# Outliers Graph

## Intro

An Outliers graph is nearly identical to a basic Line graph but allows you to call out any points you deem to be outliers. Be aware that the line in an Outliers graph is built from X and Y coordinate pairs, *not* from date-time values as in a typical Line graph. However, you can use numbers to represent time periods. For example, in the graphic further down in this topic, the numbers in the "X-axis" column represent months in a time scale.

This chart type does *not *currently include algorithms to identify outlier points. You must identify these points yourself in the DataSet you use to power the graph. However, you can use tools such as R and Python to help you identify these outliers.

## Powering Outliers graphs

Outliers graphs require three columns or rows of data from your DataSet. Two of these contain the X and Y coordinate values for each point, as in a Scatter Plot graph. The third column contains a value of TRUE or FALSE for each coordinate pair. If the point is considered an outlier, the value should be TRUE; if it is not an outlier, the value should be FALSE. For an example, see the graphic below.

For information about value, category, and series data, see Understanding Chart Data.

In the Analyzer, you choose the columns containing the data for your Outliers graph. For more information about choosing data columns, see Applying DataSet Columns to Your Chart.

For more information about formatting charts in the Analyzer, see KPI Card Building Part 2: The Analyzer.

The following graphic shows you how the data from a typical column-based spreadsheet is converted into an Outliers graph. (For clarification purposes, the values in the "X-Axis" column represent months.)

## Customizing Outliers graphs

You can customize the appearance of an Outliers graph by editing its **Chart Properties**. For information about all chart properties, see Chart Properties.