Skip to main content

​
1. Feature overview

In DingTalk Spreadsheet, go to Menu > Insert > Pivot Table to turn unstructured data into a pivot table with simple drag-and-drop. Easily perform category summaries, multi-dimensional analysis, and cross-tabulation.

​
2. Steps

​
1. Prepare the data source for analysis

First, prepare the data you want to analyze. It can be a data export from your backend system or records you entered manually. Make sure that:
  1. The first row of the data source contains no blank cells.
  2. The data source includes at least 2 rows.
  3. The data source contains no merged cells.

​
2. Insert a pivot table

Select any area within your prepared data source, then go to Insert > Pivot Table through one of the following entry points:
  1. Top-left menu > Insert > Pivot Table.
  2. Toolbar > Pivot Table.
The Create Pivot Table dialog appears. You can:
  1. Confirm the data source: Spreadsheet automatically detects the data range you may want to analyze. You can adjust it manually.
  2. Select the location to insert the pivot table: either the current worksheet or a new worksheet. We generally recommend a new worksheet.
  3. Click Confirm to display an empty pivot table along with the configuration panel on the right.

​
3. Get to know the pivot table interface

Before configuring, get familiar with the pivot table interface:
  1. Placeholder on the left: the default display area for the pivot table. Before the pivot table is generated, this area shows a black-and-white placeholder image.
  2. Configuration menu on the right:
    1. Field list: fields from the data source are automatically extracted and displayed here, ready for category summaries.
    2. Pivot table areas: drag fields from the field list into the corresponding areas to generate the pivot table results.

​
4. Configure the pivot table

Let’s walk through a real-world example to show you how to configure a pivot table for cross-tabulation analysis: This is the sales details table of a digital brand across stores in different regions. The owner wants to:
  1. View the total sales of each product by region.
  2. View the total individual sales of the salesperson “Xiao Ding”.
Here is a universal analysis framework. Every pivot table analysis comes down to 3 questions:
  1. What data do you want to analyze? — Add the field to the Values area of the pivot table.
  2. By which dimensions do you want to analyze? — Add the field to the Rows/Columns area of the pivot table.
  3. By what type do you want to filter? — Add the field to the Filters area of the pivot table.
Based on the owner’s requirements:
  1. What data to analyze: sales amount, which corresponds to the Amount field in the data source.
  2. Which dimensions to analyze by: different regions (the Region field) and different products (the Product Name field).
  3. What type to filter by: “Xiao Ding” belongs to the Salesperson field.
Next, simply:
  1. Add Amount to the Values area of the pivot table.
  2. Add Product Name and Region to the Rows/Columns area of the pivot table. Whether to place them in rows or columns depends entirely on visual clarity; generally, we add them to the Rows area.
  3. Add Salesperson to the Filters area.
You will then quickly get the summary results.

​
5. Filter and sort the pivot table

You can filter and sort the generated pivot table. When sorting, you can also choose the sort basis.

​
6. Refresh the pivot table

When the data source is updated or modified, you need to refresh the pivot table. DingTalk Spreadsheet supports both manual and automatic refresh. Manual refresh is enabled by default.
Back to DingTalk Spreadsheet