Tutorials & links
OxShef
OxShef: dataviz provides
- advice on how to select the most appropriate charts for your data and how to avoid common mistakes when visualising data.
- dedicated websites to how to build visualisations with specific tools
- dedicated websites for a wide range of different visualisation hosting services
Dataviz.shef tutorials
Dataviz.shef provides tutorials on
- Visualising data on the web with Python and Dash
- Linking visualisations in ORDA to data
- Citing data for which you have created visualisations
Web
Dataviz tools maintain a resource of tools, tutorials and information to assist with data visualisation.
Books
The University Library keeps a number of reference quality books in the collection as a guide to producing high quality, informative graphics.
- The visual display of quantatitive information, Edward Tufte
- Information is beautiful, David McCandless;
- Beautiful visualization : [looking at data through the eyes of experts] / edited by Julie Steele and Noah Iliinsky.
Python Libraries
- Python Graph Gallery
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Matplotlib is a publication quality 2d plotting library, they provide resources and documentation
- Nicolas P. Rougier has a helpful introduction to the library.
- effective matplotlib also provides useful commentary.
- Seaborn is a plotting library for statistical work, often found alongside scikit learn or pandas.
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Bokeh is a python library for generating, and publishing interactive visualisations.
- Full Stack Python maintains a helpful list resources for discovering the Bokeh library.
R Libraries
- ggplot Is a high quality plotting library for R The ggplot developers recommend the following books, available from the library:
Hosting and Publishing Visualisations
- Jupyter notebooks are self contained documents for writing, executing and publishing analysis. the resulting document is html easily shared and made interactive with other technologies referenced here.
- Shiny Allow users to publish small analysis online
- Shinyapps.io provide a platform for publishing apps, and documentation / resources are available for learning about the product.
- Plotly enable generation of plots with the option to publish the visualisations online.
Javascript
- D3.js is an underlying technology for many of the browser based visualisations. To further expand on the plotting abilities, or generate custom interactions we recommed considering this library.
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Leaflet.js is a javascript library for generating interactive maps with customisable overlays and map tiles. R-leaflet packages are available.
- Mapbox, a provider of mapping tile sets, have a number of resources to help you use leaflet.