It turns out, Excel is actually a very useful tool for data journalism. I completed NICAR's computer assisted boot camp last week, and I emerged with a new-found appreciation for Excel. If you're a Mizzou student, I highly encourage you to take the CAR class, JOURN 4430, during a regular semester or intersession bootcamp to learn more about data reporting. For everyone else, here are five reasons Excel isn't actually the worst.
1. Excel leads to a data mindset
Data-minded reporters turn to data as a must-have source for every story. Data helps reporters add context to the talking heads of a story. Instead of simply quoting people from opposing sides of an issue, data can provide factual evidence for the reader. At the CAR bootcamp, the instructors discussed how data is useful for every story, not just huge investigative pieces. A reporter at the Seattle Times used an IRE database of bridge inspection records to add context to a breaking news story of a bridge collapse. The Times used its analysis to explain the causes of the bridge collapse, and to expose other at-risk bridges in the area. The analysis included in the day-turn story also led to a map of structurally deficient bridges a few days later. Excel is your first step to becoming a data-minded journalist.
2. Excel does the math for you
I'm sure most of you are aware of the long running joke that journalists hate math. Even if you like math, Excel can help you quickly calculate numbers using a few simple functions. For example, if you have a dataset of every professional baseball player's salary and position, a few simple Excel functions can lead you to your next story. Functions like Average, Median and Mode, can help you write a story about the average salary for baseball players in the U.S. Basic Excel functions are really simple to write, and can tell you a lot about the numbers in front of you. This tutorial is a good starting place for how to write simple math functions in Excel.
3. Filters in Excel sort relevant data
Basic filtering techniques in Excel are another quick method for finding stories in data. Math functions explain an entire dataset, while filtering can explain a smaller segment of the data. A filter tool on the baseball data shows that Zack Greinke is the highest paid baseball player in the country. You can easily turn on the filter tool by clicking the filter icon and then the drop down arrow for the column you want to sort. This simple tool can reveal all kinds of interesting things about your data.
4. Pivot tables save time in data analysis
Pivot tables are a great shortcut I learned from the CAR bootcamp. Pivot tables provide a faster way to complete math and grouping functions on your data. For example, if I wanted to see the total player salaries grouped by each baseball team on my dataset, I would normally have to sort the data by team and then complete individual functions to calculate total team salary. Pivot tables group all of this data together in one quick place. To make a pivot table on a Mac, you simply select your data using SHIFT + COMMAND, ARROW RIGHT, ARROW LEFT. Then go to DATA > PIVOT TABLE. From there, you simply drag the columns you want to show into the Row Labels field and drag the column you want to complete a function on into the Values column. If you're a visual learner like me, try a video tutorial here. Pivot tables take a few minutes to learn and will save you valuable time in your data reporting.
5. Data helps you ask the right questions
This blog post just barely scratches the surface of all of the tools and tricks you can use to analyze data. Mizzou's CAR class teaches the basics of Excel, and also dives into programming languages like SQL and Python. In some ways, Excel is just the tip of the iceberg in data reporting tools. But, even basic Excel knowledge can lead you to great stories. As the CAR instructors explained over and over this week, data is not the final answer to your story. Rather, data leads you to the questions for your story. In the baseball data example, I can easily find out the highest paid player in the country. With this piece of information in mind, I can ask about this player's skills or research the player's performance statistics. Data reporters save valuable time in an interview because they can spend their time asking questions revealed by data. There are endless tools available for data journalists, but the most important thing to remember is that data is a mindset any journalist can learn.