a4-karoad-kenny-rhodes

EUData.csv

@@ -0,0 +1,28 @@
+Name,Accession,Population,Areakm2,GDP,gdpPerCapita,Currency,Gini,HDI,MEPs,Languages
+Austria Austria,1995,"8,792,500",83855,447718,"55,406",euro,29.1,0.908,19,German
+Belgium Belgium,Founder,"11,365,834",30528,517609,"50,114",euro,33,0.916,21,Dutch
+Bulgaria Bulgaria,2007,"7,101,859",110994,66250,"23,741",lev,29.2,0.813,17,Bulgarian
+Croatia Croatia,2013,"4,154,213",56594,60702,"27,681",kuna,29,0.831,12,Croatian
+Cyprus Cyprus[a],2004,"854,802",9251,24280,"39,079",euro,31.2,0.869,6,Greek
+Czech Republic Czech Republic,2004,"10,467,628",78866,246953,"40,293",koruna,25.8,0.9,21,Czech[c]
+Denmark Denmark[d],1973,"5,743,947",43075,347176,"57,781",krone,24.7,0.929,14,Danish
+Estonia Estonia,2004,"1,315,635",45227,31038,"37,033",euro,36,0.871,7,Estonian
+Finland Finland[e],1995,"5,577,282",338424,269654,"49,334",euro,26.9,0.92,14,Finnish
+France France[f],Founder,"67,024,633","632,833[8]",2707074,"45,454",euro,32.7,0.901,79,French
+Germany Germany,Founder[g],"83,149,300",357386,3863344,"53,571",euro,28.3,0.936,96,German
+Greece Greece,1981,"10,757,293",131990,214012,"29,045",euro,34.3,0.87,21,Greek
+Hungary Hungary,2004,"9,797,561",93030,170407,"32,434",forint,30,0.838,21,Hungarian
+Republic of Ireland Ireland,1973,"4,774,833",70273,384940,"89,383",euro,34.3,0.938,13,English
+Italy Italy,Founder,"61,219,113",301338,1988636,"40,065",euro,36,0.892,76,Italian
+Latvia Latvia,2004,"1,950,116",64589,35045,"30,579",euro,35.7,0.847,8,Latvian
+Lithuania Lithuania,2004,"2,847,904",65200,53641,"38,605",euro,35.8,0.858,11,Lithuanian
+Luxembourg Luxembourg,Founder,"589,370",2586.4,69453,"112,875",euro,30.8,0.904,6,French
+Malta Malta,2004,"440,433",316,14859,"43,086",euro,25.8,0.878,6,Maltese
+Netherlands Netherlands[i],Founder,"17,220,721",41543,902355,"57,101",euro,30.9,0.931,29,Dutch
+Poland Poland,2004,"37,972,964",312685,565854,"33,739",złoty,34.9,0.865,52,Polish
+Portugal Portugal[k],1986,"10,291,027","92,212[10]",236408,"33,131",euro,32.1[,0.847,21,Portuguese
+Romania Romania,2007,"19,638,309",238391,243698,"30,141",leu,31.5,0.811,33,Romanian
+Slovakia Slovakia,2004,"5,435,343",49035,106552,"32,184",euro,25.8,0.855,14,Slovak
+Slovenia Slovenia,2004,"2,065,895",20273,54154,"38,506",euro,31.2,0.896,8,Slovene
+Spain Spain[l],1986,"46,528,966",504030,1397870,"38,143",euro,32,0.904,59,Spanish
+Sweden Sweden,1995,"10,080,000",449964,528929,"52,477",krona,25,0.933,21,Swedish

PRCData.csv

@@ -0,0 +1,35 @@
+Provice,Rank,gdpPerCapita
+China (mainland),0,"10,276"
+Macao,1,"84,096"
+Hong Kong,2,"48,713"
+Beijing,3,"23,805"
+Shanghai,4,"22,799"
+Jiangsu,5,"17,918"
+Zhejiang,6,"15,601"
+Fujian,7,"15,531"
+Guangdong,8,"13,651"
+Tianjin,9,"13,100"
+Hubei,10,"11,218"
+Chongqing,11,"10,992"
+Shandong,12,"10,242"
+Inner Mongolia,13,"9,836"
+Shaanxi,14,"9,661"
+Anhui,15,"8,479"
+Hunan,16,"8,341"
+Liaoning,17,"8,290"
+Hainan,18,"8,191"
+Henan,19,"8,174"
+Sichuan,20,"8,085"
+Xinjiang,21,"7,868"
+Ningxia,22,"7,859"
+Jiangxi,23,"7,707"
+Qinghai,24,"7,100"
+Tibet,25,"7,089"
+Yunnan,26,"6,950"
+Guizhou,27,"6,731"
+Hebei,28,"6,719"
+Shanxi,29,"6,628"
+Jilin,30,"6,302"
+Guangxi,31,"6,228"
+Heilongjiang,32,"5,245"
+Gansu,33,"5,083"

README.md

@@ -1,64 +1,48 @@
-Assignment 4 - DataVis Remix + Multiple Views
-===
 
-The primary aim of this assignment is to showcase your **individual** skills at critiquing, redesigning, and extending visualizations on the web.
-
-### Your Task
-
-Your task is to choose a visualization, remix it, and add at least two linked-views.
-
-By remix, we mean:
-
-- Critique the original vis
-- Redesign some aspect of it, using better task abstractions, encodings, etc.
-- Implement your redesign
-
-Examples of remixes include:
-- taking a static choropleth map with a bad color scale, implementing a new version in d3, adding interactivity, and improving the color scale to show the original data in a more effective way
-- finding a poorly designed or hard-to-use interactive visualization, and making a new version with better interaction design, such as features that enable the user to explore the data in new ways, by adding new views
-
-By two linked views, we mean:
-
-- Have two separate visualizations (likely separate SVGs), that visualize data using different idioms
-- Linked views means that interacting in one updates the other, and vice versa. Think about the interaction flow that leads to good user experience and aligns with tasks you've identified.
-
-Examples of linked views include:
-- A large central map or scatterplot, with ancillary histograms that can be used to filter-- perhaps time or other dimensions
+3. Your writeup (readme.md in the repo) should contain the following:
 
+- Working link to the visualization hosted on gh-pages or other external sources.
+- Concise description and screenshot of your visualization.
+- Description of the technical achievements you attempted with this visualization.
+- Description of the design achievements you attempted with this visualization.
 
-**Remember: the intent of this assignment is for you to demonstrate your understanding of the theory (e.g. concepts from Munzner's book) and practice (d3, and any tools you use for exploring the data) of visualization.**
 
-Incorporating a brief writeup with your remix is a good idea.
-Communicate what the original vis was, what the major issues were, and what new things can be seen with your redesign.
-You could have text directly on the page, an "info" button, an about page, etc.
+<h1>
+    Assignment 4
+</h1>
+<h2>
+    Viz can be found at: http://www.kennyrhodes.com/projects/cs4802/project4
+</h2>
 
-### More on Two Linked Views 
-One of the most powerful techniques for mitigating the shortcomings of a given visualization is to link it with other views.
+<h2>
+    Original Viz: 
+</h2>
 
-Linking a map to a bar or scatterplot, for instance, may allow you to overcome the shortcomings of a map.
+[Viz Display from link](week1Viz.PNG)
 
-In general, linking visualizations allows you to explore different parts of the data between views, and mitigates the shortcomings of a given view by pairing it with other views.
+<h3>
+    The original viz of the USA, China, and Europes GDP had a lot of issues with scale as the range was from 1 million to a 4 trillion.
+</h3>
 
-For this assignment, we want to see at least two linked views, in that interactions in one view updates the other, and vice versa. Many multiple views visualizations use more than two views, so consider such directions as possibilities for tech/design achievements. Be sure to think about what views work best for given tasks, and try to iterate/prototype if possible.
+<h2>
+    New Viz:
+</h2>
 
-Requirements
----
+<h3>
+    My new viz used a ranking system to color the states / countries by region and then allows users to click on regions to add them to the chart
+</h3>
 
-0. Your code should be forked from the GitHub repo and linked using GitHub pages.
-1. Your project should load a dataset you found on the web from the vis you're remixing. You may extract the data by sight if necessary. Put this file in your repo.
-2. Your project should use d3 to build a visualization of the dataset. 
-3. Your writeup (readme.md in the repo) should contain the following:
+<h2>
+    Technical Achievements:
+</h2>
 
-- Working link to the visualization hosted on gh-pages or other external sources.
-- Concise description and screenshot of your visualization.
-- Description of the technical achievements you attempted with this visualization.
-- Description of the design achievements you attempted with this visualization.
+<h3>
+    This project involved a lot of learning about d3 maps
+</h3>
 
-Extra Links
----
+<h2>
+    Design Achievements:
+</h2>
 
-- https://observablehq.com/@philippkoytek/d3-part-3-brushing-and-linking
-- https://bl.ocks.org/john-guerra/raw/2c00b2d675a6bf1c84a7b140f4536b0d/
-- https://github.com/d3/d3-brush
-- https://observablehq.com/collection/@d3/d3-brush
-- https://observablehq.com/@d3/focus-context?collection=@d3/d3-brush
+<h3>
+</h3>

USData.csv

@@ -0,0 +1,57 @@
+Rank,State,GDP,PercentNational,gdpPerCapita,Region
+1, California,3120386,15,79261,West
+2, Texas,1772132,8,60357,South
+3, New York,1705127,8,88180,Northeast
+4, Florida,1111614,5,51147,South
+5, Illinois,875671,4,69566,Midwest
+6, Pennsylvania,788500,4,61682,Northeast
+7, Ohio,683460,3,58449,Midwest
+8, Washington,632013,3,82147,West
+9, Georgia,627667,3,58605,South
+10, New Jersey,625659,3,70438,Northeast
+11, North Carolina,594126,3,56045,South
+12, Massachusetts,590307,3,85631,Northeast
+13, Virginia,557986,3,64953,South
+14, Michigan,524828,3,52658,Midwest
+15, Maryland,427616,2,70612,Northeast
+16, Colorado,394271,2,67887,West
+17, Minnesota,379388,2,67071,Midwest
+18, Indiana,379293,2,56149,Midwest
+19, Arizona,378297,2,50973,West
+20, Tennessee,369063,2,53589,South
+21, Wisconsin,344500,2,59064,Midwest
+22, Missouri,325841,2,52968,Midwest
+23, Connecticut,283601,1,79730,Northeast
+24, Oregon,253849,1,59848,West
+25, South Carolina,245473,1,47043,South
+26, Louisiana,244577,1,52649,South
+27, Alabama,228062,1,46339,South
+28, Kentucky,213169,1,47611,South
+29, Utah,198630,1,61119,West
+30, Iowa,195353,1,61560,Midwest
+31, Oklahoma,186883,1,46886,South
+32, Nevada,175509,1,55925,West
+33, Kansas,175465,1,60218,Midwest
+34, District of Columbia,144653,1,191445,South
+35, Arkansas,130709,1,43130,South
+36, Nebraska,129761,1,66971,Midwest
+37, Mississippi,115900,1,39065,South
+38, New Mexico,100777,1,47845,West
+39, Puerto Rico,104989,0,31651,South
+40, Hawaii,89866,1,63870,West
+41, New Hampshire,86319,0,63178,Northeast
+42, Idaho,85552,0,46828,West
+43, West Virginia,74511,0,41747,Northeast
+44, Delaware,76468,0,77490,Northeast
+45, Maine,67129,0,49719,Northeast
+46, Rhode Island,61081,0,57780,Northeast
+47, South Dakota,55243,0,61881,Midwest
+48, North Dakota,54044,0,70613,Midwest
+49, Montana,51934,0,48061,West
+50, Alaska,50413,0,68949,West
+51, Wyoming,36000,0,61814,West
+52, Vermont,33278,0,53382,Northeast
+53, Guam,5920,0,35600,West
+54, U.S. Virgin Islands,3855,0,37000,South
+55, Northern Mariana Islands,1323,0,24500,West
+56, American Samoa,636,0,11200,West

VizCode/EUData.csv

@@ -0,0 +1,28 @@
+Name,Accession,Population,Areakm2,GDP,gdpPerCapita,Currency,Gini,HDI,MEPs,Languages
+Austria,1995,8792500,83855,447718,55406,euro,29.1,0.908,19,German
+Belgium,1993,11365834,30528,517609,50114,euro,33,0.916,21,Dutch
+Bulgaria,2007,7101859,110994,66250,23741,lev,29.2,0.813,17,Bulgarian
+Croatia,2013,4154213,56594,60702,27681,kuna,29,0.831,12,Croatian
+Cyprus,2004,854802,9251,24280,39079,euro,31.2,0.869,6,Greek
+Czech Republic,2004,10467628,78866,246953,40293,koruna,25.8,0.9,21,Czech
+Denmark,1973,5743947,43075,347176,57781,krone,24.7,0.929,14,Danish
+Estonia,2004,1315635,45227,31038,37033,euro,36,0.871,7,Estonian
+Finland,1995,5577282,338424,269654,49334,euro,26.9,0.92,14,Finnish
+France,1993,67024633,632833,2707074,45454,euro,32.7,0.901,79,French
+Germany,1993,83149300,357386,3863344,53571,euro,28.3,0.936,96,German
+Greece,1981,10757293,131990,214012,29045,euro,34.3,0.87,21,Greek
+Hungary,2004,9797561,93030,170407,32434,forint,30,0.838,21,Hungarian
+Republic of Ireland,1973,4774833,70273,384940,89383,euro,34.3,0.938,13,English
+Italy,1993,61219113,301338,1988636,40065,euro,36,0.892,76,Italian
+Latvia,2004,1950116,64589,35045,30579,euro,35.7,0.847,8,Latvian
+Lithuania,2004,2847904,65200,53641,38605,euro,35.8,0.858,11,Lithuanian
+Luxembourg,1993,589370,2586,69453,112875,euro,30.8,0.904,6,French
+Malta,2004,440433,316,14859,43086,euro,25.8,0.878,6,Maltese
+Netherlands,1993,17220721,41543,902355,57101,euro,30.9,0.931,29,Dutch
+Poland,2004,37972964,312685,565854,33739,złoty,34.9,0.865,52,Polish
+Portugal,1986,10291027,92212,236408,33131,euro,32.1,0.847,21,Portuguese
+Romania,2007,19638309,238391,243698,30141,leu,31.5,0.811,33,Romanian
+Slovakia,2004,5435343,49035,106552,32184,euro,25.8,0.855,14,Slovak
+Slovenia,2004,2065895,20273,54154,38506,euro,31.2,0.896,8,Slovene
+Spain,1986,46528966,504030,1397870,38143,euro,32,0.904,59,Spanish
+Sweden,1995,10080000,449964,528929,52477,krona,25,0.933,21,Swedish

VizCode/PRCData.csv

@@ -0,0 +1,35 @@
+Provice,Rank,gdpPerCapita
+China,0,10276
+Macao,1,84096
+Hong Kong,2,48713
+Beijing,3,23805
+Shanghai,4,22799
+Jiangsu,5,17918
+Zhejiang,6,15601
+Fujian,7,15531
+Guangdong,8,13651
+Tianjin,9,13100
+Hubei,10,11218
+Chongqing,11,10992
+Shandong,12,10242
+Inner Mongolia,13,9836
+Shaanxi,14,9661
+Anhui,15,8479
+Hunan,16,8341
+Liaoning,17,8290
+Hainan,18,8191
+Henan,19,8174
+Sichuan,20,8085
+Xinjiang,21,7868
+Ningxia,22,7859
+Jiangxi,23,7707
+Qinghai,24,7100
+Tibet,25,7089
+Yunnan,26,6950
+Guizhou,27,6731
+Hebei,28,6719
+Shanxi,29,6628
+Jilin,30,6302
+Guangxi,31,6228
+Heilongjiang,32,5245
+Gansu,33,5083

VizCode/USData.csv

@@ -0,0 +1,53 @@
+Rank,State,GDP,PercentNational,gdpPerCapita,Region
+1,California,3120386,15,79261,West
+2,Texas,1772132,8,60357,South
+3,New York,1705127,8,88180,Northeast
+4,Florida,1111614,5,51147,South
+5,Illinois,875671,4,69566,Midwest
+6,Pennsylvania,788500,4,61682,Northeast
+7,Ohio,683460,3,58449,Midwest
+8,Washington,632013,3,82147,West
+9,Georgia,627667,3,58605,South
+10,New Jersey,625659,3,70438,Northeast
+11,North Carolina,594126,3,56045,South
+12,Massachusetts,590307,3,85631,Northeast
+13,Virginia,557986,3,64953,South
+14,Michigan,524828,3,52658,Midwest
+15,Maryland,427616,2,70612,Northeast
+16,Colorado,394271,2,67887,West
+17,Minnesota,379388,2,67071,Midwest
+18,Indiana,379293,2,56149,Midwest
+19,Arizona,378297,2,50973,West
+20,Tennessee,369063,2,53589,South
+21,Wisconsin,344500,2,59064,Midwest
+22,Missouri,325841,2,52968,Midwest
+23,Connecticut,283601,1,79730,Northeast
+24,Oregon,253849,1,59848,West
+25,South Carolina,245473,1,47043,South
+26,Louisiana,244577,1,52649,South
+27,Alabama,228062,1,46339,South
+28,Kentucky,213169,1,47611,South
+29,Utah,198630,1,61119,West
+30,Iowa,195353,1,61560,Midwest
+31,Oklahoma,186883,1,46886,South
+32,Nevada,175509,1,55925,West
+33,Kansas,175465,1,60218,Midwest
+34,District of Columbia,144653,1,191445,South
+35,Arkansas,130709,1,43130,South
+36,Nebraska,129761,1,66971,Midwest
+37,Mississippi,115900,1,39065,South
+38,New Mexico,100777,1,47845,West
+39,Puerto Rico,104989,0,31651,South
+40,Hawaii,89866,1,63870,West
+41,New Hampshire,86319,0,63178,Northeast
+42,Idaho,85552,0,46828,West
+43,West Virginia,74511,0,41747,Northeast
+44,Delaware,76468,0,77490,Northeast
+45,Maine,67129,0,49719,Northeast
+46,Rhode Island,61081,0,57780,Northeast
+47,South Dakota,55243,0,61881,Midwest
+48,North Dakota,54044,0,70613,Midwest
+49,Montana,51934,0,48061,West
+50,Alaska,50413,0,68949,West
+51,Wyoming,36000,0,61814,West
+52,Vermont,33278,0,53382,Northeast