When A Picture Actually is Worth a Thousand Words: Data Visualization
If a “picture is worth a thousand words,” then why not make data more visual for business users so they can easily analyze and assimilate information? According to research, managers that make use of visual discovery tools are 10 percent more likely than their peers to access the information they need in the time necessary to impact decision making. Check out this article to see how big data visualization is worth more than a thousand line spreadsheet.
In today’s day and age journalists are relying less heavily on words to get their stories across and more on multimedia. Often times photos and videos are paired with text to paint a more thorough image for readers. Additionally, graphs, charts and maps can be great resources for journalists — if used correctly.
The world of data journalism is fairly new and only a small group of people have become masters at it. After learning about it and trying it out myself it’s not hard to see why. Working with data and graphics is much harder than simply finding statistics and writing up a piece on them. Nonetheless, using data visualization can be extremely beneficial.
After toying around for a few hours with Datawrapper and Google Fusion tables I was (by the grace of God) able to create a bar chart and a map. I began with the chart first because I knew it would be much easier.
First, I found some data on the nyc.gov website from the NYPD. The information I used for my chart was a pdf of weekly crime statistics from the prior week. The categories ranged from murder and rape to burglary, transit crimes, etc. The data I found included percent change between one year, two years, five years and 22 years.
Because there was so much raw data I knew that I had to cut back a bit. I chose to focus on only major crimes and looked at the change from 2014 to 2015 specifically.
Once I cleaned my data on my Google Excel sheet, I was able to go into data wrapper and create a bar graph. It was actually quite simple!
When creating my graph I tried to be as detailed, but brief, as possible. I think that seeing the change in the form of bars instead of reading it on a chart with multiple columns of text is a lot more effective.
After creating my chart I decided to tackle a map. Because I have never used Google Fusion Tables before it took me quite some time to figure out what I was doing. Emma Carew’s slideshow proved to be extremely useful. I don’t think I could have gotten through the map without it.
Seeing as I was having a difficult time I tried to make the map as simple as possible. I used the 2014 population estimate in the United States provided by the Census Bureau and simply focused on the least populated states.
I decided to do this after looking at the data on my Google Drive excel sheet and looking for outliers. After browsing the estimates I quickly realized that there were certain states that had a much smaller number than the rest.
North Dakota, South Dakota, Vermont and Wyoming all had less than a million people in their states. I thought this would be interesting to point out.
After toying around with the color scheme and merging my data set with a Shape zip file I was able to come up with my beautiful map and key:
Before creating this fusion table my map looked like this:
You would have to click on every single dot in order to find out the population estimate. By using Google Fusion I was able to do the work for the reader and point out my focus. (It also looks a lot cooler!)
All in all, I found this exercise to be very useful. I may not be a data journalism pro but I do know the absolute basics and can now list these skills on my resume.