Week5-bgmsadoques-wpi-Benjamin-MSadoques

week1.md

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+Copied from other repo
+
+Benjamin M'Sadoques
+
+vis: https://insights.stackoverflow.com/survey/2020#technology-programming-scripting-and-markup-languages-professional-developers
+
+I found this dataset to be rather interesting and informative. Unfortunately I've ran out of time to write the rest of this.

week2.md

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+Reflections Week 2
+---
+
+By Benjamin M'Sadoques
+
+vis: https://www.reddit.com/r/dataisbeautiful/comments/ljzcqk/most_commented_subreddits_201821_oc/
+
+I found this vis and data to be rather interesting. I am not a reddit user, I'm just an outside observer, but I know about a few of the trends the vis shows. 
+From the data, it seems that reddit tends to reflect both real world and internet trends. <br>
+r/Ask reddit dominates for most of the video but you can see r/Coronavirus rise in march, when the virus really started to spread.<br>
+You can see r/memes get a lot of traffic as people are in quarantine. You can see r/politics overtake ask reddit at the election peak and debates. <br>
+You can see r/wallstreetbets explode towards the end, when the sub started heavily buying GameStop stocks to screw over hedge funds that were betting the GameStop stock to fail, 
+costing the hedge funds millions.<br><br>
+
+There are a areas where I think OP could improve. The animation is rather fast and can be hard to follow. Avideo is a good way to demo this kind of vis. 
+Maybe OP could include a seperate link where users could have direct control over stepping, or animation speed. <br>
+I would like the option to see a higher number of bars.

week3.md

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+Reflections Week 3
+--
+
+Benjamin M'Sadoques
+
+Vis: https://www.reddit.com/r/dataisbeautiful/comments/lps8ba/oc_algorithmically_organizing_a_social_network/
+Library: https://github.com/shobrook/communities
+
+This vis/library finds community structures in network graphs. The libary provides several algorithms such as the louvian method to detect communities.
+The library provides visuaization and animation using matplot lib and networkx. 
+Since the libary is highly specialized, you could build a vis with very little code. 
+
+There are a few problems I have with the vis. I have no idea what these end groups are, sure I know the items are correlated,
+but there should be some sort of key. The graph seems to missing an x axis, I think it is measuring algorithm time, but I am not sure.

week4.md

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+Reflections week 4
+
+Vis: https://www.reddit.com/r/dataisbeautiful/comments/lu9tp6/hours_of_daylight_around_the_world_as_the_year/
+
+A bit late on this one.
+
+I thought this vis does a good job showing hours of day light. I have always known about this happening,
+but I have never seen anyone visualize how the daylight changes through the year.
+I like the color scheme that is used. It is meant to be a diverging color scale. 
+Instead of just using monochrome, they used colors to clearly show both
+the extremes and the transition from low hours to high hours of daylight.
+I like the one year clock, it helps show where we are through the year.
+
+The only problem with this vis for me, is the map can look a bit hazy. 
+We know that the shift in daylight is caused by the earth's tilt, so I am not sure why the vis does not mention that.
+I think the year clock could be changed to show exactly how the earth goes around the sun (heavily simplified) 
+where it starts and ends during the year, and clearly show the earth's tilt.

week5.md

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+Reflections week 5
+
+Vis: https://www.reddit.com/r/dataisbeautiful/comments/lzohca/tools_of_dedicated_dataviz_professionals_oc/
+
+Found this vis to be interesting sice I did not know what tools data vis professionals used exactly. 
+Looking at this chart gives me quite a few tools I could try that I have never used such as Mapbox.
+I like the seperation between job roles, it shows where people are using the tools.
+I have never seen this chart type before, I am not sure what it is called, but it clearly shows the percentage of job focus. 
+I do not see an easy way to judge how many people are using a particular tool, some bar thickness are close in size.
+The bar thickness also skews the y bar labels, there are some lines to show the name for each bar to aid in perception, but I still have to look over there to follow the line.
+OP could have changed the range on the thickness so the names could line up better.
+
+The vis combines multiple high-level explanations before showing the data, so it makes the chart easier to understand.
+The writing also helps explain the data, and what is included in the data set.
+I think the custom annoations help show some of the hidden detail, especially for the "Online tools" category.