portal Tool user Guide:

Merge Aggregated datasets

This page contains information on how to merge aggregated datasets within the AURIN Portal

Introduction

Similar to the Tabular Inner Join, the Merge Aggregated Datasets tool allows you to join together datasets of the same geographical aggregation (and in the same place!) to allow you to compare and investigate the relationship between the two (or more) datasets. In this tool, if one row in a table does not have a corresponding row in the other table, it will be empty on that side in the output table (compare with Tabular Inner Join, where rows which do not have corresponding entries are excluded entirely). Merging tables allows us to continue with other processes such as scatterplot, which rely on variables being in the same dataset.

Set Up

For this worked example we will investigate the relationship between housing stress and socio-economic status across Melbourne

To do this:

  • Select Greater Melbourne (2016) as your area
  • Select the following datasets and variables:
DatasetVariables
SA2 SEIFA 2016 - The Index of Relative Socio-economic Advantage and Disadvantage (IRSAD)A2 9-digit code 2016
SA2 Name 2016
IRSAD Score
NATSEM - Social and Economic Indicators - Synthetic Estimates SA2 2016SA2 Code
SA2 Name
Housing Stress (30/40 rule)

Once you have added these datasets, you are ready to merge your datasets – click the Inputs tab above to see how to do this

Merge Inputs

We are now ready to merge our datasets

To do this click the Tools button in the Analyse panel, click Data Manipulation and then Merge Aggregated Datasets. Enter your parameters as shown in the image below and click the Add and Run button



 

Merge Outputs

Once the tool has run, a pop up box will appear asking you to display your results (shown below). Click Display to open the output table. You will see that there has been an entirely new table created (also shown below), which has connected each row (SA2s in Greater Melbourne).  You should now rename this datasets to something meaningful and easy to recognise



 

Scatterplot Inputs

We are now ready to create a scatterplot of our two variables

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



  • Dataset Input: For this we want to select our merged dataset: SEIFA + Housing Stress
  • VariablesFor this we need to select the following variables in the order of X and then Y. In this case we want to put IRSAD Score as the X (horizontal) variable and Housing Stress (30/40 rule) as the Y (vertical) variable
  • Use Variable TitlesDetermines whether we want the human readable name (titles) or computer readable name (names). Always tick this box
  • Chart Title: Here we enter the title for the plot. In this instance we have chosen SEIFA IRSAD Score vs Percentage of Households in Housing Stress
  • Grid: Select this if you want to choose gridlines for your graph
  • GreyscaleSelect this if you want your graph to be in grey scale, rather than in the default colour

Scatterplot Outputs

Once the tool has run, a pop up box will appear asking you to display your results (shown below). Click Display to open the output image. You will now see a scatterplot which shows the relationship between the IRSAD score (x axis) and the percentage of households in housing stress (y axis). You can see that as the IRSAD score increases (that is, as advantage increases) the percentage of households in housing stress decreases). You can right click on this image and export it as a .png image for inclusion in a report or document.