### pearson function

The pearson function returns the Pearson coefficient between column1 and column2, evaluated within groups defined by the group parameter if required.

The pearson coefficient represents the relationship between two continuous variables.

The Pearson coefficient ranges from -1 to +1, where:

• -1 represents a negative correlation, and

• +1 represents a positive correlation.

Function and parameters

`pearson(column1, column2, group)`

Parameter

Description

column1

It identifies the first column to which you want to apply the formula. The column1 parameter is mandatory.

column2

It identifies the second column to which you want to apply the formula. The column2 parameter is mandatory.

group

It allows you to group the results by a certain column.

Example

The following example uses the Bike Sales dataset.

Description

Screenshot

• In the example here, we would like to retrieve the Pearson coefficient between the Profit and Cost attributes.

• We write the following formula:
`pearson(\$"Profit",\$"Cost")`

The value of the Pearson coefficient is 0.902, so the result is considered positive. • If we want to go further with our analysis, we can group our results by a specific attribute values.

• In the example here, we decided to group out results by the Country attribute, so the formula becomes:
`pearson(\$"Profit",\$"Cost",\$"Country")`

• The results are as follows:

• The Pearson coefficient between the Cost and Profit in Canada is 0.937;

• The Pearson coefficient between the Cost and Profit in Australia is 0.934, and so on. 