Group dimensions are utilized in scenarios where dimension values are categorized. For instance, the age field can be segmented into minor, youth, middle-aged, and elderly groups to analyze the vaccination rates across different age brackets.
Prerequisites
You have created a dataset. For more information, see Create and Manage Datasets.
Create a group dimension
On the Data processing page, click Create Group Dimension.
You can also hover your mouse over the target field in the field outline or data preview interface, click the
icon, and select Create -> Create Group Dimension.
In the New Grouping Field dialog box, set the following configurations and then click OK.
For item ④ configuration in the following figure, see Example scenario.
NoteGroup dimensions cannot be referenced by calculated fields.
Example scenario
Categorize data by geographical location. For instance, the province field can be used to create the following regional groups:
Northeast region:
Heilongjiang,Liaoning,JilinNorth China region:
Beijing,Tianjin,Hebei,Shanxi,Inner MongoliaEast China region:
Shanghai,Jiangsu,Zhejiang,Anhui,Fujian,Jiangxi,ShandongCentral South region:
Henan,Hubei,Hunan,Guangdong,Guangxi,HainanSouthwest region:
Chongqing,Sichuan,Guizhou,Yunnan,TibetNorthwest region:
Shaanxi,Gansu,Qinghai,Ningxia,Xinjiang
After the configuration is saved, a dimension field is added to the dataset, and group names are populated in this column according to the configuration.
Group data by age. For example, you can divide the customer age field into the following age groups:
0 years old ≤ Minor <18 years old
18 years old ≤ Youth <40 years old
40 years old ≤ Middle-aged <56 years old
Elderly ≥ 56 years old
Group data by date. For example, you can group data by date field to divide activity phases.
