Learn Data Journalism
In a world that is increasingly driven by data, reporters who have learned data journalism skills have the power to shine the light of public attention on important stories. Great data journalism can help readers understand climate change, follow politics, or grasp the grim realities of drone warfare — just to name a few examples.
Even if you don't aspire to be a "data journalist" or create immersive, interactive pieces like those linked above, being able to acquire, analyze, and visualize data can help you find stories you'd otherwise miss, and it can help you add important context and perspective to the stories you're already reporting.
And even if you have no experience with programming or statistics, learning data journalism isn't as difficult as you might think!
Big Picture: What You Need to Learn Data Journalism
To become an adept data journalist, you'll need to learn some programming and some statistics. Let's look at each of these in a little more detail:
- Programming: Python and R are the two most commonly-used languages in data science, and either will work for data journalism. If you're not sure which to learn, we would suggest Python, as your Python skills will transfer more smoothly into other sorts of programming (like building web apps).
- Statistics: You don't need a Math PhD, but you will need to learn a little statistics to do more advanced types of analyses.
Learning some design for data journalism may also be helpful, particularly if your outlet doesn't have staff designers that can help you create attractive visualizations for your data.
How Hard is Learning Data Journalism?
Learning data skills is like learning any sort of skill — it takes both time and dedication. But you might be surprised by how quickly you can get from "zero" to being able to build your own data science projects and apply your data skills to your reporting.
Here's a personal story that highlights three major mistakes to avoid in your learning journey. If you approach things in the right way, we think you'll be surprised with how fast you progress, and how more you enjoy the process!
Below, we've outlined a logical course sequence with three steps. The first step is doable in less than a month, and will give you enough skill to start doing data projects that can actually impact your work.
Learn Interactively with Dataquest
This series of courses can take you from zero experience to working with data quickly and smoothly using our interactive courses, and some relevant tutorial articles.
To enroll in our courses, you'll need to sign up for a free Dataquest account. You may also want to bookmark this page so you can quickly refer to the relevant courses and tutorials.
Even working full-time and studying just a few hours per week, you could be using your new data skills to find and report real stories in less than a month!
Quick Start: Skills For Writing Basic Data Stories
Work through these courses and tutorials and you'll have the skills you need to start collecting original data sets and writing cool data stories.
Estimated time: less than 1 month.
Going Further: Building Data Expertise
Take your data skills to the next level and become a true master of uncovering stories using data science!
Estimated time: less than 3 months.
Next Level: Becoming a Data Journalist
Learn the skills you need to become a data journalist and get data-specific journalism jobs.
Estimated time: less than 3 months.
Learn Data Journalism the Right Way
Before you dive into learning to code, there are a couple of things to keep in mind that will prove tremendously valuable for learning data journalism regardless of the platform you choose to learn with. Follow these two rules and you're much more likely to meet your goals:
First, stay motivated by building projects. It's hard for anyone to stay engaged when they're learning rote programming syntax with no context for how it might apply to their life. In Dataquest courses, you'll start working with real-world data immediately to help keep things engaging, but the sooner you can apply your new skills to the projects you care about, the better.
Second, apply what you're learning! If you learn on Dataquest, you'll be doing this naturally because our platform challenges you to write code constantly and checks your work from right inside your browser. But if you're using a different learning platform, like a video-lecture-based course, do not skip the step of trying to apply what you've learned for yourself. It's easy to watch a video and think you've understood the lecture, only to realize a week or two later that you don't know it well enough to apply it in your own work.
Dataquest's interactive learning platform makes it easy to do both of these things. Commit to learning data journalism by subscribing to our Premium plan today and get access to 100% of our course content!
Here are some other links and learning materials you'll probably find helpful in your journey to learn data journalism:
- ProPublica's Collaborative Journalism Guide - Lots of helpful things here!
- Anaconda - We recommend Anaconda and specifically Jupyter Notebooks for data science work in Python, it makes getting Python and the various packages you'll want installed on your system much easier, and allows you to work with and present code and visualizations in a way that's more intuitive. Check out some of our tips and tricks for Jupyter Notebooks, too.
- Dataquest's R Path - This page is focused on Python, but if you'd prefer to learn R, that's also a great choice for data journalism and following our R path from the beginning will cover everything you need to get up and running. (If you choose to learn R, also check out R Studio rather than Anaconda.)
- Hacks/Hackers - An organization with real-world meetups and events for people interested in learning data journalism
- Awesome Public Datasets - A massive list of public data sets you can use for stories or just to work on practice projects. (Most local and national governments also have dedicated open data portals you can browse).
- Free Data Sets for Projects - If you're looking to practice a specific skill, we've curated a list of data sources with data that works well for specific project types.