portal Tool user Guide:

filter dataset by attribute

This page contains information on how to filter a dataset by an attributte within the AURIN Portal


This tool allows you to keep some parts of a dataset based on their values.

For example, you may only want to keep part of the dataset where the value of Variable X is greater than 2, and exclude the remainder of the dataset

Set Up

For this worked example we use some population data across the Greater Perth area

To do this:

  • Select Greater Perth (2016) as your area
  • Select the following datasets and variables:
SA2 Aggregated Population & Dwelling Counts 2016 Census for AustraliaSA1 Code
Total Usual Resident Population 2016

If you open this table up and sort by the Total Usual Resident Population 2016 column, you will see a number of SA2s with a zero count (shown below). We will be removing these rows. Click the Inputs above tab to see how to do this.


We are now ready to filter our dataset. In this instance we will remove all SA2s that have a population of zero

To do this click the Tools button in the Analyse panel, click Data Manipulation and then Dataset Attribute. Enter your parameters as shown in the image below and click the Add and Run button. These parameters are also explained below

Dataset attribute filter tool parameters

  • Dataset Input: The dataset that you would like to run the filter over. In this instance, we are using SA2 Aggregated Population and Dwelling Counts 2016 Census for Australia
  • Attribute: The attribute that you would like to use to filter based on its values. In this instance we are using Total Usual Resident Population 2016
  • Operator: the rule for describing the data that you want to keep. In this instance, we are selecting Greater Than
  • Attribute Value: The ‘value’ for applying to the attribute. In this instance we are selecting 0.


Once you have run the tool, click on the Display button. This will open up the new dataset now shown in your Data panel named Output: geojson_filter XXX (you should rename this something meaningful). If you open the dataset and sort lowest to highest, you will note that there are no SA2s in this dataset with a zero population count