- Data Application: Visualisation
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- Topic 1: Colour Scales
- Topic 2: Map Projections
Many areas of environmental science make use of spatial data, and a good way of displaying and exploring spatial data is by showing the data on a map.
This topic discusses some of the main challenges of projecting spatial data onto a 2-dimensional image, and some of the different trade-offs you can make when choosing how to present your data.
- Topic 3: Timeseries
After considering how to visualise space, we move to discuss how to display data spread out over time. Timeseries data is very common in all areas of research, and in this topic we discuss a few different options for visualising such datasets.
- Topic 4: Using Python and Jupyter notebook
This topic focuses on some of the tools used for creating visualisations and for organising your code. We introduce one specific tool - Jupyter notebooks - and how you can use it to organise your code and analysis notes more efficiently.
- Topic 5: Interactivity
Visualisations don't have to be single images. For complex data, it is often useful to allow the user some means of interacting with the data in a visual way. This could be simply adding some way of filtering the data behind a graph, or some more complex interactions, including panning, zooming, or highlighting different aspects of a complex dataset.
In this topic, we discuss some of the concepts of interactivity and present a couple of examples to illustrate the ideas.