Kelly Kaufhold, Data Journalism

Live meeting Friday, July 24, 3 p.m. (watch for the Zoom link by email and our #datajournalism Slack channel).

Agenda for our live Zoom session Friday, July 24, at 3 p.m. (if you haven’t completed the online assignment for the week, please see that below)

  • Help me build an interactive Google Map
  • A quick look at data scraping
  • A bit deeper into Google Flourish
  • Q&A and practice with: Pivot Tables; Google Maps; Google Flourish; & Google Trends

Lets build your Restaurants and Bars Map

https://www.google.com/maps/d/

https://docs.google.com/spreadsheets/d/1TTniZ55–OTKqIGoCZu9y3wg4LSSRTIAMvAOI-AmaHI/edit?usp=sharing

A quick data scrape…

Here’s a link to that AEJMC/ICA jobs data which you can experiment with to make both Regions and Points layers with in Flourish.

=== Original lecture for the Week of July 17 ===

Hi, everybody, and welcome back to another week of Data Journalism! You learned in my online lecture from spring a bit about the origins, types and application of data in shaping and telling stories. This week, we’ll be much more practical, focusing on skills and tools that you can practice then teach your students starting this fall.

I’m going to introduce you to four data tools this week, all of which are free and all of which can be used to make data visualizations:

1) Pivot Tables within Microsoft Excel;

2) Google Maps;

3) Google Flourish;

4) Google Trends.

I’ll also share the datasets that I use in my demonstrations this week and you’re welcome to use that data in your future classes, or you can (and should) find your own data and experiment with it using these tools. I’ll also show you some pitfalls where you might get stuck the first time you use these, and suggest some solutions. I want you to practice these tools this week before we meet, then we’ll troubleshoot and practice some more during our Friday session in person.

Let’s start with Pivot Tables in Excel. I already taught you in the spring online lecture about sorting data to isolate one variable – like age or dollar amounts – to simplify what a dataset is telling you. Pivot Tables let you compare two, or three, or four variables at once.

Imagine you had a substantial dataset on military spending from the annual Pentagon budget. You might want to sort that by dollar amount by contractor (Boeing vs. General Electric vs. Lockheed Martin); or by state, or city, or Congressional district. In Pivot Tables, you could bunch up variables and sort data by state, contractor and dollar amount at the same time.

I have a detailed tutorial video entirely about Excel Pivot Tables and I use these three datasets:

1) Beth Potter’s data on immigration, which she uploaded on the #datajournalism Slack Channel;

2) Lourdes Cueva Chacon’s data on shootings in the U.S., also from Slack;

3) A dataset on Major League Baseball salaries I got from an Investigative Reporters and Editors training session a few years ago.

I’d suggest you download the datasets, open Excel, then follow along. Be prepared to pause or even repeat parts of the video:

  • Try to repeat what I do with each dataset in Pivot;
  • Try to find some new relationship that you can share with us on Slack or in person.

My second and third tutorials are in video #2: Google Maps and Google Flourish. I’ll use a fourth dataset for this one, a super simple 2-column list I compiled from an article I read of the percentage of bee population loss from one year to the next.

Google maintains a host of open-source files including in Google Maps. You can go to this Google Developer link, click the Menu icon in the upper left and Create a New Map. I’ll show you in the video how to upload an Excel to add a layer of data to make an interactive map.

https://www.google.com/maps/d/

Also, here’s the link to Google’s Flourish Studio tool, a free online resource that lets you quickly make interactive data visualizations like animated bar graphs, pie charts, maps and much more.

https://flourish.studio/

My third and final video tutorial is short and sweet – it introduces you to Google Trends, including how you can find trends from our collective Google search Data; sort and modify the data by date, location and more; then share it interactively on social media or on your own website – or even download the data. You won’t need a dataset for this tutorial (you may actually create one yourself!) but you should go experiment a bit on Google Trends.

https://trends.google.com/

One last assignment: We’ll start Friday with a quick, fun application of your data to an instant visualization – you’re going to help me build an interactive map. My students love this and it’s a great way to demystify “data visualization” by showing them how easy it can be. I want you to go to this link of a Sheet in my Google Drive and enter data in 3 columns:

1) The name of your favorite restaurant or bar, anywhere in the U.S.; 2) The address (but you MUST follow Google’s precise address parameters, including abbreviating St., Ave, Dr., etc. – it’s best to just copy the address from Google Maps and I’ve put a few of our favorite places at the top as an example); 3) Whether it’s a Restaurant or Bar. You’ll help me turn your data into an interactive map Friday at 3!

This Friday, July 24, at 3 p.m., we’ll meet and I’ll do some more quick demos of these techniques and help you troubleshoot and answer questions. Feel free to send questions before our meeting on Slack #datajournalism. See you soon!