One spreadsheet can tell many stories. You just have to know the right questions to ask.

Based on a decade of training journalists and working with news organisations on data-driven stories, Finding Stories In Spreadsheets outlines the techniques for asking the right questions of data using tools like Excel and Google spreadsheets.

These aren't just questions about numbers: you'll find out how spreadsheet techniques can help you find the 'needle in the haystack' in text data. You'll learn how to clean up and modify your data so that you can ask it different questions, or get it ready for maps or charts, how to create new data from raw materials, and how to combine datasets to look for connections and trends.

With regular examples from journalism and real life data to work with, Finding Stories In Spreadsheets is *full* of those questions, in the language that spreadsheets understand. 

Cover image concept by @CarolineBeavon. Illustration by Matt Buck at Drawnalism.

Scraping - getting a computer to capture information from online sources - is one of the most powerful techniques for data-savvy journalists who want to get to the story first, or find exclusives that no one else has spotted. Faster than FOI and more detailed than advanced search techniques, scraping also allows you to grab data that organisations would rather you didn’t have - and put it into a form that allows you to get answers.

Scraping for Journalists introduces you to a range of scraping techniques - from very simple scraping techniques which are no more complicated than a spreadsheet formula, to more complex challenges such as scraping databases or hundreds of documents. At every stage you'll see results - but you'll also be building towards more ambitious and powerful tools.

You’ll be scraping within 5 minutes of reading the first chapter - but more importantly you'll be learning key principles and techniques for dealing with scraping problems.

Unlike general books about programming languages, everything in this book has a direct application for journalism, and each principle of programming is related to their application in scraping for newsgathering. And unlike standalone guides and blog posts that cover particular tools or techniques, this book aims to give you skills that you can apply in new situations and with new tools.

Data journalism is a key skill for journalists to differentiate themselves in a world where almost anyone can publish, and competition for journalism jobs is fierce.

Whether it's hard stories from government spending and MPs' expenses, or softer stories from sports data, fashion trends or music and social activity, our increasingly digital world is providing a rich range of potential new story sources - and new forms of storytelling too.

This short ebook introduces you quickly to key techniques in finding that data and turning it into stories - through a 'Data Journalism Heist'.

This isn't about the huge investigative projects that you hear about, but the everyday stories that you can do with speed and simplicity. It's about getting in, getting the data, and getting the story out safely. No one gets hurt.

In the process you'll learn about:

• Sources of data - where to find data stories and leads
• Typical data stories - how to find simple stories in data
• Basic spreadsheet techniques - finding the biggest and smallest values; calculating averages and totals.
• Top techniques for getting stories against a deadline - using filters and pivot tables to get to the story quickly
• Making a clean getaway - avoiding mistakes in data journalism
• Telling the story - basic techniques in visualising and humanising your data-led story

As the book is published you'll receive regular updates as you build on previous skills towards the final story. User feedback, examples and ideas will be incorporated as they come in.