Who Old Are You?
This data visualization from informationisbeautiful.net takes in your date of birth and compares you to many, many other people and events in life using a dotplot. Each of the colors represents a type of event, usually corresponding to a certain person, while the black dot represents where you are on the visualization. For example, my age is 18, and right behind my dot is Frida Kahlo’s beginning of painting. The dots are placed along a vertical and horizontal axis, where the vertical represents the amount of people at that approximate age while the horizontal represents that age at which a certain event or associate person is placed. What I can see here is that I am right at the cusp of where many famous individuals had their start. What I find most interesting about this data visualization is that I can really see that most people had their start at an older age at me, which is somewhat reassuring as my peers and friends, along with myself, feel that they need to “catch up” with others at various competitive values, such as academics, career, sport, etc. I also like that despite the large amount of dots, it’s still very readable and shows a clear pattern.
Hot Days
This data visualization from flowingdata.com takes your hometown and birth year to output a series of line graphs that show the number of days on average per year where the temperature exceeded 90 degrees Fahrenheit. There are two axis: the vertical represents the numbers of days on average per year that were hot, and the horizontal represents each year that has passed (and to be passed). For example, I used my birth year (2000) and my birth town (Duluth, GA) and found that it was relatively hot that year, which made sense seeing as it’s Georgia. Then, the data visualization showed me that today, it would be an average of 42 hot days a year, which is an 8 day increase from the previous graph. The final graph shows a prediction for the next 60 years, which shows a significant increase in hot days per year and includes an approximate range since the statistics are predictions that cannot be pinpoint accurate. This data visualizations purpose is to show the trend of increasingly warmer and warmer summers due to climate change. I find it interesting that they used data like birth year and hometown because it’s more personal, so it’ll have more of an impact to those who are viewing the graphs.
For your first data visualization I find it very interesting however I was very confused because I can not access it. But from what you have said I can make a connection in the sense of that at my age now, many famous people had their start to fame. I also like how you stated that many people started their road to fame at an older age, it IS very reassuring to me that I could still be very successful at a younger and older age. Everyone succeeds differently and at their own pace, but everything turns out well in the end however, sometimes everyone needs a little competition or push to keep going.
From your second data visualization I can connect with you because I was born in 2000 as well but here in the central part of Washington state, however it was very hot that day because it was still summer. I also observed the data for the next 60 years and it is a little frightening seeing how much hotter it can get over the years (maybe because of global warming?). Other than that, I really like how you explained your observation of the data and gave your opinion at the end. Getting to add your year and hometown does make it more personal!
I found this other data visualization that may connect with the two you have! Either or.
https://www.usclimatedata.com/
I’ve chosen to observe data that pertains to how accurate weather reports actually are. These observations were very accurate ultimately they’ve shown that weather reports are more accurate when it is predicted 4 days ahead which is very shocking given you would think that when the more far fetched a weather report is the least accurate it would be but it turns out it is actually the opposite. This is how i interpreted this data ultimately this chart is not very clear. I say this because the data is harder to process. If this was a much simpler visualization it would be easier to understand. The color code helps none because there are mini sub charts in one bigger chart the only thing that is understandable is the amount of days shown on the chart for the amount of days weather is measured ahead of time. With that I would say this chart is not very helpful. If it was to be put to use it would be useful for a weather reporter or maybe an opposing weather network because of the way it shows data from different weather reports in comparison. This chart can be used to improve the accuracy of weather predictions if need be. In a more easily interpreted format.