From 6e82206795f37892d46e0b780bbc8bbb7f4119bc Mon Sep 17 00:00:00 2001 From: johvanniperez <64498761+johvanniperez@users.noreply.github.com> Date: Sun, 23 Jan 2022 13:23:23 -0500 Subject: [PATCH 1/2] Update week2.md Week2 reflection --- week2.md | 8 ++++++++ 1 file changed, 8 insertions(+) diff --git a/week2.md b/week2.md index e69de29..7d5258b 100644 --- a/week2.md +++ b/week2.md @@ -0,0 +1,8 @@ +### Johvanni Perez +### Data Viz - CS573 +### Professor Harrison +### Reflection 2 + +- This week I decided to do some exploring in Reddit for any cool or interesting data visualizations. This week I came across this interesting and thought provoking graph https://www.reddit.com/r/dataisbeautiful/comments/s75sm7/oc_us_life_expectancy_vs_of_taco_bell_locations/. While the graph aims to model the life expectancies of every state per number of Taco Bell stores per 100,000 people. While I agree that the graph does not fully encapsulate a complex topic such as life expectancy especially since it is a topic that has many societal, political, agronomical, and various other factors, this graph does provide some context worth exploring. For example, we can see that the states with the lowest life expectancies are the ones located in the south, southwest, and midwestern regions as some people in the subreddit comments pointed out. I feel that this is a valid correlation in the sense that some regions have adverse life expectancies because many people in those regions live in food deserts as explained in a documentary I personally know and like, *A Place at the Table*, as well as many other food/social justice documentaries. + +- I think that it is important to recognize that this graph does tell a complete story and I think that it is even more important to understand that Taco Bell is not the sole driving force behind low expectancy in certain states as the the creator themself stated. While some may find this graph to be a spurious correlation or a prime example of "correlation is not causation", I think that the graph conveys data in an amusing way that forces us to think and question what the data is trying to tell us. In this graph, I believe that the data is trying to tell us something more than just Taco Bell. That it is worth exploring fast food as whole and the political, societal, and agronomic forces that influences fast food chains and ultimately a person's health. In doing so, I think this graph could be supplemented with more meaningful data that create a much more nuanced an reputable story. From e30ae3b0187124aaa1321d019be61ed18727d072 Mon Sep 17 00:00:00 2001 From: johvanniperez <64498761+johvanniperez@users.noreply.github.com> Date: Sun, 23 Jan 2022 13:30:14 -0500 Subject: [PATCH 2/2] Update week2.md Updated grammatical errors --- week2.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/week2.md b/week2.md index 7d5258b..8721268 100644 --- a/week2.md +++ b/week2.md @@ -3,6 +3,6 @@ ### Professor Harrison ### Reflection 2 -- This week I decided to do some exploring in Reddit for any cool or interesting data visualizations. This week I came across this interesting and thought provoking graph https://www.reddit.com/r/dataisbeautiful/comments/s75sm7/oc_us_life_expectancy_vs_of_taco_bell_locations/. While the graph aims to model the life expectancies of every state per number of Taco Bell stores per 100,000 people. While I agree that the graph does not fully encapsulate a complex topic such as life expectancy especially since it is a topic that has many societal, political, agronomical, and various other factors, this graph does provide some context worth exploring. For example, we can see that the states with the lowest life expectancies are the ones located in the south, southwest, and midwestern regions as some people in the subreddit comments pointed out. I feel that this is a valid correlation in the sense that some regions have adverse life expectancies because many people in those regions live in food deserts as explained in a documentary I personally know and like, *A Place at the Table*, as well as many other food/social justice documentaries. +- This week I decided to do some exploring in Reddit for any cool or interesting data visualizations. This week I came across this interesting and thought-provoking graph https://www.reddit.com/r/dataisbeautiful/comments/s75sm7/oc_us_life_expectancy_vs_of_taco_bell_locations/. While the graph aims to model the life expectancies of every state per number of Taco Bell stores per 100,000 people. While I agree that the graph does not fully encapsulate a complex topic such as life expectancy especially since it is a topic that has many societal, political, agronomical, and various other factors, this graph does provide some context worth exploring. For example, we can see that the states with the lowest life expectancies are the ones located in the south, southwest, and midwestern regions as some people in the subreddit comments pointed out. I feel that this is a valid correlation in the sense that some regions have adverse life expectancies because many people in those regions live in food deserts as explained in a documentary I know and like, *A Place at the Table*, as well as many other food/social justice documentaries. -- I think that it is important to recognize that this graph does tell a complete story and I think that it is even more important to understand that Taco Bell is not the sole driving force behind low expectancy in certain states as the the creator themself stated. While some may find this graph to be a spurious correlation or a prime example of "correlation is not causation", I think that the graph conveys data in an amusing way that forces us to think and question what the data is trying to tell us. In this graph, I believe that the data is trying to tell us something more than just Taco Bell. That it is worth exploring fast food as whole and the political, societal, and agronomic forces that influences fast food chains and ultimately a person's health. In doing so, I think this graph could be supplemented with more meaningful data that create a much more nuanced an reputable story. +- I think that it is important to recognize that this graph does tell a complete story and I think that it is even more important to understand that Taco Bell is not the sole driving force behind low expectancy in certain states as the creator stated. While some may find this graph to be a spurious correlation or a prime example of "correlation is not causation", I think that the graph conveys data in an amusing way that forces us to think and question what the data is trying to tell us. In this graph, I believe that the data is trying to tell us something more than just Taco Bell. That it is worth exploring fast food as a whole and the political, societal, and agronomic forces that influence fast-food chains and ultimately a consumer's health. In doing so, I think this graph could be supplemented with more meaningful data that create a much more nuanced and reputable story.