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week 7 reflection - Joselin Barbosa #117

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week 1 reflection - Joselin Barbosa
joselinb Jan 16, 2024
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Update week4.md
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week6.md
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3 changes: 3 additions & 0 deletions week1.md
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https://datainnovation.org/2018/03/visualizing-income-mobility-across-racial-and-gender-groups/

This animated data visualization was published by The New York Times to show how based on your gender and race the likeliness of income mobility if you were raised by a poor family. The data visualization that’s pictured in this article compares the lives of 50,000 American Black and White women. It demonstrates although Black and White women have similar individual earnings, they do not have the same household incomes. In fact, White Women tend to have higher household incomes. I think this is a good visualization and it highlights differences and similarities between groups well. The colors chosen for the visualization are distinct enough to be able to track the different dots on the screen. I also like the way it’s designed so that you can visually see how the people that are poor are at the bottom and the people that are getting richer move up the graph. I enjoy that it is an animated visualization so the viewer can actually “follow” the dots or perhaps the life of an individual person and see if they rise in economic status. I would have preferred a bolder color or a different way to display the labels such as “poor adult” and “lower middle class adult” since it does get harder to read them as more dots pile in. Ultimately, visualizations like these could be use to promote policies that can help Americans achieve economic mobility and move out of poverty.
3 changes: 3 additions & 0 deletions week4.md
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https://flowingdata.com/2022/03/01/change-in-common-household-types-in-the-u-s/

To illustrate changes in common household types in the U.S. this article uses an alluvial diagram. It's a combination of a flowchart and stacked area chart. The graph shows how we went from it being more common to be a married household with kids in the 1970s to living alone or married with no children in 2020. Overtime, Americans have waited longer to get married and have fewer to no kids. The visualization dooes a very good job at showing the changes over time. It does get harder to follow what each color means, specially as some sections get smaller and smaller. At first glance, I didn't even notice the single father at the bottom of the graph. I think a simpler way to showcase this data would be through a line graph. The colors used by the visualization are generally good, with an exception of the two yellows. The yellow that signifies married couple with children and the yellow that signifies a single mother are too similar that it gets slightly confusing.
3 changes: 3 additions & 0 deletions week5.md
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https://stats.stackexchange.com/questions/622611/is-this-data-visualization-of-heat-and-cold-deaths-misleading

I found this data visualization as a part of a discourse on whether or not this visualization was misleading and climate change propaganda. The visualization is meant to show country level cold and heat annual raw death rates broken down by age group. I do find the having two different scales for excess death rate to be deceiving. The way the visual is split in two it makes the viewer want to draw comparisons between both, although the scale is not the same. Also, the break in the x-axis I feel is not really necessary. I think a better way to bring the point across would be to separate the data into two separate graphs. Although the visualization intends to draw comparisons between the different European countries, the design could be improved. They have total bars as well for the four regions and the different saturation for them is confusing. I definitely think the whole visualization should be redesigned. This was used as a part of a scholarly journal, so I believe a better representation of the data should've been used.
3 changes: 3 additions & 0 deletions week6.md
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https://medium.com/nightingale/https-medium-com-data-visualization-society-wedding-data-viz-36e7b9f4787f

For this reflection I chose a more peculiar data visualization. A couple who met through collaborating on a data visualization project decided to tie in dataviz into their party favors/badges. The couple decided on a design that would visualize how long each of their guest knew the pair and how they met them. The visualization was in the shape of a heart, with each lobe being either the groom or the bride. The size of the lobe would indicate the length of the relationship and the color would be the type of relationshhup. Because of the heart shape of the visualization, it is harder to compare how long the guest has known the couple. It is interesting to note that the couple was mindful in setting a minimum size to how small the lobe could be (indicating length of relationn). This was done so guests that had recently met the couple, still had fun looking badges. The data visualization was done using R and ggplot. Using these tools they would label each plot with the guest name and have two dots - with color and size adjusted accordingly. Then using Adobe Illustrator the graphic was designed to look like the heart and match the color scheme of the wedding. At the end, they created a network diagram of all the guests.
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https://truth-and-beauty.net/projects/the-rhythm-of-food

This visualization is focused on when people tend to Google search different food items throughout the year. This data visualization is a radial year clock chart, which allows the viewer to see the interest in the food item throughout different seasons and years. Each year, from 2004-2016, is color coded. The radius, so where the segment is in the circle, is the amount of searches, meaning the closer to the center the less searches. Some interesting trends were certain foods being searched whenever they were in season. A beginning of the year trend that was fun to see was people searching up smoothies in January - for people pursuing the “new year new me” mentality. I liked that the visualization had notes to highlight certain trends that explained the random increase of interest. For instance, mint julep had an increase in searches during the end of May due it being the official drink of the Kentucky Derby. I think the visualization overall does a good job at highlighting trends in food searches, and I specially liked the context it provides. This is a visualization I would like to recreate, so it’s nice to know that it was created using d3.