Due: Sep 07 by 11:59pm
Weight: This assignment is worth 3% of your final grade.
Purpose: The purpose of this assignment is to get more familiar with R and RStudio and to develop some basic strategies for working with data in R.
Assessment: This assignment is graded using a check system:
- ✔+ (110%): Responses shows phenomenal thought and engagement with the course content. I will not assign these often.
- ✔ (100%): Responses are thoughtful, well-written, and show engagement with the course content. This is the expected level of performance.
- ✔− (50%): Responses are hastily composed, too short, and/or only cursorily engages with the course content. This grade signals that you need to improve next time. I will hopefully not assign these often.
Notice that this is essentially a pass/fail system. I’m not grading your writing ability and I’m not counting the number of words you write - I’m looking for thoughtful engagement.
If you haven’t yet, go to the Course Software page and install all the software we’ll need for this course. You’ll need these tools for this assignment.
Download and edit this template when working through this assignment.
Open up a notebook (physical, digital…whatever you take notes in best), and take notes while you go through these readings:
RStudio offers many excellent primers to get up and running quickly in . Running through these exercises will help prepare you for class next week:
Reflect on what you’ve learned while going through these readings and exercises. Is there anything that jumped out at you? Anything you found particularly interesting or confusing? Write a few sentences in the template you downloaded for this assignment, then create a zip file of everything in your R Project folder and submit the zip file in the “Assignment Submission” page on Blackboard.
Not required, but probably helpful, especially if you’re new to .
Write R code to install the dslabs package from
CRAN, then write code to load the library. Write some code to preview
and inspect the movielens data frame that gets loaded when
you load the library using some of the techniques we saw in class. For
each of the following questions, write code to find your answer and
leave a detailed response in a comment:
For each of the following questions, write code to find your answer and leave a detailed response in a comment:
title (in terms of numbers of letters in the title)?The vast majority of the time, you will install external packages
using the install.packages() function. This installs
packages from the Comprehensive R
Archive Network (CRAN), where most packages are published. But you
can also install packages that are under development or haven’t been
published to CRAN yet. Most of the time, these packages are hosted on
GitHub - an online platform for sharing code (it’s also where all of the
files that make up this website are stored).
To install a package from GitHub, you first need to install the
remotes library. Then you can use the
remotes::install_github()` function to install packages
directly from GitHub. To try this out, install the
remotes library, then trying installing the
BRRR package:
remotes::install_github("brooke-watson/BRRR")Note: Packges on GitHub are in development and often require other packges to work. So if you get an installation error about some other package dependency, try restarting your R session and try again.
Not sure what this package does? Well, one of the other nice things
about packages listed on GitHub is the authors tend to write detailed
descriptions - check out the GitHub page for the BRRR
package. Then try using the BRRR::skrrrahh() function
with different number arguments (turn your volume up). In the
#welcome channel on slack, post your favorite argument to
skrrrahh() (mine is 24).