UCLA Syllabus:
UA Syllabus:
Resources:
Download class folder structure zip file
Programming/Data Science Resources
Problem Set Resources and Guideline
RStudio cheat sheets zip file
RStudio cheat sheets link
Class Textbook: R for Data Science
R Markdown: The Definitive Guide
Software Installation and Knitting Problems
Things to do before class
beamer header.tex
UCLA Links to Lecture materials:
Lecture 1.1 pdf
Lecture 1.1 Rmd
Lecture 1.2 pdf
Lecture 1.2 Rmd
Lecture 1.2 R
Images (image files that will be called by lecture .Rmd)
unzip and save these files in the same folder you saved the lectures
UA Links to Lecture materials:
Lecture 1.1 pdf
Lecture 1.1 Rmd
Lecture 1.2 pdf
Lecture 1.2 Rmd
Readings:
GW 1,
GW 2,
GW 4,
GW 20.1-20.3
Links to Problem Set:
UCLA Links to Lecture materials:
UA Links to Lecture materials:
Readings:
GW 5.1-5.4
XAG 3.1
RMarkdown Reference Guide [spend 15 min reviewing]
Links to Problem Set:
UCLA Links to Lecture materials:
UA Links to Lecture materials:
Readings (read after lecture):
Wickham 2014, Advanced R, sections 4.1-4.4
Teach youself R in 24 Hours, Hour 11, section on “Sorting” [about 3 pages]
Note: data frame “airquality” used in this section is an internal dataset that you can use anytime you open R
Links to Problem Set:
UCLA Links to Lecture materials:
UA Links to Lecture materials:
Readings:
Links to Problem Set:
UCLA Links to Lecture materials:
UA Links to Lecture materials:
Readings:
Links to Problem Set:
UCLA Links to Lecture materials:
UA Links to Lecture materials:
Readings:
GW 15.1 - 15.2 (factors) [this is like 2-3 pages]
GW 20.6 - 20.7 (attributes and augmented vectors)
GW 10 (tibbles) [this is like 3-4 pages]
[OPTIONAL] GW 15.3 - 15.5 (remainder of "factors" chapter)
Links to Problem Set:
UCLA Links to Lecture materials:
UA Links to Lecture materials:
Readings:
Data Cleaning Guidelines pdf
Data Cleaning Guidelines Rmd
note: Don't worry about topics we haven’t covered yet (e.g,. Acquiring data, merging, reshaping)
Links to Problem Set:
UCLA Links to Lecture materials:
Lecture 8 html
Lecture 8 Rmd
Lecture 8 ppt
UA Links to Lecture materials:
Readings:
Grolemund and Wickham 12.1 – 12.2 [required]
Pivoting data vignette [required]
Grolemund and Wickham 12.3 – 12.4 [optional]
Grolemund and Wickham 12.5 – 12.7 [required]
Links to Problem Set:
UCLA Links to Lecture materials:
UA Links to Lecture materials:
Readings:
Link to Problem Set:
UCLA Links to Lecture materials:
Lecture 10 pdf
Lecture 10 Rmd
Data zip folder
UA Links to Lecture materials:
Readings:
Link to Problem Set:
Problem Set #10 Instructions
Note: UCLA students should only complete questions 1-3
Problem Set #10 R script
Note: add code to this R script and submit to piazza
Links to Lecture materials:
Readings:
GW 14 Strings
GW 16 Dates and Times
Link to Problem Set:
Problem Set #11
Submit Problem Set Here
Note: submit file (.R script) using this naming convention "lastname_firstname_ps9"
Links to Lecture materials:
Readings:
Link to Problem Set:
Problem Set #12
Submit Problem Set Here
Note: submit file (.R script) using this naming convention "lastname_firstname_ps10"
Links to Lecture materials:
Readings:
Link to Problem Set:
Problem Set #13
Submit Problem Set Here
Note: submit file (.R script) using this naming convention "lastname_firstname_ps10"
Links to Lecture materials: