Due: March 30 by 11:59pm
Submit: To submit this assignment, create a zip file of all the files in your R project folder for this assignment. Name the zip file
hw9-netID.zip, replacingnetIDwith your netID (e.g.,hw9-jph.zip). Use this link to submit your file.Weight: This assignment is worth 5% of your final grade.
Purpose: The purposes of this assignment are:
- To practice creating data frames in R.
- To practice merging and slicing data frames in R.
Assessment: Each question indicates the % of the assignment grade, summing to 100%. The credit for each question will be assigned as follows:
- 0% for not attempting a response.
- 50% for attempting the question but with major errors.
- 75% for attempting the question but with minor errors.
- 100% for correctly answering the question.
The reflection portion is always worth 10% and graded for completion.
Rules:
- Problems marked SOLO may not be worked on with other classmates, though you may consult instructors for help.
- For problems marked COLLABORATIVE, you may work in groups of up to 3 students who are in this course this semester. You may not split up the work – everyone must work on every problem. And you may not simply copy any code but rather truly work together and submit your own solutions.
Download and use this template for your assignment. Inside the “hw9” folder, open and edit the R script called “hw9.R” and fill out your name, GW Net ID, and the names of anyone you worked with on this assignment.
Using good style
For this assignment, you must use good style to receive full credit. Follow the best practices described in this style guide.
Write R code to install the dslabs package from
CRAN, then write code to load the package. Write some code to preview
and inspect the movielens data frame that gets loaded when
you load the package 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)?Write R code to read in the prisoners2019.csv file
located in the data folder. Store the object as
df. Write some code to preview and inspect the
df data frame 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:
Read and reflect on next week’s readings on data wrangling. Afterwards, in a
comment (#) in your R file, write a short reflection on
what you’ve learned and any questions or points of confusion you have
about what we’ve covered thus far. This can just few a few sentences
related to this assignment, next week’s readings, things going on in the
world that remind you something from class, etc. If there’s anything
that jumped out at you, write it down.