class Script and chart function

The class function assigns the first parameter to a class interval. The result is a dual value with a<=x<b as the textual value, where a and b are the upper and lower limits of the bin, and the lower bound as numeric value.

Syntax:

class(expression, interval [ , label [ , offset ]])

Return data type: dual

Arguments
Argument	Description
interval	A number that specifies the bin width.
label	An arbitrary string that can replace the 'x' in the result text.
offset	A number that can be used as offset from the default starting point of the classification. The default starting point is normally 0.

Example: Chart expressions
Example	Result
class( var,10 ) with var = 23	Returns 20<=x<30
class( var,5,'value' ) with var = 23	Returns 20<= value <25
class( var,10,'x',5 ) with var = 23	Returns 15<=x<25

Some of the examples in this topic use inline loads. For more information, see Using inline loads to load data.

Example - class fundamentals

Overview

A data table is loaded that contains names and ages. You want to classify the people by age groups (with a ten year interval) and provide a count of the number of people in each group.

Open the Data load editor and add the load script below to a new section.

The load script contains:

A dataset which is loaded into a data table called Example.
The following fields in the data table:
- Age
- Name

Load script

Example:
LOAD * INLINE [
Age, Name
25, John
42, Karen
53, Yoshi
43, Bob
27, Charles
];

Results

Load the data and open a sheet. Create two new tables.
In the first table, do the following:
1. Add these dimensions:
  - Age
  - Name
2. Create the following measure:
  - =class(Age, 10, 'age'), to classify the data into age categories.
In the second table, do the following:
1. Add this expression as a dimension
  - =class(Age, 10, 'age')
2. Create the following measure:
  - =Count(Age), to count the number of people age classification.

The first table shows the raw data for Name and Age, and which age category they are classified in.

Results table 1
Name	Age	class(Age, 10, 'age')
Bob	43	40 <= age < 50
Charles	27	20 <= age < 30
John	25	20 <= age < 30
Karen	42	40 <= age < 50
Yoshi	53	50 <= age < 60

In the second table, you can see how the data is now classified and summarized. The results of the class function created 3 age categories in the first measure. The second measure counts the number of people in each age category.

Results table 2
class(Age, 10, 'age')	Count(Age)
Totals	5
20 <= age < 30	2
40 <= age < 50	2
50 <= age < 60	1

Overview

A data table is loaded that contains names and ages. You want to add a field that classifies each person according to an age group with a ten year interval. The original source table looks like the following.

Original source table
Name	Age
John	25
Karen	42
Yoshi	53

Open the Data load editor and add the load script below to a new section.

The load script contains:

A preceding load statement that uses the class function to create a new field called Agegroup.

Load script

LOAD *,
class(Age, 10, 'age') As Agegroup;

LOAD * INLINE
[ Age, Name
25, John
42, Karen
53, Yoshi];

Results

Load the data and open a sheet. Create a new table and add these fields as dimensions:

Name
Age
Agegroup

Results table
Name	Age	Agegroup
John	25	20 <= age < 30
Karen	42	40 <= age < 50
Yoshi	53	50 <= age < 60

The new field Agegroup classifies each person by age category.

Example - class scenario

Overview

A data table is loaded that contains customer data. You want to classify customers by the number of lifetime value points earned and provide a count of the number of customers in each category.

Open the Data load editor and add the load script below to a new section.

The load script contains:

A dataset which is loaded into a data table called Example.
The following fields in the data table:
- CustomerID
- CustomerName
- LifetimeValue

Load script

Example:
Load * Inline [
CustomerID, CustomerName, LifetimeValue
1, John Doe, 12500
2, Jane Smith, 36000
3, Sam Brown, 15000
4, Lisa White, 50000
5, Tom Harris, 22000
];

Results

Load the data and open a sheet. Create two new tables.
In the first table, do the following:
1. Add these dimensions:
  - CustomerID
  - CustomerName
  - LifetimeValue
2. Create the following calculated dimension:
  - =Class(LifetimeValue, 10000, 'Lifetime Value Group'), to classify the data based on the LifetimeValue field.
In the second table, do the following:
1. Add this expression as a dimension
  - =Class(LifetimeValue, 10000, 'Lifetime Value Group')
2. Create the following measure:
  - =Count(CustomerID), to count the number of people age classification.

The first table shows the raw data that has been entered and the results of using the class function.

Results table 1
CustomerID	CustomerName	LifetimeValue	Class(LifetimeValue, 10000, 'Lifetime Value Group')
1	John Doe	12500	10000 <= Lifetime Value Group < 20000
2	Jane Smith	36000	30000 <= Lifetime Value Group < 40000
3	Sam Brown	15000	10000 <= Lifetime Value Group < 20000
4	Lisa White	50000	50000 <= Lifetime Value Group < 60000
5	Tom Harris	22000	20000 <= Lifetime Value Group < 30000

The second table shows how the data can be classified and summarized. The data is categorized into four groups using the class function, and then counted to show the number of customers in each group.

Results table 2
Class(LifetimeValue, 10000, 'Lifetime Value Group')	Count(CustomerID)
Totals	5
10000 <= Lifetime Value Group < 20000	2
20000 <= Lifetime Value Group < 30000	1
30000 <= Lifetime Value Group < 40000	1
50000 <= Lifetime Value Group < 60000	1

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class Script and chart function

Example - class fundamentals

Example - class scenario

Field

Preceding load

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