Create a pie chart

The Pie chart (also called Pictogram or Pictorial Chart) displays relative proportions of multiple classes (categories) of data.

  1. When to use a pie chart?
  2. Create a pie chart
  3. Configure the pie chart
  4. Example

When to use a pie chart?

The Pie chart is useful to  compare different categories. 

It allows to see clearly the  composition of the dataset as each slice represents the portion of the dataset that fits a category.

It can only be used if the sum of the individual parts (categories/slices)  add up to a meaningful whole (entire dataset).

If you need to compare more categorizations/dimensions, maybe a bar chart would be a better idea (article here)

Create a pie chart

To create a pie chart:

  • Click "Analytics" in the main menu (left)
  • Click the + sign
  • To create the new analytics report, you must:
    • Enter a name
    • Select a dataset
    • Select an output type (in this case: Pie chart)
    • Click Save
  • A draft data visualization will be displayed
  • Configure your report:
    • Click the "Toolbox icon" to open the configuration panel
    • Configure the chart to fit your needs
    • Click "Generate" see the result
  • Click "Save" to save the report
  • If you open this pie chart in the future, it will be updated to reflect newly added data. So if you need to keep the report that reflects the current data, you must export it.

Configure the pie chart

In the configuration panel of the pie chart, you will see the following parameters:

Parameter Details Example or Link
Calculation method Allows to select the calculation that will be applied (Average, Sum, Count, etc.) For more details, you can read the "Calculation methods" article.
Field If the labels are displayed, you will see the proportion of the slice Example: The dataset has 15 rows. 3 of them are in category A. Then if this box is checked, it will display "20%" instead of displaying "3" in the slice representing category A.
Parts/colors Field (categories) that will be compared  (this could be gender/region/budget line, etc.)
Distinct values Allows to count items only once and avoid duplicates Example: a participant could have attended multiple activities of the same type. If you need to count participations only once per attendee/type, then you need to select the Attendee field as a distinct value.

For more details, you can read the "Distinct count" article.
Position of labels Allow to specify if you want to display the values on the chart. Hide, inside or outside.
Dropdown lists: use predefined colors Allows to colors slices using the colors attributed to each category. Otherwise, colors will be attributed randomly For more details, you can read the "Manage system lists" article.
Filters Allows to filter out part of the dataset This is optional.


In this example, we want to see the proportion of male vs female beneficiaries.

This example uses the "Beneficiaries" (form) dataset.

Parameter Chosen option for the parameter
Calculation method Count
Display the value as a percentage Checked (yes) 
Parts/colors Gender
Distinct values not applicable - empty
Position of labels Inside
Dropdown lists: use predefined colors Checked (yes)
Filters Project = the project for which we want that information