What is data visualisation?
Data visualisation is a means of taking numerical data and making it easy to read, interpret and understand by turning it into images, graphs and diagrams.
By visualising data, we can shape it into narratives, or stories.
Who is your audience?
Before beginning your visualisation, consider who your intended audience is. This will guide your design process, so you should only include visual elements which align to that audience.
You could be making a visualisation for:
- Academics in your discipline
- Research Professionals
- Industry Professionals
- The Public
For example, visualisations for a public audience you would keep simple and clear, whereas as visualisations aimed at an academic audience may include technical language or concepts aligned to that field.
Types of data visualisations
Different types of Data Visualisations. (Image: Michelle Borkin, Harvard SEAS)
Data visualisations come in all forms and sizes, and depending on your audience and how creative you want to get, there are many options. Below are links to websites covering the various types of data visualisations.
- from Data to Viz From Data to Viz leads you to the most appropriate graph for your data.
- The Data Visualisation Catalogue A library of different information visualisation types.
- The Data Viz Project Presents all relevant data visualizations, so you can find the right one for you.
How to make data visualisations
- Excel Data Visualization: Mastering 20+ Charts and GraphsThis LinkedIn Learning course offers a practical guide to over 20 useful Excel charts and graphs for data visualisation, and provides some introductory tips to help you customize any kind of chart in Excel.
- Excel Data Analysis - Data VisualizationThis tutorial will show you how to use Excel charts and Excel formatting features on charts that enable you to present your data analysis results with emphasis.
- Power BI Essential TrainingThis LinkedIn Learning course covers the web-based Power BI service, explaining how to import data, create visualisations, and arrange those visualisations into reports, how to pin visualisations to dashboards for sharing, how to use Power BI Mobile to view and share your data, and more.
- UTS Library Getting started with data visualization and infographicsThis class was presented to staff and students at the LX Labs hosted Reshub event in Spring 2018. In the class, spreadsheet data on widget sales was manipulated into graphs and maps using Microsoft's Power BI software.
- Tableau Essential TrainingThis LinkedIn Learning course will show you how to create and manipulate data visualisations in Tableau Desktop—including highlighting tables, charts, scatter plots, histograms, maps, and dashboards—and how to share your visualisations via the web.
- Introduction to Tableau PublicIn this Library exercise, Tableau Public was used to manipulate some data on the elevations of cities and their rainfall in Spain. Tableau was used to form a union between the data point common to the cities and then graph them to see if there is any trend of rainfall rising as the altitude of the cities decreases. Finally, using the mapping function in Tableau to visualize the rainfall and altitude across Spain by using colours and icons.
- Data Visualization in R with ggplot2This LinkedIn Learning course will teach you how to create data visualisations using ggplot2, the leading visualisation package for R. The course will show you how to create basic visualisations, how to beautify those visualisations by applying different aesthetics, and how to visualise data with maps.
- Comprehensive Guide to Data Visualization in RThis article will briefly teach you how to make several visualisations from simpler ones such as histograms and box plots to more advanced ones such as mosaic maps and 3D graphs. This does require having RStudio installed and basic knowledge of R.
- Python for Data VisualizationThis LinkedIn Learning course will show you how to build accurate, engaging, and easy-to-generate charts and graphs using Python. Explore the pandas and Matplotlib libraries, and then discover how to load and clean data sets and create simple and advanced plots, including heatmaps, histograms, and subplots.
- 10 Python Data Visualization Libraries for Any Field | ModeProvides an overview of 10 different Python data visualisation libraries and tools, with links to further tutorials.
Free data visualisation software
- Tableau Academic A user-friendly data visualisation software that can accept a variety of input files. Students are eligible for a free one-year licence of Tableau Desktop. Otherwise, Tableau Public is free with some limited capabilities.
- Power BI Another free (for students) entry level data visualisation platform that can accept a variety of file type and also work with a variety of API driven sources, including Google Analytics, Survey Monkey and Facebook. Can also plug into cloud based platforms like Microsoft Azure. Currently PC only, for some reason.
- Datawrapper Can take CSV data and turn it into graphs, including bar, pie charts and maps. It can even create manipulable HTML graphs that can be embedded in web pages. Best of all it's pretty easy to use.
- RAWGraphs An open-source data visualization framework built with the goal of making the visual representation of complex data easy for everyone.
Good v Bad Visualisations
Good
- Data is beautiful 10 of the best data visualization examples ever
- 15 Data Visualizations That Will Blow Your Mind The description is in the title
Bad
- WTF Visualisations Data visualisations that make no sense
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