My Goal

My goal was to learn what R Markdown was, and begin to experiment and explore what I could do with it. Being a total beginner to coding, my strategy to achieve this goal was to keep up with the content in the video tutorials and recreate some of the coding functions on my own.

Challenges

The most of my challenges have come from the precision required with some functions. Often I would forget to add, or add too many spaces which caused numerous error messages.

While making a graph I accidentally clicked the down arrow numerous times to try move around my markdown however this deleted lots of my code! This problem actually lead to a very useful reminder - that the up and down arrows take you backwards and forwards in your progress. I therefore learned that when I wanted to clear my overwhelming document I could click control “l” and the up arrow!

Making plots is the most challenging thing for me so far, with all the different coding elements required.

My Successes

I was able to create a readable and clear docuent!

Here I learnt how to add equations: \[a^2+b^2=c^2\] Here is an image I have inserted:

I enjoyed learning how to make plots, and playing around with the aesthetics. Here is my attempt I made at making a plot on my own from the data given in the tutorials. As you can see I played around with different aesthetics.

library(tidyverse)
## ── Attaching packages ─────────────────────────────────────── tidyverse 1.3.0 ──
## ✓ ggplot2 3.3.3     ✓ purrr   0.3.4
## ✓ tibble  3.0.6     ✓ dplyr   1.0.4
## ✓ tidyr   1.1.2     ✓ stringr 1.4.0
## ✓ readr   1.4.0     ✓ forcats 0.5.1
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## x dplyr::filter() masks stats::filter()
## x dplyr::lag()    masks stats::lag()
picture <- ggplot(data=mpg) + geom_point(mapping = aes(
  x = displ, y = hwy,colour = cyl, size = cty))

print(picture)

Next Steps in my coding journey

Here is a list of what I would like to achieve in the upcoming weeks:

  • Finish the Data Visualisation tutorials
  • Create plots from different data sets
  • Continue to explore and play around with different codes.