03 August 2017 | by Matt Steele

Customize Your Visualizations Using Q

In our last post on visualizations, we looked at how easy it is to generate visualizations in Q. In that post, we outlined how you can create a table that ‘hooks up’ to a visualization to generate the output.

But you don’t need to have a separate table of data: you can paste the data into the visualization directly.

This feature is very handy for two reasons:

  • It can alleviate the need to craft the perfect table in Q.

  • It can allow you to integrate data that might not be in your main data file (e.g. sales figures, population sizes, or segments).

So this option gives you more flexibility to customize your visualizations.


How to do it?

  1. Pick your visualization from Create Menu > Charts > Visualization.

  2. On the right-hand input panel, change the drop-down menu for Data Source from Use an Existing Table to Type or Paste Data.

  3. Click the Edit Data button that appears immediately below the Data source drop-down menu.

  4. Type or paste (from Excel) your data into the blank spreadsheet that opens in Q.

  5. Click OK to close the spreadsheet, and then click the red Calculate button.

There are a few important things to keep in mind when entering data manually:

  • The first row and/or column may be used by the visualization as labels for, e.g., axes or specific data points.

  • The data that you enter should have a layout which is appropriate for the visualization. For example, a Heat Map requires a table with at least two rows and two columns, and a Labelled Bubbleplot requires four columns of data (one each for the vertical and horizontal coordinates, one for the bubble size, and one for the labels).

Here’s an example of a Bubbleplot. The following data was pieced together for all 50 US States from a variety of data sources:

Q picks up the text in the first column for the state label, the next two columns as values for the x and y-axes respectively (with the top row as their label), and the bubble size from the fourth column (using population of the state as an index to bubble size, again with its label in the top row).

This produced the following Bubbleplot.

Note: The “Voted Trump” and “Voted Hilary” colorings are actually another dimension – the “Group indices” – which were added to the input panel as per the below. The X-axis and Y-axis titles were also tweaked to include “(per 1000)”.

 

Q will flag an error if your data is not entered in a way that is readable by the visualization. Q will then advise you what you need to do to correct it. You just need to go back into Edit Data to make the necessary alterations.

Author: Matt Steele

Matt has over 14 years of experience in the marketing research arena, with a combination of research experience (qualitative and quantitative), marketing training, academic psychology (cognitive), creative leadership, geekiness and artistic flair. He currently works for Displayr (the home of Q and Displayr) and is based in London: supporting, selling, marketing and training for Q research software and associated software packages (eg: Displayr). He holds a Honours degree in Psychology from UNSW, a Grad Cert. in Marketing from UTS, and a Grad Dip in Directing from NIDA (all based in Sydney, Australia).

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