Classify Cases from Dataset - Map and Group

This feature is available in NVivo Pro and Plus editions. Learn more

This dialog box is displayed when you click the Map and Group button to:

Map attribute values from a dataset to new or existing attributes in your project.
Group numeric attribute values—for example, you might group ages into age ranges (18-30, 31-49 and so on).

Refer to Using the Classify Cases from Dataset Wizard for information about launching this dialog.

Options on this dialog

Column This displays the attribute you have selected to map or group. You cannot change the attribute—to select another attribute, you must click OK or Cancel to return to the Wizard.

On the Mapping tab:

Select Existing attribute to map an attribute from the dataset to an existing attribute—for example, you could map occupation to the existing attribute employment. Select the existing attribute from the list—only attributes for the selected classification are displayed. You select the classification in Step 1 of the Classify Cases from Dataset Wizard.
Select New attribute to map an attribute from the dataset to a new attribute in the selected classification. You can define the name, data type, decimal places and default value for the new attribute.

On the Grouping tab:

Select Each unique value to update or create attribute values based on each unique value defined in the dataset.
Select Values grouped by if you want the values for the selected attribute to be grouped—for example, you might group individual ages into age ranges. You can select:

Grouping	Description
Equal Interval	The difference between the minimum and maximum values in each group is equal. For example, if your survey has respondents aged between 18 and 61, you can use this option to create four groups of equal interval: 18-28 (11 values) 29-39 (11 values) 40-50 (11 values) 51-61 (11 values) If the values cannot be equally divided, then NVivo adjusts the grouping to make the intervals as equal as possible.
Standard Deviation	The values are grouped based on how they vary from the average value (mean). For example, if the average age of your respondents is 30 (with a standard deviation of 9), then you could use this option to create the following groups: 18-20 (up to two standard deviations below average) 21-29 (up to one standard deviation below average) 30-38 (up to one standard deviation above average) 39-47 (up to two standard deviations above average) 48-56 (up to three standard deviations above average) 57-61 (more than three standard deviations above average)
User-defined Interval	Select this option, if you want to create your own groupings and specify the start and end values for each group

If you select Equal Interval, you can:

Adjust the Start and End values, to create groups that cover values outside the range of values in your dataset. For example, if you are grouping survey respondents by age, and have values between 18 and 59, you can set the start value to 16 and the end value to 65, to create age groups to cover anyone aged 16-65. This could be useful if you later get responses from younger or older respondents
Adjust the number of groups that will be created.
Click Calculate to show your groupings in the groups preview area. You can change the names of the groups by entering your preferred names in the Name column. If you are not satisfied with the groupings, change the settings and then click Calculate again.

If you select Standard Deviation, you can:

Adjust the number of groups that will be created, by changing the Group range.
Click Calculate to show your groupings in the groups preview area. You can change the names of the groups by entering your preferred names in the Name column. If you are not satisfied with the groupings, change the settings and then click Calculate again.

If you select User-defined Interval, you can create your own groupings and specify the start and end values for each group:

To create a group, specify the Start and End values of the group, and then click Add to add the group into the groups preview area.
You can change the names of the groups by entering your preferred names in the Name column in the preview area.
You must create groups that cover the range of values in the column you are using.
You can optionally create groups that cover values outside the range of values in your dataset column. For example, if you are grouping respondents by age, and have values between 18 and 59, you can set the start value to 16 and the end value to 65, to create age groups to cover anyone aged 16-65. This could be useful if you expect to get responses from older respondents in the future.
You can remove a group from the groups preview area, by clicking Remove.