/r/dataisbeautiful: A Look Inside

I have to admit, I was excited when I was assigned to write about two data visualizations. This is because Reddit was one of the allowed sites to visit. I love using Reddit, so I’m grateful that I get to use a site I’m so familiar with. The subreddit I could use is called r/dataisbeautiful. In this subreddit are a bunch of user-submitted visualizations of very kinds of data. They’re all very interesting to look at, but I narrowed it down to two posts I could write about. The first data visualization I really found interesting was a graphic representation of the total amount of noise energy given off by fans during a soccer match between two German teams, Bayern Munich, and TSG Hoffenheim. The site lets you see a visualization of how loud the crowd gets in real time. The site even features crowd energy during specific moments in the game, like when a Bayern player scores, or when the players are introduced. It really makes me think about just how powerful a group of voices can be. The second most interesting post I found was a collection of Tropical Cyclone data collected by the National Hurricane Center. The site shows almost everything you can think of when it comes to hurricane data, from past hurricane tracks to probable origin points for new hurricanes. I think this kind of stuff has always been fascinating to look at, and I’m pretty thankful that we now have the technology to obtain so much information about these destructive storms.

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2 thoughts on “/r/dataisbeautiful: A Look Inside

  1. The first visualization you were describing was also one of my favorite depictions of data. The visual is also very exciting in my opinion because it is a recently developed technology, has a lot of room for growth and involves something I care about: sports. I am also very curious to see if this technology can provide statistical evidence around the World of the craziest/ loud fans in comparison to crowd size, total volume, etc. All these statistics are valuable to see numerous different companies and groups, but it is also fascinating for the World of sports to observe. The second visualization you describe is also very interesting. I think that it is very cool how scientists have been able to develop a visual representation of future hurricane/ storm paths by passing it off of previous knowledge. This also makes me wonder how strong this representation really is. Recently hurricanes have devastated the United States, and these same equations failed to predict then what could have occurred. I wonder if we will ever be able to perfectly track/ understand weather patterns.

    https://www.bloomberg.com/graphics/2018-crop-shift/?srnd=premium
    This images above are visual representations of the United States agricultural development. You can view what crops are thriving in what regions, and what crops are failing in certain regions. This is like the hurricane tracker because it is directly affected by weather. This visualization also involves several variable factors that can change the outcome entirely. The representations also showed just how much our economy has been affected by global crop competition.

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  2. I liked the first one you did your homework over. Being into sports my whole life I am very interested in any type of statistics, even noise. Even though my knowledge on soccer is limited, I still know that soccer in those countries are big. It was cool to find out the noise levels in these matches with certain teams playing.
    http://statsbylopez.netlify.com/post/playing-at-home/
    This visualization shows which teams have the loudest home field advantages while playing at home. This graph is similar because it talks about sports and noise level, which is exactly what your graph talked about.

    The second visualization you did was interesting. I have always been interested in weather and think it is very cool an fascinating. Hurricanes cause major damage, and you can see that this visualization goes into it very well. I like how well this visualization looks, and displays different types of data.

    The visualization that I chose to go along with your visualization was a cool map that shows how warm it is in a particular part. Seeing that some places have gotten hotter is cool an knowing if your hometown has gotten hotter since you left is very interesting. This visualization is about weather, and the country just like your visualization was.

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