Data Visualization paper
The graph is a bar graph titled ’Pickleball Growth in the US”. I found this graph in an article written in 2023 about the fastest growing sport in 2023. It has years from 2017-2022 on the y axis and players in millions from 0-10 on the Y axis. This visualization is trying to tell the story of the exponential growth of the sport, Pickleball, from 2017 until 2022. It is trying to show the reader that the sport has grown rapidly over the course of 5 years and shows a quick jump from 2021 to 2022.
I think that the visual does a decent job at conveying the story. It is a very minimalistic graph, so it does not provide much detailed information about the story it is trying to convey. It gives me the general idea of a sport with not many players exploding to a huge amount over a short amount of time, but it may not give the full story. For example, if there was a long period of stagnation before this. I am not sure if it is relevant, but it could be helpful in telling the story that they are trying to convey.
I do not think that the visual is being intentionally misleading. Something that could be misleading is the lack of detail/labeling on the bars. It is easy to see the jump in popularity from 2021 to 2022, but without labels, it may be difficult to see the drastic jumps in each year. For example, the years 2017-2021 don’t look like much of a big difference, but there is a close to 60% increase in those years. Another misleading aspect could be the Y axis. It is labeled “Players (in millions), but does not give further specifications or context. Are people who have played once counted in this number? Or is it only people who continue to/play consistently? It is hard to tell without further context or specification and could lead people to believe that there are more people that are playing than there actually are.
In relation to visualization principles we learned about, it is not too poorly constructed. First off, it is important to consider the amount of clutter on this graph. The graph is fairly minimalistic and only shows what it needs to to convey its story. This is also a detriment in that it does not give much detailed information. Another good thing that the visual has is that it uses the principle of proximity to easily show a growth trend over the given period. Lastly, the visual uses contrasting colors to differentiate the bars from the labels of the X and Y axes which makes it easier to read and understand.
The visual could be improved in a few different ways. The first way I could think of would be to add more data points. The sport was invented in the 1960s, so you could include its number of players from the very beginning of the sport. I think that it would look fine as a bar graph if it were to keep the same format, but it could also be changed into a line chart in order to show a more fluid change in players over time. This visual would more fluidly show the change in player count over a long period of time. To keep it simple, I will keep the graph as a bar graph for the improved version. I think it would be okay to include 10 years of data to show a more accurate growth rate. If you were to keep it a bar graph, it would be good to show the number of players each year within the bar in order to make the visual easier to read, rather than having to try and estimate the amount with eye measurements with the Y-axis. Along with this, because the Y-axis does not hold a large amount of values (1-10), it would make the graph easier to read if you made ruler lines for each integer. Lastly, you could add something related to the players on the Y-axis. We do not know what types of players they are, so we need to add something to the label. For example, we could change the label to ‘Players who have played 1+ times’, or ‘Concurrent players’. The data the graph is based on is probably based on a predictive study, and I will assume it is people who have tried the sport at least once.
My improved version has a few changes that makes the graph easier to understand. First off, I extended the range of data from 5 years to 10 years. This gives the reader a wider range of data to compare, and shows a more quick and dramatic increase in the latter years. Next, I added numbers to the bars in order to make the value of the bar more quickly available for comparison for the reader. I also added the values of the odd integers to make it even easier for comparison of the bars when looking at the graph. Also, in order to get rid of confusion on who the “Players” are, I added more detail to the label on the Y-axis. Lastly, I added the time frame of the data being visualized into the title.