RDIM Step 2 - Manage Analyse Data Data Visualisation
Data Visualisation
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Data visualisation uses statistical graphs, plots, information graphics and other tools to create visual representations of data. The goal is to summarise and communicate data clearly, precisely and efficiently so that it might promote new insights.
There are many types of visualisations and thousands of tools available and they range greatly in complexity (e.g. from bar graphs to heat maps, networks, 3D models etc) and specificity.
The following are some of the more popular tools and training resources. Keep in mind that data visualisation tools are often used for exploratory data analysis and not just for displaying results. Some of these tools are designed to do both.
- leads you to the most appropriate graph for your data. It links to the code (R, Python, D3.js) to build it and lists common caveats you should avoid.
- is a curated collection of tools that the people behind Datavisualisation.ch recommend. View the entire list or filter by function (maps, charts, data or colour) and whether you are willing to write any code.
- is a library of different visualisation types and can be searched by function e.g. comparisons, hierarchy, processes & methods, analysing text etc) or viewed as a list. Each entry includes an example, explains how the visualisation is used and links to tools.
- 's Categories (filters) include data handling, charting, programming, multivariate, mapping, web-based, specialist and colour.