Sites to help you become a data vis pro
Interested in data journalism, data visualisation and analysis and want to go further than using spreadsheets? We have compiled a list of the best places you can visit to learn how to code and then use your coding skills to create incredible visualisations.
Many data journalists use data visualisation to convey statistical information. This can take the form of tables, graphs, maps and infographics. In recent years, sites, such as Datawrapper, have made creating data visualisations easier by allowing you to turn data collated in spreadsheets into high quality visualisations. However, coding languages, like R for example, can have an advantage over using spreadsheets as it’s designed to be used to handle larger data sets, to be reproducible, and to create more detailed visualisations.
Python and R are the most commonly used languages for data analysis and visualisation.
So, here are some places you visit to get you started:
Codecademy is perhaps one of the most popular and well-known places to learn coding. Codecademy offer courses in Python and R but also a wide array of other coding languages that will help you get to grips with the basics. It’s easy to use and displays the results as you’re coding. It offers a specific course on how to “Visualise Data in Python”.
2. DataCamp
DataCamp is very similar to Codecademy as it also offers a wide array of languages to learn using interactive challenges. DataCamp is more geared towards data science. If you’re particularly interested in R, then DataCamp is probably better suited to you. Codecademy only offers 2 courses on R but DataCamp offers a multiple courses in R, including several courses on data visualisation in R.
A blog set up by City alumnus Rob Grant, R for Journalists is a “resource for journalists and other interested people to see what you can do in R”. The website really demonstrates the potential R has and once you’ve got to grips with R, the website offers the full code for various projects that you can experiment with. Take a look at this post: Which Arsenal and Tottenham Hotspur players follow each other on Twitter?
4. Guided Python Data Visualisation Projects on Coursera
Similarly to R for Journalists, the guided data visualisation projects on Coursera offer the chance to apply what you’ve learnt in Python.
5. Git Hub
GitHub is a hosting site where developers and programmers can upload the code they create and work together to improve it.
GitHub also functions as a sort of social media site for developers and programmers. Their work is published publicly and anyone can view it and propose improvements. Like 3 and 4, you can use the published code to experiment with and learn from. A good page to look at is the BBC Shared Data Unit’s code where they publish a lot of the code that they use for their visualisations. Also take a look at the BBC Visual and Data Journalism cookbook for R graphics, that guides you through and provides the code for how to create various types of charts and graphs in R.
Conclusion
Leaning coding can be difficult and applying it even more so but constant practice and experimentation will help you become better at creating amazing visualisations. If you’re struggling, it might be good chance to reach out to data journalists you like to help you out (this might also help get your name out there).
This article was originally published on Interhacktives, a website for student journalists at City, University of London.
