| Week 1 |
Collaborative working environment:
Git, GitHub, and R Markdown |
- Jan 14
- Course intro & syllabus | Collaborations - test case | data: csv, xlsx
- Jan 16
-
what you said | Solution to test case (Rmd file) (other Rmd file)| R, RStudio, RMarkdown
|
| Weeks 2-3 |
Intro to R |
- Jan 21
-
R intro | R code: inclass
- Jan 23
-
more R intro (missing values) | first graphics | R code: inclass
- Jan 28
-
first graphics | boxplots, histograms, & barcharts | R code: inclass
- Jan 30
- logical vectors and filters | R code: inclass
- Extras
- Coding style | Project workflow
|
| Weeks 4-5 |
Data structures: logical variables and filters |
- Feb 4
- logical vectors and filters | R code: inclass
- Feb 6
- factors | R code: inclass
- Feb 11
- visualizing factors | R code: inclass
|
| Weeks 5-7 |
Tools of data management |
- Feb 13
- visualizing factors | intro to the tidyverse | R code: inclass
- Feb 18
- Intro to dplyr | R code: inclass
- Feb 20
- More dplyr | R code: inclass
- Feb 25
- More dplyr | R code: inclass
- Feb 27
- More dplyr | | R code: inclass
|
| Weeks 8-10 |
Data tidying |
- Mar 3
- Reshaping data | R code: inclass
- Mar 5
- Reshaping data | Dealing with messy (2) | R code: inclass
- Mar 10
- Dealing with messy (2) | R code: inclass
- Mar 12
- Dealing with messy (3) | Dealing with messy (4) | R code: inclass
- Mar 24
- Dealing with messy (4) | R code: inclass | yourturns: solutions
- Mar 26
- Dealing with messy (4) | missing values | dates & times | R code: inclass | yourturns: solutions
|
| Weeks 10-14 |
Data structures |
- Mar 31
- dates & times | R code: inclass | yourturns: solutions
- April 2
- visualizing time | layers in ggplot2 | R code: inclass
- April 7
- Midterm prep | cheatsheets
- April 9
- Midterm
- April 14
- maps | R code: inclass
- April 16
- maps | R code: inclass
- April 21
- polishing plots
- April 23
- string manipulation
|
| Week 15 and Finals |
Project presentations |
Apr 28
Apr 30
May 7
|