Posts

Final Project Spring 2018

Image
    I have always had a fascination for language and how it influences the world around us. When researching what to do for my final project I knew that I had to do something related to that idea. Being a German speaker in the United States, I wondered how my situation compared to the world around me. After ding much research I came up with some data to put into my visualization. After questing the internet to find a data set I came across a 2016 American Community Survey of the amount of languages spoken by people in the United States. While this data was impressive, I wanted something else to compare it to to get more of my point across. Getting data for how many people speak a certain language around the world was not as easy. I eventually found a data set from Ethnologue of data from over 7,000 languages. I decided to just stick to the top 20 languages for both the United States and the World population. Here are the two datasets     The next step...
Post a Comment
Read more

Module # 12 Social Network Assignment

Image
    This week, we were asked to create our first visual social network analysis. We were given the choice to use either NodeXL or RStudio and I chose to use the latter. The syntax was fairly simple and installing the packages for the code was no trouble at all. Once I ran the code, it displayed the nice, simple design I have below. The code is from an example given by Ehsan Ahgaei on his GitHub page. The most challenging part was to get the packages to run, I eventually had to install it as a standalone package and then it worked fine. I really like the looks of these designs and I am looking forward to doing more in the future.
Post a Comment
Read more

Module # 11 Edward R. Tufte - Modern Pioneer in the Field of Data Visualization

Image
    This week we learned of Edward Tufte and followed his instructions on how to create a dot-dash plot. I chose to create one in ggplot2 and it turned out pretty well. Once I installed all the packages and ran them in the background, I was able to plug in the code and run it smoothly. Below is an image depicting the code, the packages running in the background, and the final design.
Post a Comment
Read more

Module # 10 Time Series and Trends Through Visualization Lens

Image
   This week we worked with coding in R to create a time series graph. We were given multiple examples and we could either replicate the examples or create our own. Since I am still getting used to how R works, I just decided to copy the code from the very first example.  Here is the code for reference:  >hotdogs <- read_csv("http://datasets.flowingdata.com/hot-dog-contest-winners.csv") >head(hotdogs) >(library("ggplot2")) >colors <- ifelse(hotdogs$New.record == 1, "darkred", "grey") barplot(hotdogs$Dogs.eaten, names.arg = hotdogs$Year, col=colors, border=NA, main = "Nathan's Hot Dog Eating Contest Results, 1980-2010",  xlab="Year", ylab="Hot dogs and buns (HDBs) eaten")     The reason I chose this example was because I feel it represented what a time series graph is supposed to be very well. The red represents a year when a new record was put into place and it shows the progression of t...
Post a Comment
Read more

Module 8 - Correlation and Analysis

Image
    The data I chose to represent was whether or not there was a correlation between the height of men and their self esteem. The height was measured in inches and the self esteem was based on an average of 10 on a 1-to-5 grading scale determined by the person being interviewed. Following Fews' advice on creating the graph, I determined to follow the principle of making the graph have distinguished colors to give it more of a visual appeal.     As you can see, from this specific survey of 20 males, there seems to be a correlation between the height of a man and his self esteem. As the height of a male increases, so does the rating of self esteem. Now this may not be the case if a larger survey was taken, but this is just a visual representation of the data at hand.
Post a Comment
Read more

Module 7 Distribution Analysis

Image
    I used Plotly to design this graph and I think that it turned out pretty well. It clearly shows the distribution over time by showing the rise, peak, and fall of the distribution. The colors I chose ended up looking very nice together and can be clearly differentiated. Overall, I think this design represents the data well. 
Post a Comment
Read more

Visual Deviation Analytics

Image
    When comparing the two graphs you can clearly see the deviation between the two of them. Below is a representation of the US price of palm oil.     And after that, here is the representation of the Global price of palm oil.     When you put the two of the data sets together, that is when you can really see the vast amount of between them.     The Price of the US Palm Oil is so far below the Global price, it is almost hard to tell we are comparing the two. You see, without the deviation analytic design, the data sets seem similar. However, when put together you can just see how different they are.
Post a Comment
Read more