What are Groupings in Sigma?
Groupings in Sigma Computing allow for easy aggregation at different levels of hierarchy. This is particularly useful when analyzing data at a higher level, such as summarizing sales by region or grouping customer data by demographics.Â
Group columns in a table to compare rows of data based on shared values within a column. You can use any column in a table to define a grouping, and multiple groupings.
Note: To apply this feature, make sure you have Can Edit or Can Explore access to the workbook.
How to Apply/Add Groupings to a Table
Step 1: Open Your Sigma WorkbookÂ
Log in to Sigma: Start by logging into your Sigma account.
Open Workbook: Navigate to the workbook where you want to create groupings. If you don’t have a workbook, create a new one and import your dataset.
Step 2:Â Select the Datasource/Dataset
Choose Dataset: In your workbook, select the dataset you want to work with. This could be a table, a view, or any other data source you have connected to Sigma.
In this example, we are using
PLUGS_ELECTRONICS_HANDS_ON_LAB_DATADataset.
Step 3: Create a New Grouping
We are going to apply grouping on Product Type and Product Family.
Please refer to the arrow where Groupings columns are added in a Table.
Groupings can be added in multiple ways.
Take 1: Columns can be added by clicking on the + sign.
See the screenshot for reference.
Take 2: The Second way is to select the column and select the Group Column option from the list.
Once columns are grouped, the table will change, and you will see the –and + signs with the column headers and values, which are used to collapse and expand values in the column and hierarchy.
You can also create calculations for the grouped columns. In this example, We have created a Distinct count of orders (# of Orders) to calculate the Grouped columns Product Type and Product Family.
To create a calculated column, within the grouping, next to Calculations, select Add calculation…, then choose Order Numbers.
A calculated column is created as a Count of Orders.In the editor panel, hover over the calculated column name and click the caret (
) to open the column menu.
) to open the column menu.Select Set aggregate > CountDistinct.
The column updates to CountDistinct
This way, you can create Groupings and aggregated columns.
Table Summary in Sigma
Table summaries are like grouping calculations made at the entire data set level. These can be incredibly useful when wanting to show company-wide averages or totals.
Table Summary columns can be created for aggregating existing or new columns.
Choosing a Column: You can create a summary for an existing aggregate column or select New summary to create a custom summary with a custom formula.Â
Custom Summaries: You can create a new summary based on a formula, which can be referenced in other formulas within the workbook.Â
Grand Total: Sigma has a function to calculate the grand total of a column, such as the total number of orders.Â
Reordering Summaries: You can easily reorder the summaries by dragging and dropping them.Â
To create a New Summary column, Click on the plus icon and select New Summary
In the screenshot below, we have created a new Table Summary Column, Total Orders, which is a new Table Summary aggregated value.
In a similar way, we can aggregate the existing column as shown below. We added Total Quantities in the Table Summary by taking the existing Quantity Column from the table.
Closing
In Sigma, groups are an effective feature for combining and analyzing data, yielding more insightful findings and significant visuals. Following the detailed procedure described in this article, you can easily create and apply groups to your datasets, improving your data analysis skills.
Understanding groups in Sigma will help you realize the full potential of your data, whether you’re evaluating customer demographics, summarizing sales statistics, or investigating any other dataset.
Looking to get even more out of your Sigma experience?
Connect with the experts at phData—we’re here to help you unlock deeper insights and drive smarter decisions with your data.
