In approaching Tableu and my first chart, I intended to emphasize the differences in time by making each category a shape of some sort, then by enlarging or minimizing said shape depending on the time. Another thing I wanted to keep in mind was a sentiment my high school AP Statistics teacher told me about the college lifestyle being made up of three main time occupants: sleep, social life, and studying. While I would assume that the data set encompasses time usage across a wide range of ages – which ends up being a question that remains at the end of the data visualization process because little to no context is provided on the website the data is published on – I thought that the inability to account for participants' ages would skew the data, but I also deduce that the "college lifestyle triad" is not much different post-grad. That being said, that could be a short-sighted claim, especially given my position as a college student.
The following screenshots are representative of my learning process, both of Tableu, and also the data set and how to isolate the categories Education, Attending Events, Other Leisure Activities, Seeing Friends, Personal Care, and Sleep. The final screenshot is the final presentation of the data which conveys the disparities in priorities in countries across the globe. With Time (in minutes) being on the x-axis, such placement implies that the more time spent doing any given activity, the more prioritized, or rather, the more normalized. This visualization allows for viewers to associate the circles on the right side of the graph with the most normalized or prioritized activity. With the white outlines on each circle, viewers able to see the overlaps in categories, and with each circle being a different color and different size, viewers are able to compare and contrast the differences of time usage in each country.
QUESTIONS:
Would it be more beneficial to combine data to make three categories (self care, social life, and education)? Or would that complicate things?
Are there any similar studies done but with a focus on a specific age group?
How long does it usually take data journalists to settle on a visualization that is most appropriate and best fit for the data and the story they are trying to tell?
FINAL DATA SET
ATTEMPT 1
ATTEMPT 2
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