DanielTLis4317

Daniel Tafmizi Dr. Friedman December 3, 2024 Lis 4317 Stock Exchange Analysis Github:  daniel.R/Work.R/LIS4370Rprog/4317FinalProjectCode.R at main · DanielDataGit/daniel.R Kaggle:  Global Stock Exchanges (Cap = 1 trillion+) 04-23      A stock exchange, securities exchange, or bourse is  an exchange where stockbrokers and traders can buy and sell securities, such as shares of stock, bonds and other financial instruments.   -   Stock exchange - Wikipedia     I was interested in seeing how global stock exchanges compare. I decided to construct my comparison by visualizing the market capitalization and performance of exchanges worth north of One trillion USD. Market capitalization is the sum of all securities in the exchange. This allows us to inspect the economic significance of the exchange. Performance is seen through the overall returns in the exchange. This allows us to inspect the quality and growth potential of the exchange. Through m...

Daniel Tafmizi Dr. Friedman November 24, 2024 Lis 4317 Module 13 Github:  daniel.R/Work.R/LIS4370Rprog/AnimationR.R at main · DanielDataGit/daniel.R     After some researching, I decided to use ggplot's gganimate package to create my visualization. I used this because I am familiar with ggplot's ecosystem. It offers a useful function for animating line plots. The " transition_reveal(year)" method, initiates a program that renders the data to appear by year. I applied this to my precious Stock Exchange Data and am pleased with the result. I initially colored the lines by the exchange name, but it was kind of difficult to link the legend and lines in real time. I decided to group by region to simplify the links between the data and the legend.      I like this design. A static graph is great for displaying complex data visualizations. However, the animation allows the data tell its own story.  

Daniel Tafmizi Dr. Friedman November 17, 2024 Lis 4317 Module 12 Github:  daniel.R/Work.R/LIS4370Rprog/networkAnalysis.R at main · DanielDataGit/daniel.R I enjoyed working on this network analysis. I was hoping to incorporate a similar element into my text mining final project, so this lesson acts a precursor to that. I used some reddit data that I retrieved from their API. I started by preprocessing the data, then I tokenized it, finally I found co-occurrences. The ggnet2 streamlines well with igraph. This allowed me to create a network analysis of co-occurrences from the reddit text. Further research will be done to add more elements to the graph. I would like to color in the nodes based on their connection to the keywords, "Kamala":Blue and "Trump":Red. Words related to both will be colored purple. 

Daniel Tafmizi Dr. Friedman November 4, 2024 Lis 4317 Module 11 Github:  daniel.R/Work.R/LIS4370Rprog/tufteviz.R at main · DanielDataGit/daniel.R Piwek's paper on Tufte visualized data in a refreshing and invigorating way. The art of the visualization really stood out. I honestly would rather go to a museum of Tufte's work then one with modern art. I used the ggplot minimal boxplot design to map my YOY stock exchange change. I think my graph needs some metadata to explain it further. I feel that most people will not understand what the graph is displaying. I think a label showing where each exchange's 2014 and 2024 values lie on the graph would help. I thought Tufte's graphs were not colorful enough, so I added color to mine.