In the world of data visualization, maps are not just tools; they are storytellers that transform complex datasets into compelling narratives. Among the various types of maps, choropleth maps, symbol maps, and locator maps each have unique characteristics and applications. Knowing when and how to use these maps can significantly enhance the clarity and impact of your data presentations. Here’s a casual dive into how these map types can be your best friends in visual storytelling.
For this blog I used three different datasets to tell three different stories; US airport delays in 2023, EV shares by country in 2023, and EV Drive Distances from Kulpsville. Additionally, I used the Datawrapper tool to visualize each of the datasets. Let’s look a little closer.
Choropleth Maps
First up is the choropleth map. These are the go-to for thematic mapping. They use color gradients to represent data values across predefined regions, such as states or countries. This makes them perfect for displaying data like voting results or unemployment rates. The key is to use these maps for data that is aggregated over geographic areas (Monmonier, 1991). However, beware of their limitations: larger regions can dominate the visual field, skewing perception. To counter this, use rates or per capita figures instead of absolute numbers (Datawrapper, 2021). As I learned with Datawrapper, it’s crucial to know the story you want to tell and ensure your dataset is clean before selecting this map type.
For this story, I wanted to answer the question Which Airport in 2023 had the most weather delays? Before I could start for any of the maps, the process was the same; clean the data. That is, remove duplicates, unnecessary columns and/or rows that didn’t help tell the story. This dataset was challenging because there were over 10,000 rows of data just for the year 2023. The data was broken down by month, airport, airport name, and so on. Additionally, I had over 304 rows which were not recognized by Datawrapper. This meant going back into the dataset and filtering until I identified those 304 rows. It turns out it was airports outside the contiguous 48 states. Once this was fixed I was able to produce the Choropleth map below.
Symbol Maps
Symbol maps, or proportional symbol maps, are all about pinpoint precision. They use symbols of varying sizes to represent data values at specific locations, making them ideal for showing quantitative data like city populations or earthquake magnitudes. Unlike choropleth maps, symbol maps can display two variables at once—size and color—offering a richer data story (Cairo, 2016). These maps shine when your data is tied to specific points rather than areas, helping to highlight patterns or outliers with ease (Datawrapper, 2021). Remember, refining the data until your story is clear but not misinterpreted is key.
Next up was my dataset to help show which country had the largest percentage of EV shares across the world. This dataset was challenging too. There were two factors adding to the challenge. The first issue I ran into, after cleaning the data was that Datawrapper threw errors. Datawrapper couldn't use the percentage of new electric cars raw data because some were in decimal value and other values were whole numbers. For example, Chile and South Africa were in decimal value, the rest of the countries were whole numbers. This caused countries like Norway, whose value was 93 to be 9300%. Once I converted the whole numbers to decimals the data provided more accurate percentages in Datawrapper. Another cleanup I had to do was to obtain and input latitudes and longitudes for each of the countries for more accuracy. The outcome of this map can be seen below.
Locator Maps
Locator maps are your navigational aids. They provide context by showing the location of something within a broader geographical setting. These maps are typically static and serve as a reference point, helping viewers understand where an event occurred or where a specific place is located. They are often used alongside other map types to give context, such as placing a city within a country (Monmonier, 1991). When the goal is orientation rather than data complexity, locator maps are your best bet.
My locator map in Datawrapper used a dataset that combined two pieces of data merged into one. From there I went to https://www.511pa.com/#:Alerts and manually looked up distances from my starting point. Using each of the reported EV range at 70mph I looked up the distances and randomly plugged them into the end location field on my dataset. I thought it would be fun to see how far each of the reported EV's could get from the start location in Kulpsville, PA. In Datawrapper I also included the car details (year, make & model), tire size, and distance in miles inside the tooltip for each locator. This allows the audience to hover over and see the information so there is a reference point.
Conclusion
Choosing the right map type is crucial for effective data storytelling. Choropleth maps are best for regional data, symbol maps excel in representing data at specific locations, and locator maps provide essential geographical context. By understanding the strengths and limitations of each map type, you can craft visual stories that are both informative and engaging. And remember, with tools like Datawrapper, the process becomes all the more intuitive and rewarding.
Additionally, there are a number of tools for data visualization, but especially data mapping. For this blog I used Datawrapper. However, for future projects I plan to explore ARCGIS with my student plan for $100 annually. I will also plan to see about how to use Flourish as it offers more interactivity for my audience.
Resources
Monmonier, M. (1991). *How to Lie with Maps*. University of Chicago Press.
Cairo, A. (2016). *The Truthful Art: Data, Charts, and Maps for Communication*. New Riders.
I recently purchased a new electric vehicle (EV) which is currently still in production. Since this is my first EV, I want to learn as much as possible about how they work in comparison to internal combustion engine vehicles. For months I’ve been scouring the internet to find articles and videos from industry influencers to the point that I’ve become consumed with watching YouTube videos about EVs. I follow several EV experts on YouTube, who have so much influence that they have attracted the attention of car manufacturers. I’ve developed a habit of binging their content, soaking up all the knowledge I can. For example, I might start watching a video at 7:00 pm and before I knew it, four hours had passed. This wouldn’t happen once or twice a week, but on a daily basis. I’d consume the content in the YouTube app on my mobile phone, on my iPad, or on my TV. Then I realized “WOW! YouTube is only one app. How much time is this app taking me away from others in my life?”
The Experiment
Data Detox Visualization – Legend
With that I embarked on seeing if I could go without watching a single YouTube video—not just the content about EVs, but ALL videos on YouTube! My goal was to “detox” for a total of five days. During that time, I would measure several data points. I kept track of the weather and my mood during this experiment. I captured how many times I was tempted to access the app either on my mobile device or on my TV. Additionally, I logged the amount of exercise I did and how much I slept, because I had more available time. I allowed myself to watch other streaming TV content and I tracked that activity. Data gathering takes time. Yet, when you collect the right type and amount of data, you begin to see a story. The story can be surprising, or it may confirm what you already suspected. What story would my data tell? Is there a behavior I expect to emerge? Let’s take a day-by-day look at my five days without YouTube.
Day 0 – Monday
Okay, to be fair let’s discuss before the start of the detox. You see, I felt like I did when I was growing up. During Lent we’d have to give something up for forty days. So, I’d say, “I’ll give up eating candy during Lent.” Then without fail, I would shove as much candy as possible in my mouth the night before Lent began! In my childish fashion, I did the same thing with this detox. No, I didn’t shove candy in my mouth; I watched three hours of EV content right before midnight. Now, onto Day 1.
Day 1 – Tuesday
I woke up as normal and began my day. I thought to myself “You got this!” Everything was good because I had work to distract me from being on YouTube. As the day continued, my friends wanted to know when I was getting my new EV. Well, then all I could think about was what was happening in the EV world. I felt myself getting anxious and wanting to abandon my detox from EV videos. Throughout the first day, I attempted to go into the YouTube app on my mobile phone fifteen times and tried accessing it on my TV five more times, but I stopped myself before actually watching a video.
Day 2 – Wednesday
After getting through Tuesday, I expected Wednesday to be better, and it was… a little. My attempts to access YouTube declined slightly to twelve on the app and five on TV. Day 2 also presented a new challenge at work, where I’m expected to access YouTube for research purposes. I had an internal struggle; I’m trying to detox, but my job requires me to use YouTube. Am I not detoxing? Am I cheating? Finally, my inner self said “Dude, you need to get a grip! Remember, you were trying to detox from personal consumption of EV content. Lighten up!” My inner self was right. Thanks, inner self!
Day 3 – Thursday
Thursday proved interesting. I started to forget about seeing EV video content on YouTube unless someone reminded me by asking a question related to EVs. I was calmer and I only attempted to access the YouTube content ten times on the app and three times on TV. Even though I may be weaning off watching YouTube (except where needed for work), my Instagram access increased.
Day 4 – Friday
Oops! Photo Evidence almost ending the detox early
Friday was easier because no one asked me about my EV and most of the day I didn’t even think about going on YouTube. My wife planned a family trip to a local botanical garden called Longwood Gardens. The weather was beautiful, and we brought our daughter and her friend with us. We walked around the grounds for several hours and had dinner. Detox is working…well almost. While I was sitting on a bench waiting for the girls to meet up again, my wife caught me almost finishing a day early! Yikes! Almost slipped and opened YouTube. Luckily, we have a picture as proof. I did not finish tapping to open the app. Whew! Thanks Honey!
Day 5 – Saturday
Finally, the last day. I have to say today went pretty well. I did think about YouTube and almost attempted to watch videos three times on each device. But I resisted since I wanted to see this experiment through.
Lessons Learned
Data Detox Visualization – 5-Day Results
Wow! What an experiment that was. While I didn’t give up Instagram or Facebook, my YouTube detox was helpful. One take away from the experiment is proving you can walk away from technology and survive. Sometimes it’s good to take a break and get yourself refocused. Collecting data helps you get perspective and tell your story. If you want to change a habit, try detoxing at regular intervals. This experiment showed me how much time I spend in front of a screen, not taking time to enjoy what’s around me. It’s okay to learn about something, but don’t be too obsessive. Based on this experiment, I plan to do a quarterly 5-day detox from everything digital. During that time, I will branch out and try some new things I’ve never done before.
How many times at a magic show did you ask yourself; “How did they do that?” Or, after seeing the show, did you get your own magic set and try the disappearing milk in the newspaper trick? The milk would spill. At the next magic show, you might have asked a magician how he did it. They’d always give you the same line “A magician never reveals their secret.” This is because to do so would make it…well, not magic. By now you are pondering why I am talking about magic. Wasn’t this blog supposed to be about deep thinking and tech related stuff? You’re right, but you’ll see where I’m going shortly.
As Hari describes, magicians figured out the secret early. In his words, “The job of a magician is – at heart – to manipulate your focus.” (Hari, p. 106). Good magicians can read people. In doing so, they can redirect our focus to where they want it. Before we go any further, we need to understand what manipulation is. The Cambridge Dictionary, defines manipulation as the “controlling someone or something to your own advantage.” Let’s focus on controlling the outcome to your favor. This is what marketers and advertisers want. A magician hides the liner inside the milk pitcher. This way you don’t see what’s happening. The milk is actually going back into the pitcher. They’ve drawn your focus to them and not the pitcher.
Akin to a magician, Hari goes on to describe examples at companies who use manipulation. Companies, such as Google, measure product success by “engagement.” They use this to get users to stay “hooked” on their devices. The more we stay on our devices, the more money companies make. Manipulation didn’t start with tech companies such as Google. Instead, manipulation or loss of our attention predates the digital age. The only difference is that it’s more prevalent with the advent of constant connection. B.F. Skinner used reinforcement to change (manipulate) a behavior. Think about Instagram or Facebook. Your liked posts receive hearts and thumbs up or other emojis.
I’ll take that!
A magician entertains you by focusing your attention on them and not the trick itself. The con artist though is the one who changes your focus with malicious intent. A good con artist will study their “mark” and learn everything about them. The more the con artist knows, the easier it is to play to the mark’s weakness. Today companies know their customers better then the customers know themselves. Why you ask. Because Hari says “companies are building up a profile of you to sell to advertisers who want to target you.” (Hari, p. 125). Remember, each click provides the tech companies more data so they can “better” serve you. Many are unaware of this data collection. Digital natives are aware and most have become immuned.
Mesmerized
Adaptation of Nir Eyal’s Hooked model illustrated by Tony DeRose
All this discussion about magic and manipulation reminded me about a book on a similar topic. It’s a book by Nir Eyal titled Hooked – How to Build Habit-Forming Products.Hooked and Stolen Focus have some parallels. In it, Eyal focuses on describing his four-step “Hook” model, to change customer behavior. Each cycle consists of a trigger, action, variable reward, and investment. A well-designed product keeps users in the loop. Take Instagram for instance. You took a great vacation and want to share it with the world. (Trigger). In the Instagram app and you upload several pictures, type a description. The post is available for all to see (Action). Your friends and family see the post with your beautiful pictures. Many of them will likely click the like icon or post a comment (Variable Reward). Because you’re receiving comments and likes, you stay in the app longer. You’re now invested to see more posts. Before you know it, you’ve spent two hours on Instagram (Investment)… and you didn’t get your assignment done! This type of manipulation is what makes a product successful. Yet, like Hari, Eyal does admit a morality check needs to occur. Eyal offers a simple tool which he calls the “Manipulation Matrix.” (Eyal. p. 167). The matrix asks two simple questions: “Would you use the product yourself?” and “Will the product help users materially improve their lives?” Your answers determine where you fall on the Manipulation Matrix. Eyal defines them as peddler, dealer, facilitator, or entertainer.
Finale
A magician taking a final bow.
It was interesting to see how both Stolen Focus and Hooked share similarities. Yet Stolen Focus looks at several factors of manipulation. One, how our attention is being taken from us, two, how to recognize it, and three, offers some ideas how to change it. Hooked, looks at how to build apps to change your customer’s behavior so they want your product. While there is a small chapter on the morality of doing this, the book focus’ on getting the customer “hooked.”
With that, I leave you with this final thought from the late great “Professor” Neil Peart (from the rock band Rush). Neil was a great philosopher and a phenomenal lyrist. The lyrics for the song “Freewill” are about predestiny and freedom to choose. The lines below sum up how we choose to get our attention back and control the hold that the digital realm can hold on us. Even in a digital age, when our stolen focus, we have free will. So, it’s our choice to decide how we balance our digital interactions and the real world.
“You can choose from phantom fears And kindness that can kill, I will choose a path that’s clear I will choose free will.”
-Freewill (Rush)
References
Eyal, N., & Hoover, R. (2019). Hooked: How to build habit-forming products. New York: Penguin Business.
Hari, J. (2023c). Cause Six: The Rise of Technology That Can Track and Manipulate You (Part One). In Stolen focus: Why you can’t pay attention–and how to think deeply again (pp. 105–123). New York: Crown.
Hari, J. (2023d). Cause Six The Rise of Technology That Can Track and Manipulate You (Part Two). In Stolen focus: Why you can’t pay attention–and how to think deeply again (pp. 124–142). New York: Crown.
Rush. (1980). Freewill [Vinyl recording]. Le Studio, Morin-Heights, Quebec: Terry Brown.
