Data Viz Thoughts .|: Viva Las Vegas’ Growth and Lindsay Betzendahl (of #ProjectHealthViz) has our Viz of the Week
A Tableau-centric weekly blog about the viz making process, #datafam member interviews, #DataVizThoughts Viz of the Week + entertainment for introverts (consisting of a music morsel & a binge bite).
This week we will share thoughts on one of my vizzes + Lindsay Betzendahl (@ZenDollData) Autism Spectrum Disorder in the United States is our Viz of the Week (#VoTW)!
Michael Sandberg (@michaelangeles) interviewed me as part of his Tableau Community Spotlight series in his data visualization blog. If you want to know a little more about me and find another great blog, please check out the interview!
Viz Thoughts on….
It’s been a couple weeks, but I leveraged a holiday to escape cold weather & enjoy the balmy San Diego climate. After returning from the ‘escape’, I felt like I missed out on so much in the community. Worse yet, I’m in an early winter prison and Mother Nature shanked me (this past Thursday, the windchill was three degrees… it’s barely November).
Helping heal Mother Nature’s battle scars, the #MakeoverMonday crew had a topical data set (to start with) and inspired more exploration to see Las Vegas’ economic trends (obviously timely and relevant as next week is #TC19).
The data covered Clark County (chiefly Las Vegas) visitors, gambling expenditures, rooms (+ occupancy rates) and other good bits from 1970 through October of 2019. After a brief review, something told me further context was needed to analyze actual trends.
The gambling expenditures means very little without adjusting for inflation. For example, $1 in 1970 equaled the spending power of $6.62 by 2018. Next, we needed to grab population context — although, Las Vegas attracts visitors worldwide, in 2018, only 5.8 million of 42.1 million or less than 14% were international visitors. As a result, the contingent population metric used was annual population in the USA. Digging even further down this rabbit hole, the UNLV research implied that a lot of the change in the reduced dependence on gaming (gambling) revenues was chiefly due to ‘Other’, which was mostly nightlife and retail spending — the revenue categorizations began in 1984 and ended at the end of 2018 and better yet also broke down various revenue generators with measurements of the Las Vegas Strip (hereafter referred to as ‘The Strip’).
‘The Strip’ is important to detail because of any place visitors stay, most vacationers stay and spend in & around that area of Vegas. Other places outside ‘The Strip’ would have a much larger factor of local expenditures (rather than just the visitors). In short, ‘The Strip’ is Vegas’ touristic trend pulse.
How was I going to put this together and what did I want to test?
— I knew the review period was the 35-year period of 1984–2018 covered with the revenue breakdown needed to be the viz’s time period.
— ‘The Strip’ was nearly ½ of the entire state’s revenues with the gaming, room, food, beverage and nightlife/retail, so obviously it would cover the lion’s share of Clark County.
— Using inflation’s context, how has gambling been impacted?
— Are visitors coming to Vegas at a similar rate to the growth of the US population or has it changed?
— And the big question… If gambling was impacted by different revenue streams, is it because of retail/nightlife or something else?
— If it’s something else, what and how?
You can see how this data deep-dive became bigger than the initial intent to look at convention rates and gambling over time.
Applying the context to the data began to reveal beautiful data diamonds that added luster to some of the conventional wisdom, but it also uncovered many other cracks in that wisdom while revealing other gemstones. It’s no surprise that over time gaming (or gambling) revenue leaked. In 1988, it peaked from $387.19 per visitor, but fell to $236.65 in 2016. When we are looking at millions of visitors, that’s a big deal! (1)
What did Vegas do in response?
They went all-in. In 1988, there were 61,394 hotel rooms in Clark County and even in the face of gambling revenue depletion, they continued to build. From that point through 1999, they nearly doubled their rooms to 120,294 while gambling dropped 9.23% in total revenue.
Did their total revenue drop?
Bleep no. The Strip’s total revenue climbed from $7 billion to $11 Billion.
While gambling slipped significantly, room revenue bolted from 17.28% to 22.14% of total revenue. They built rooms and people continued to come. Even in the face of all this development, the occupancy rate grew from 85% to 88%.
Other cash streams that upsurged with the room revenue were retail and nightlife (as concluded by UNLV). During the same period, it climbed from 7.41% to 12.99% of total ‘The Strip’ revenue or roughly the same clip as the room revenue. This tells me the ‘new face’ of the Las Vegas visitor changed from the lost-shirt high roller to an amalgam of folks looking to be entertained and leave the casinos from time-time to watch shows, party and shop.
This visitor remix became more pronounced until recession hit in 2008. The next breakdown looks at continued changes from 1999–2007. By the close of 2007, 41.02% of (The Strip’s) revenue was for gambling, 25.8% was room revenue and 13.78% was gambling and nightlife while total Clark County spending hiked from $15 to $19 Billion. Although the recession stung everything for Vegas visitors (think… vacations/conventions/gambling requires some disposable income), it has since rebounded with similar trends prior to the nation’s economic meltdown.
And yes, Vegas continued to build at a breakneck pace through the recession. From 1999–2011, they added 29,867 rooms in Clark County (or a 24.29% increase/nearly 2% each year). After 2011, they stopped building as available rooms steadied, but occupancy rates have been slowly inching toward 90% for the entire county since the builders put their construction caps away.
What does this mean for the future of Vegas?
They effectively sunk their mob past with the fishes. More people started coming when it was no longer ‘just’ a gambling town. The options, revenue streams and additional fantastic outlets attracted (and continue to fetch) a wide net of visitors.
The top viz shows a trend of continued growth — even when compared to the growing U.S. population. Back in 1989, only 7% of the U.S. Population went to Las Vegas (18 million visitors) — as of 2018, the visitor amount has risen to 42 million and has ballooned to 13% of the U.S. population. These visitors are dripping money and the previously unthinkable has happened….
In the past, Vegas was tarnished with a long history of fixing sporting games and a strong criminal element to ensure outcomes to make money. This taint made Vegas a forbidden location except for prize fights. With the slow evaporation of gambling and its criminal fog layer, major sports franchises came and are continuing to come!
In 2017, the NHL laid claim to Las Vegas and brought the Golden Nights; the next year, WNBA brought the Aces and in 2020 the Oakland Raiders will be the Las Vegas Raiders. These franchises will undoubtedly bring more income to the city. (2)
Sports venues (not just ‘sporting’), more adult options and adding a wider entertainment net and family-friendly options (shows, shopping malls/outlets, exhibits and arcades that continue to pop up) is today’s Las Vegas. (3) With the changed narrative and diverse entertainment avenues for all type of visitors, the only growth ceiling in sight for the destination is one imposed by the economy and how much the city can build.
Viz of the Week
Lindsay’s viz and topic for October is very dear to me. When I was a kid, nobody really knew what high functioning autism or Asperger’s was and the only diagnosis was provided to those with very severe disabilities. Prior to adulthood, my lone experience to autism (because of the above, I had know way of knowing I had Asperger’s) was a film in class of a young boy with a severe autism-impacted limitations. It’s magnificent to see so much more research put into autism and states stepping up in recent years to prioritize detection and education.
Adam Mico (AM): The data set is very interesting. How did you come across it and what inspired it and the topic to be the inspiration for last month’s #projecthealthviz?
Lindsay Betzendahl (LB): I actually came across the Autism data back in April when I was searching for interesting data sets to utilize for #projecthealthviz, but held on to it until November. As someone who worked for many years as a child behavioral health clinician, data about children’s mental health is particularly interesting to me.
When I found this data set, I was unaware of the CDC’s Autism and Developmental Disabilities Monitoring (ADDM) Network. I found it particularly interesting that the CDC has been working on using these sites around the nation to survey the prevalence of ASD. They use a small population (8-year-old youth) which is used to more globally estimate overall prevalence.
Additionally, with any #projecthealthviz data set, I strive to challenge participants to think about the data and read the articles to better comprehend the data story and to best interpret it. In this case, it was important to know how the data is collected, what the population was, and what prevalence rates really mean. With any mental health diagnosis, variance in prevalence rates can be due to so many factors, and we need to be careful not to make assumptions about the likelihood of getting a disease based on a rate.
Mental health prevalence rates are only as good as diagnosis rates. If people don’t have access to care (such as treatment or early intervention programs for ASD) then they don’t get diagnosed. If they aren’t diagnosed, prevalence rate may appear low, but the truth of the matter is that people aren’t getting the care they need. For example, in the data set, New Jersey has high prevalence rates of ASD according to the ADDM Network data. However, this could mean that New Jersey has excellent care for ASD and more youth who need treatment are able to get it, not that living in New Jersey will increase your likelihood of getting ASD, because that is false.
AM: Do you know adults and children in your personal life that have autism or Asperger’s (which fits my experience best) and how has working with the data and seeing the community’s viz responses and discussion impacted your view of the condition?
LB: Yes, I know people both personally and in my behavioral health career history with various types of diagnoses along the ASD spectrum. I had a wonderful client who had Pervasive Developmental Disorder (or PDD, when that was a DSM diagnosis), and I worked with youth with severe ASD as well as mild (or high functioning) ASD. Through my experience I’ve learned that each person with any of the ASD diagnoses is going to present differently and it’s important to realize, that just like anything else, with similarities also comes differences.
I’ve been very touched by the personal experiences many people have shared after participating in #projecthealthviz. It’s beautiful to see people share how they relate to the data and can put their personal experience or knowledge into a viz. “Telling the stories of our health” is the tagline of the project, and I’m thankful that people are taking that to heart and telling these stories.
Stigma is one of the reasons that people don’t share more about personal behavioral health or medical conditions. Stigma is a direct result of a lack of awareness and knowledge. With #projecthhealthviz, I aim to reduce stigma by increasing awareness and promoting more conversations which lead to connection. We are all more connected than we know! Many people in the data viz community this month have shared that their they have a type of ASD or have a direct relative that does. I know it can be hard sometimes to share personal stories, but I believe it helps to increase awareness. Stigma is an ugly thing and I’m glad that perhaps #projecthealthviz can help reduce it, even in a tiny way.
AM: It looks like you smartly used dashboard buttons and parameter actions for states to make the layout manageable and make data digging a fun exploration. What inspired the design and layout?
LB: Thank you. Yes, I used both collapsible container buttons and parameter actions for the state section. Not long before I started working on the viz, I saw a viz by Spencer Baucke (@JSBaucke) and Luke Stanke (@lukestanke). I really liked the layout: the background color, the padding of the containers, the little graph under the title, the text within the graphs to tell a compelling story, and the two-color palette. It was those small details that gave me inspiration for my viz.
I started with a similar width dashboard and an overall container with lots of outside padding to give it the feel of margins. What I didn’t want was a very long dashboard like theirs, which while I love theirs, I didn’t have that much data. But I did want people to slow down to read and view the information, and have a chance to interact. This is where I decided to add the buttons after I saw a viz by Pradeep Kumar (@pradeep_zen) where he had created some very lovely buttons. I created similar ones in PowerPoint and used that as the idea to have separate sections for each of the data elements I had in the data set: gender, race, and states (or location).
I think the design allowed me to keep the viz elegant, simple, quick to interact with, and clear to understand. There is no sense trying to increase awareness of Autism if you make an overly complex viz. I first attempted the no-polygon technique for the race section then realized it just was silly. While a fun method, it rarely is actually practical to show the data in that way. I changed it to simple bar charts with some custom calcs to get the max value label to populate and the colors. So even with a simple viz, I challenged myself with the back-end calcs to make things happen. Bars are NOT boring! (4)
AM: As far as the data is concerned, what struck you as the most interesting data nugget uncovered when analyzing the information in the data set?
LB: In my experience, white males consistently have the highest prevalence for ASD. That is a known data point both nationally, but in individual states as well. What I found interesting, was that there were some states in the ADDM Network where the prevalence was higher in other racial groups than whites: Arizona, Arkansas, North Carolina, and Minnesota. Since prevalence takes into account population, I wondered why these states went against the normal finding and wonder if it has to do with reduced stigma in these populations or if they have any specific programs for early identification and treatment that cross cultures and perhaps socioeconomic groups or different areas of the state. The CDC didn’t explain these differences, but it was something I noticed and wondered about. (5)
Thanks again, Adam, for allowing me to share some information about #projecthealthviz, its mission, and about my recent viz on Autism Spectrum Disorder. It’s an honor to share this information with others and explain why I’m passionate about telling the stories of our health.
Bruce Springsteen is a boomer artist and his brand of rock music sounds totally boomer-ific, but ‘Brilliant Disguise’ is a bit different. Yes, it sounds a bit polished with that mid-1980s slick production matte, but listening to the track and seeing the video, this cheesy love song devolves into a maze of anxiety of self-doubt that pairs perfectly with the video’s zooming perspective.
The Devil Next Door is the most captivating and provocative true crime documentary (or docuseries) I have ever seen. It involves Nazis, survivors, hidden identity and/or mistaken identity, international trials and riveting arguments/judgments.
Note: The subject matter is very disturbing with some gruesome imagery, so please keep that in mind if you are about to check it out.
2)For more info on that, please review this detailed local economic impact of sports franchises.
3) Check out 60 Things to do in Las Vegas with Kids.
4) Especially if you read Zach Bowders’ Behind Bars Volume 1
5) My best guess is that white children have the best combination of lesser stigma of autism and access to medical professionals than can make the autism diagnosis (there are a very limited number of people that can make that diagnosis, are usually very booked and are best found/accessible with good health insurance plans with robust mental health coverage. With reduced stigma via education, having more professionals making accurate ASD diagnoses and care is more democratic, I believe there will be a smaller gap between races and sexes.