Chapter 5. Analyze data in pivot tables

Table of Contents

5.1. About the Pivot Table app
5.2. Create a pivot table
5.2.1. Select dimension items
5.2.2. Modify pivot table layout
5.3. Change the display of your pivot table
5.4. Manage favorites
5.4.1. Open a favorite
5.4.2. Save a favorite
5.4.3. Rename a favorite
5.4.4. Write an interpretation for a favorite
5.4.5. Create a link to a favorite
5.4.6. Delete a favorite
5.4.7. View interpretations based on relative periods
5.5. Download data from a pivot table
5.5.1. Download table layout data format
5.5.2. Download plain data source format
5.5.3. Download a CSV format without rendering data in the web browser
5.6. Embed a pivot table in an external web page
5.7. Visualize pivot table data as a chart or a map
5.7.1. Open a pivot table as a chart
5.7.2. Open a pivot table selection as a chart
5.7.3. Open a pivot table as a map
5.7.4. Open a pivot table selection as a map

5.1. About the Pivot Table app

With the Pivot Table app, you can create pivot tables based on all available data dimensions in DHIS2. A pivot table is a dynamic tool for data analysis which lets you summarize and arrange data according to its dimensions. Examples of data dimensions in DHIS2 are:

  • data dimension itself (for example data elements, indicators and events)

  • periods (representing the time period for the data)

  • organisation hierarchy (representing the geographical location of the data)

From these dimensions you can freely select dimension items to include in the pivot table. You can create additional dimensions in DHIS2 with the group set functionality. This allows for different aggregation pathways, such as aggregation by "Partner" or facility type.

A pivot table can arrange data dimensions on columns, rows, and as filters. When you place a data dimension on columns, the pivot table will display one column per dimension item. If you place multiple data dimensions on columns, the pivot table displays one column for all combinations of the items in the selected dimensions. When you place a data dimension on rows, the pivot table displays one row per dimension item in a similar fashion. The dimensions you select as filters will not be included in the pivot table, but will aggregate and filter the table data based on the selected filter items.

[Tip]Constraints and tips
  • You must select at least one dimension on columns or rows.

  • You must include at least one period.

  • Data element group sets and reporting rates can't appear in the same pivot table.

  • A pivot table can't contain more than the maximum number of analytic records which have been specified in the system settings. The maximum number of records could also be constrained by the maximum RAM which is available to your browser. Consider making smaller tables instead of one table which displays all of your data elements and indicators together.

  • The Pivot Table app supports drill-down and up for periods and organisation unit. This means that you can for example drill down from yearly periods to quarters, months and weeks inside a pivot table. You can also drill down from the global organisation unit to countries, provinces and facilities.