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A scatter plot consists of a 2D representation of one variable along the Y-axis, compared to another variable along the X-axis. The third component, the condition variable, is not required, but can be used to reveal additional information in the scatter plots.

The resulting view is usually called a scatter-plot given the dispersed appearance of the data. A scatter plot can be used with both numerical and symbolic variables.

To launch the scatter plot editor, select Visualize > Scatter Plot from the menu. Alternatively, click the icon () in the sidebar and then add New.

Create a Scatter Plot

The parameters for a scatter plot are defined on two tabs at the top of the page: Data and Properties.

On the Properties tab:

Select a Record set from the list.
Select from the Variable list to set variables for X and for Y, and one for C (Condition), if required.

Find a Variable

Variables are listed alphabetically. To find a variable, use the scroll bar or enter the name in the Variable field.

On the Advanced tab:

Enter a chart Title.
Enter Font Size, if required.
Select Legend Position. The Default position is on the left-corner of the graph. You can also have the option of have no legend (None).
Enter a Generalization level. For more information, see Generalization level.
Select Show statistics to display standard deviations and average values. A bell curve displays corresponding to the theoretical normal (Gaussian) distribution using the mean (average) and standard deviation of the selected record set.
Select Show Linear Regression. It is the simplest form of regression. The data is modeled as a linear combination of input variables to create an output predictive model. The model searches a line (y=ax+b) that fits best the data. The task is to find coefficients (weights) to provide the best fit to the training data. The value of the coefficient quantifies the strength of the relation between the output and the different inputs.
Select a Plot type from the drop down list (Values versus Density plot):
1. The Values option is a cartesian coordinate graph type (X-Y plot) displaying two or three variables (third variable can be displayed if a condition (cond.) is designated).
2. Density plot type is selected, the third variable is replaced by a value representing the density or number of data points per value range.
Enter Conditional Class Count, if required, use the arrow buttons, default 3.The number of buckets for the condition or number of discretized groups for a conditional variable added as color coding to Histograms and Scatter Plots. For more information, see Conditional class count.
Select the X Temporal Units to display a numerical date value as a date on the X axis select the relevant date format. All files uploaded since DATAmaestro 4.0 will have dates converted to Unix time (ms).
Define zoom area using X axis, Y axis. Enter values for X and Y axis. If X axis is a time variable then select a date in the calendar.
Click Save to load the data.

Change number buckets

To change the number of buckets for the Condition, use Class Count.

Control the View

Use the control menu below the chart to modify the zoom, apply rulers to create new record sets. For more information, see Control Menu.

Switch X-Y

Click on Switch X-Y button to switch x an y axis.

Copy/Save Scatter plot

To copy or save the curve click on the curve with the right click and select Copy image or Save image as.

How to confirm if two variables are correlated?

A scatter plot can show you how two variables are correlated. For example, two variables can be put on either axis and the scatter plot can show the degree of correlation (not causation) between them. Correlations may be positive (rising, dots slope from lower left to upper right), negative (falling, dots slope from upper left to lower right) and none (uncorrelated).

Example Visualization

The following example illustrates the weekly average electrical consumption (kWh) by year.

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