visualization include the following:
Color Configuration: Collection, Palette
The Collection dropdown provides a themed group of color palettes (albeit a very limited group in the case of the boxplot visualization). These palettes enable you to change the outline color of your boxes (the interior color will always be white). For example, if you select Springfield from the Collections dropdown you boxplot will recolor itself to look like this:
If you click Palette, you’ll see the one predefined palette for your collection, as well as a tab labeled Custom:
By clicking the Custom tab, you can change any of the values found on the currently selected palette. For example, here we’ve changed the orange color to red, something we can do by clicking the orange color in the palette and then entering the color name red(we could can also #FF0000, the hex code for the color red):
In turn, the boxes in the visualization are recolored accordingly:
Reverse colors
Directly beneath the palette shown on the Style tab you’ll see a checkbox labeled Reverse colors:
If you look at the palette, you’ll also see that the first square in the palette is colored orange; it’s no coincidence that orange is also the color assigned to the individual boxes:
In addition, you might have noticed that the last square in the palette is colored dark green. So what happens if you select Reverse colors? You got it: the last color in the palette (dark green) swaps places with the first color in the palette (orange). Similarly, the second color swaps places with the second-to-last color, the third color swaps places with the third-to-last color, and so on. As far as your visualization goes, the net result of all that swapping looks something like this:
The Style tab
Configuration options for the entire visualization include the following:
Show Full Field Names
When set to On the entire field name, including the name of the Explore (Event Fact), is shown in the visualization:
When set to Off, the Explore name is hidden:
The X tab
Configuration options for the X (horizontal) axis include the following:
Show Axis Name
When set to On, the name of the X axis (Event Fact Time Stamp Quarter) is displayed at the bottom of the visualization:
When set to Off, the name is hidden.
Custom Axis Name
Specifies a custom name (e.g., 2020 Quarterly Results) for the X axis:
To revert to the default axis name, simply delete the value you entered in the Custom Axis Name field.
Axis Value Labels
When set to On, value labels (such as 2020-Q2) are displayed on the X axis:
When set to Off, value labels are hidden:
Gridlines
When set to On, vertical gridlines are displayed in the visualization:
When set to Off, those vertical gridlines are hidden:
Note that you can configure this value only if Axis Value Labels is enabled. If you set Axis Value Labels to Off the Gridlines checkbox disappears.
The Y tab
Configuration options that apply to the Y (vertical) access include the following:
Show Axis Names
When set to On, the axis name (Event Fact Count Entity Creates) is displayed on the Y axis:
When set to Off, the name is not displayed.
Custom Axis Names
Specifies a custom name (e.g., Number of User Profiles Created) for the X axis:
To revert to the default axis name, simply delete the value you entered in the Custom Axis Name field.
Axis Value Labels
When set to On, value labels (e.g., 350,000) are displayed along the Y axis:
Set this value to Off to hide the labels:
Note that setting Axis Value Labels to Off also hides the horizontal gridlines.
Gridlines
When set to On, horizontal gridlines are displayed in the visualization:
When set to Off, the horizontal gridlines are hidden:
You can configure this value only if Axis Value Labels is enabled. If you set Axis Value Labels to Off the Gridlines checkbox disappears.
Minimum Values
Minimum value displayed on the Y axis. By default, the Y axis starts at 0. However, by setting a minimum value you can specify the lowest displayed number. For example, this visualization sets the minimum displayed value to 100,000 (note how the bottom of the chart is then cut off):
Maximum Values
Maximum value displayed on the Y axis. By default, the Y axis ends with the largest number in the dataset. However, by setting a maximum value you can specify the highest number to be displayed. For example, this visualization sets the maximum displayed value to 250,000 (note how the top of the chart is cut off):
Tick Density
Use the slider to control the relative number of tick marks (value labels) shown in the Y axis. Moving the slider all the way to the left removes all the tick marks:
By comparison, moving the slider all the way to the right maximizes the number of tick marks:
Y Axis Format
Specifies how numeric values are displayed along the Y axis. For example, if you want to display your value using a single decimal point, use this format:
#,###.0#
Customer Insights uses Microsoft Excel-style formatting for specifying value formats.
Updated over 2 years ago