How to Automatically Combine Categories - By Value – Displayr Help

This article describes how to automatically combine categories together. For example, the number of SMS messages sent in a typical week combined into percentiles.

Requirements

A data set loaded into a Displayr document

Method

There are four different methods available for combining numeric values in this tool:

Tidy categories divides the range of values into tidy categories, which are intervals of 2, 5, 10, 20, 50, and so on.
Percentiles divides the range up into percentiles. This is useful when you want to create categories which contain even proportions of the cases in your data.
Equally spaced categories divides the range of values into categories that all have the same range. This is similar to Tidy categories, but has additional options for customization.
Custom categories divides the range of values up into ranges of your choice. This is useful when you want to specify uneven ranges of values.

Automatically Combine Categories into Percentiles

Let's say you want to compute percentiles for the variable How many SMS sent in a typical week. Ensure that the variable you use is numeric.

Click on the variable from the Data Sets tree.
From the Anything menu, select Data > Variables > New > Ready-Made-New-Variables > Automatically Combine Categories> By Value > Percentiles.
Select the options you want. In this example, we will take the defaults.

A new variable will be added to your Data Sets tree with a preview of what the variable will look like after the categories are combined. If the variable doesn't look right, for instance maybe the category boundary is not what you expected, you can still make changes as long as the options dialog is visible.
Displayr will automatically assign each value to a percentile.
Drag the new variable onto the page.
The results are as follows:

Automatically Combine Categories into Equally Spaced Categories

Let's say you want to compute equally spaced categories for the variable How many SMS sent in a typical week. Ensure that the variable you use is numeric. This time we will use the variable hover method instead of the Anything menu

Click the to the right of the variable from the Data Sets tree.
From the menu, select Ready-Made-New-Variables > Automatically Combine Categories> By Value > Equally Spaced Categories.
Select the options you want. In this example, we change the Number of categories to 3. The default is 2.

A new variable will be added to your Data Sets tree.
The results are as follows:

Automatically Divide Categories into Tidy Categories

Click the to the right of the variable from the Data Sets tree.
From the menu, select Ready-Made-New-Variables > Automatically Combine Categories> By Value > Equally Spaced Categories.
Select the options you want. In this example, we changed the Number of categories to 3 and the Label style to Inequality notation.

A new variable will be added to your Data Sets tree
Drag the new variable onto the page.
The results are as follows:

Automatically Combine Categories into Custom Categories

Click the to the right of the variable from the Data Sets tree.
From the menu, select Ready-Made-New-Variables > Automatically Combine Categories> By Value > Custom Categories.
Select the options you want. In this example, we changed the Cut points to 0,25,50,100 (comma separated) and the Category boundary to Start of range.

A new variable will be added to your Data Sets tree
Drag the new variable on the page.
The results are as follows:

Options

The settings that are available for Automatically Combine Categories - By Value change depending on which method you choose, and whether the input data are categorical. Settings that are available for all methods are shown first, and method-specific settings are shown below.

Variable(s) Choose which variable(s) are being used to create new categories.

Use numbers found in category labels This option will only appear if there are any categorical variables selected in Variable(s). When this is ticked, the tool will try to identify numeric values from the data labels and use those values when forming categories. If this is not ticked, the tool will ignore the category labels and will instead use the underlying data values for each category. Labels contain This option will also only appear if there are any categorical variables selected in Variable(s). This option allows you to communicate the nature of the values in the labels:

Single values This causes the tool to assume that your labels always contain single values. Any labels which contain more than one numeric value will not be combined.

Ranges of values This causes the tool to assume your data labels describe ranges of values. The tool will expect to find pairs of labels, with the exception of the lowest and highest values in the range.

Method The method to be used to identify ranges of values to use for creating new categories. The different methods are described above.

Category boundary Whether the value at the start of each range is included in the new category or the value at the end of each range is included in the new category. For example, if dividing the interval up into ranges of 10, do we create a category which is 10 to 19 (Start of range) or 11 to 20 (End of range).

Label style Determine the style of the labels for the new categories.

Tidy labels describes the range of values that is contained within each range in English. For example, 10 to 20.
Inequality notation describes the range of values that is contained within each range using greater-than and less-than symbols. For example, 10 to <21.
Interval notation describes the range of values using interval notation. For example, [10, 20) describes a range of values which include the value 10 and range up to 20 but does not include the value of 20. Similarly, (10, 20] describes a range which does not include 10 but includes all values greater than 10, up to and include the value of 20.

Use open-ended labels When ticked, this setting produces open-ended category labels at the start and end of the range. For example, an open ended label would be Less than 10, whereas a non-open-ended label would be 0 to 9

Number prefix / Number suffix Allows you to add text before and after the numeric value in each new label. For example, you may wish to add a dollar sign or other currency symbol in front of each number in the new labels. This is not available if using Ranges of values, where the text to place before and after is drawn from the original category labels.

Decimals in label Choose the number of decimals that are displayed in the new category labels.

Decimals symbol / Thousands symbol These options are only available when there are categorical variables selected in Variable(s). They allow you to communicate the number format of the data labels. For example, the number convention in the United States and other countries is to use periods to denote the position for decimal values, and commas to separate units of thousands, resulting in numbers of the form 10,000.50. In other countries, the convention is reversed, so that the same value may be represented by 10.000,00.

Tidy categories

Target Number of categories This option allows you to specify how many categories should be created when using the Tidy categories option. Note that the Tidy categories algorithm always tries to make ranges of values which are intervals of 2, 5, 10, 20, 50, etc, and so it will not always be able to achieve the desired number of categories. For more control, you can try using the Equally spaced categories method instead.

Percentiles

Percentages This option allows you to control how categories are created when using the Percentiles method. You can enter a single number here, to divide the range up into even percentiles. For example, entering 10 will create the 10, 20, 30, etc percentiles. Alternatively, if you don't want even percentiles, you can enter a comma-separated list of percentiles. For example, you can enter 50, 75, 85, 90, 95, 99, 100 to create these uneven percentiles.

Equally spaced categories

Number of categories Specify how many categories will be created. Alternatively, rather than dividing the range into a set number of categories, you can set the Increment option to divide the range into categories that have a set width.

Start point / End point Use these options to determine where you want the range to start and end. This range will then be divided up according to the Number of categories setting, or the Increment setting.

Increment Use this option if you want to specify how wide each interval should be instead of specifying how many categories you wish to create.

Custom categories

Cut points Use this field to specify which values should define the new categories.

Always include highest and lowest values When this option is ticked, the entire range of values will always be included in the set of categories even if the highest and lowest values are not entered in Cut points. Turning this option off will result in missing values for any numeric values which fall outside the range of values specified in Cut points. This is useful if you want to exclude values which are too low or too high (e.g. outliers, respondents providing unrealistically high or low values in a survey).

Ranges of values

Number of categories Specify how many categories will be created. When the input data are categorical, and the category labels contain ranges, this tool will combine adjacent ranges into this many categories.

Start of range / End of range Many examples of range categories, like Age or Income questions from surveys, contain ranges that are open-ended at the start and end of the range. For example, an Age question may start with 18 years or younger and end with 65 years and older. If combining such range categories into Equally spaced categories, the algorithm does not how the start and end points for the range of values. These fields allow you to communicate values to use as the highest and lowest in the range. For example, if you conduct a survey, and the youngest respondents who were allowed to complete the survey were 13 years old, entering 13 in Start of range would have the effect of converting 18 years or younger to 13 to 18 from the perspective of finding ranges of values in this algorithm.