Data journalism reading list

These are books I recommend on data journalism, from a reading list for a course I run on the subject. If you want to find out about when the course will run again, or about one-to-one or corporate data journalism training, there is more information here.

e-books

Paul Bradshaw, The great data journalism heist – introduction to data journalism techniques. Also available on Amazon.

Paul Bradshaw, Finding stories with spreadsheets – more advanced techniques focusing on spreadsheets.

Paul Bradshaw, Scraping for journalists, Paul Bradshaw – more advanced stuff on extracting data from webpages. Also available on Amazon.

eds Jonathan Grey, Liliana Bounegru and Lucy Chambers, The data journalism handbook – a crowd-written collection of advice and case studies on data journalism. Free online (can also be bought in print).

Print books

Jordan Ellenberg, How not to be wrong: the hidden maths of everyday life – general book on understanding mathematical concepts, including plenty of use for data journalism.

Michael Blastland and David Spiegelhalter, The Norm chronicles: stories and numbers about danger – an entertaining read on how we think about risk.

Philip Tetlock and Dan Gardner, Superforecasting: the art and science of prediction – how to make better predictions by knowing a lot about a few things and realising when you’re wrong.

Nate Silver, The signal and the noise: the art and science of prediction – an awful lot about baseball, but an interesting account of some clever techniques in prediction including Bayesian analysis.

eds Philip Cowley and Robert Ford, Sex, lies and the ballot box: 50 things you need to know about British elections – 50 political academics distil their research on politics, including lots on opinion polling.

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