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Final Project

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What Affects College Graduation Rates? LIS4317 Final Project After a long semester, we have reached the end of LIS4317, Visual Analytics! Using what I have gained from this course, I will establish work that will represent the numerous topics covered. The best way to accomplish this is by answering a question or issue that I am experiencing in my own life. In a few short days, I am expected to graduate from the University of South Florida. A challenging, but rewarding experience to which I will be forever grateful for. However, this brought upon the question of college graduation and the hurdles that come along with completion. What factors play into an individual graduating? How many people actually graduate from college? Do specific locations lead to more college graduates? How much does financial aid impact the graduation process? Using this dataset titled  College Completion Dataset , from Kaggle, I will answer these questions through various visualization methods.  The so...
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Module # 13

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Your assignment: Create a simple animation and discussion the result in your blog posting.  Reference to Yihui Xie's and animation R package website, click  here . A note, his package now available via CRAM repository and not GitHub.  For Bryan's blog posting on Animation in R, click  here   A note: In order to post your work on blog, you need to save your animation. The code for saving the image you created in R is as follow: saveGIF({     for (i in 1:10) plot(runif(10), ylim = 0:1) }) Working on this assignment was incredibly interesting. Before this module, I had no idea we could create animations through R studio.  Below is an animation for the code that was given for this assignment.  > saveGIF({ + for (i in 1:10) plot(runif(10), ylim = 0:1) + }) Now I will focus on my rendition of an animation through R.  The first animation I created was a relatively simple one where I demonstrated an investment account after a cons...
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Module # 12

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  Your assignment is to create your first visual Social Network analysis. You can select from any two platforms you feel more comfortable with. The first is called  NodeXL Links to an external site. . It is based on Microsoft Excel support platform. To download NodeXL package for Microsoft Excel click  here Links to an external site.  (Links to an external site.) Links to an external site. . Make sure you have Microsoft Excel in your computer. For full documentation on how to use NodeXL, click  here Links to an external site.  (Links to an external site.) Links to an external site. . ( https://www.smrfoundation.org/nodexl Links to an external site. ) The second option is using Rstudio. In my presentation, I used ggnet2: network visualization with ggplot2. The creator of this page is  Ehsan Aghaei.  (Links to an external site.) Links to an external site.  You can find the full documentation on his code o...
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Module # 11 assignment

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  Your assignment for module # 11 is to review   Dr. Piwek posting on Tufte and  C. Minard in R  http:// Links to an external site. and see if you can generate  one  of the visualization he discussed in his post that include: i. Marginal histogram scatter plot ii. Dot-dash plot in ggplot2 iii. Dot-dash plot in lattice Or  any one you like the best.  After installing the packages, I get a library that looks like this: > library(CarletonStats) > library(devtools) > library(epanetReader) > library(fmsb) > library(proto) > library(RCurl) > library(reshape) > library(reshape2) > library(ggplot2) > library(ggthemes) > library(latticeExtra) > library(MASS) > library(PerformanceAnalytics) > library(psych) > library(plyr) > library(prettyR) > library(plotrix) After plotting the given code below, I get a PDF that looks like this: This is a time series plot that shows the budget expenditures over the years....
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Module # 10 assignment

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Review the reading resources and post on your blog a new entry with your work with ggplot2 and time series (try yourself) and discuss the input of visualization on time series analysis. The dataset I will be using is titled "Video Game Sales" ( https://www.kaggle.com/datasets/anandshaw2001/video-game-sales ) The first plot I created deals with the amount of video game sales over the years. Using ggplot, I was able to establish a relationship of the total amount of video games sold over the course of forty years.  > ggplot(videoGameSales, aes(x = as.numeric(Year), y = Global_Sales)) + + geom_line(stat = "summary", fun = sum) + + labs(title = "Global Video Game Sales Over the Years", x = "Year", y = "Total Sales (millions)") The next plot was created with R-base graphics. This one was a little trickier without the use  of ggplot. More steps had to be incorporated such as the use of the aggregate function. I divided the code into s...
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