Tag: data

http://www.visualcomplexity.com/vc/project_details.cfm?id=980&index=980&domain=

This diagram displays the areas most walked in downtown Boston, it uses lines to demonstrate a path of travel, the darker and denser the line, the more popular that street is walked. The map is much darker in the center and diffuses out, streets near the water are also more populated. We can learn from this that the city center and water ways must have something attracting people likely food, jobs, and activities that cause more people to want to be there. We can also tell from this that the city was likely designed to have these things closer together so people could easily go from place to place. The areas by water are likely attracting people because it’s more scenic for walking and running, for those living in the city it’s better to walk or run away from the center of the city where there is a lot of traffic. This is useful for people in Boston to see where most activity is so they can find places, or avoid highly trafficked areas. This is interesting because it differs from a normal map which only shows the streets, instead it actually shows the areas on the streets that are populated. The data here is interesting because this also demonstrates a pattern, if we were to look at other city maps showing places of travel we would likely find similar results, a dense city center and coast.

https://www.reddit.com/r/dataisbeautiful/comments/9ddzey/oc_amount_of_music_listened_to_vs_time_of_day/?utm_content=title&utm_medium=hot&utm_source=reddit&utm_name=dataisbeautiful

The bar graph demonstrates the number of songs listened to per given time of day. There are large peaks at 3pm and 9pm, we can use these trends to see why people are listening to more music at these points in the day. We can assume the 3pm peak is from students getting out of school and listening to music and the 9pm peak is from people listening before bed or partying. There is also a smaller peak at noon, we can assume this is because most people are at their lunch break around this time. The graph is in no way symmetrical, the left side is empty from 3am-8am while the rest of the day is packed with music, this is likely because most people are asleep from 3-8am and aren’t listening to music. This data can be used by companies to know when they should put in ads to make sure they reach a larger audience. The trends in this data is interesting to understand not only when people like to listen to music, but also to understand society. People often listen to music independently today on their phones with headphones, this data shows us when people are more independent during the day. It also demonstrates when people usually wake up and go to bed. Data can represent more than just what the variables show nbecause data trends demonstrate other trends in society.