knitr::opts_chunk$set(echo = TRUE)

Knit early and often!!

Save your file somewhere where you can find it in a reasonably tidy folder structure!

  1. Read in the dataset class.csv and generate a boxplot showing the distribution of each of the skills. Edit one or more of the visual aspects of this plot (Ex: change the color, add a title, change the ylim, add the outliers, make the x-axis labels vertical for a challenge in base R.)

Hadley Wickham and Lisa Stryjewski’s paper on

{r eval = TRUE}. print("Hello")

df <- read.csv('dat/classProfiles.csv')

# THE OG BOXPLOT
boxplot(df)

# THE VERSION WITH THE NICE LOOKING LABELS
# FROM: https://www.tenderisthebyte.com/blog/2019/04/25/rotating-axis-labels-in-r/
par(mar = c(6.1, 4.1, 4.1, 4.1), # change the margins
    lwd = 2, # increase the line thickness
    cex.axis = 1.2 # increase default axis label size
    )

boxplot(df, xaxt = "n", yaxt = "n")

## Draw x-axis without labels.
axis(side = 1, labels = FALSE)

## Draw y-axis.
axis(side = 2,
     ## Rotate labels perpendicular to y-axis.
     las = 2,
     ## Adjust y-axis label positions.
     mgp = c(3, 0.75, 0))

## Draw the x-axis labels.
text(x = 1:length(df),
     ## Move labels to just below bottom of chart.
     y = par("usr")[3] - 0.45,
     ## Use names from the data list.
     labels = names(df),
     ## Change the clipping region.
     xpd = NA,
     ## Rotate the labels by 35 degrees.
     srt = 35,
     ## Adjust the labels to almost 100% right-justified.
     adj = 0.965,
     ## Increase label size.
     cex = 1.2)

# THE VERSION WITH POINTS

boxplot(df,col = "white")
# Points
stripchart(df,              # Data
           method = "jitter", # Random noise
           pch = 19,          # Pch symbols
           col = 4,           # Color of the symbol
           vertical = TRUE,   # Vertical mode
           add = TRUE)        # Add it over

  1. Write at minimum two paragraphs about your goals for the class and for your work in data science more broadly. (No more than a page please.) This can be an elaboration on one element of the skills listed above. Tell me the story of how you came to be a fledgling data scientist. What made you sign up for this course? What brought you to Baylor?

How I became a data scientist before there was such a thing

  1. I started out at BU as a pre med major after spending the summer at MD Anderson Cancer Center. I learned how to run Western blots, but I found I didn’t love biology. Later that year, I started working in a physics lab after waxing poetic about swirls in cups of tea 🫖. I studied chaos and complexity science and read everything I could find about the Santa Fe Insitute.

  2. I worked at Mission Waco and Gospel Cafe, and I felt the gulf between the questions I asked downtown and those I asked in the physics lab keenly. I started searching Google Scholar for paper on poverty and physics and found Nathan Eagle’s work on human mobility from cell phone data. I tracked down that dataset and went to England to work with a similar data set studying the mathematics of epidemics.

Currently, I’m wrestling with the gulf between human flourishing and online datified systems that seem designed for anything but. So I read a lot of Wendell Berry’s Manifesto Mad Farmer Libeartion Front

So, friends, every day do something that won’t compute.

an image of me generated by canva

Issues with implicit AI photo bias
  • AI can’t tell us where we’re going. It can only tell us where we’ve been, which frankly, is old hat.
  • photo generators can reinforce tropes about race, class, gender, wealth, intelligence, religion
  • turned all my photos into blue-eyed portraits and obviously removed my glasses
  1. Format your paragraphs with some markdown. For full credit you must use at least five of the following formatting elements:
  • An ordered list
  • An unordered list
  • A math formula
  • Bold/underlined/italicized text
  • An embedded link
  • A block quote
  • Sections and subsections
  • A table of contents.

Feel free to be creative with this! For example: block quote your personal manifesto, give me an ordered list of ideal elements of the perfect coding environment!

  1. (Optional but fun) Alter the theme in your YAML heading with Bootswatch https://bookdown.org/yihui/rmarkdown/html-document.html#appearance-and-style

  2. Knit to HTML and if you like, upload the folder with your files to Netlify Drop to publish to the web

  3. Knit to PDF and submit to Canvas