Week 3 Coworking Session (Spring 2026)
This lesson is called Week 3 Coworking Session (Spring 2026), part of the R in 3 Months (Spring 2026) course. This lesson is called Week 3 Coworking Session (Spring 2026), part of the R in 3 Months (Spring 2026) course.
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Course Content
148 Lessons
1
Welcome to Fundamentals of R
01:20
2
Update Everything
02:26
3
Start a New Project
02:38
4
The Tidyverse
03:24
5
Pipes
03:52
6
select()
04:43
7
mutate()
03:22
8
filter()
10:18
9
Quiz
10
summarize()
05:38
11
Grouped Summaries
04:24
12
arrange()
02:50
13
Create a New Data Frame
03:30
14
Quiz
15
Bring it All Together (Data Wrangling)
07:09
16
Week 2 Project Assignment
13:10
17
Week 2 Coworking Session (Spring 2026)
18
Week 2 Live Session (Spring 2026)
59:16
1
The Grammar of Graphics
04:36
2
Scatterplots
03:40
3
Histograms
04:51
4
Bar Charts
04:53
5
Quiz
6
Setting color and fill Aesthetic Properties
02:43
7
Setting color and fill Scales
05:12
8
Quiz
9
Setting x and y Scales
02:58
10
Adding Text to Plots
05:50
11
Plot Labels
02:59
12
Themes
02:10
13
Facets
02:56
14
Save Plots
02:49
15
Bring it All Together (Data Visualization)
06:14
16
Week 3 Project Assignment
06:02
17
Week 3 Coworking Session (Spring 2026)
18
Week 3 Live Session (Spring 2026)
1:00:46
1
Downloading and Importing Data
08:13
2
Overview of Tidy Data
05:03
3
Tidy Data Rule #1: Every Column is a Variable
06:26
4
Tidy Data Rule #3: Every Cell is a Single Value
09:27
5
Tidy Data Rule #2: Every Row is an Observation
04:05
6
Quiz
7
Week 6 Coworking Session (Spring 2026)
8
Week 6 Live Session (Spring 2026)
59:31
1
Best Practices in Data Visualization
03:38
2
Tidy Data
02:25
3
Pipe Data in ggplot
08:18
4
Reorder Plots to Highlight Findings
03:50
5
Line Charts
04:13
6
Use Color to Highlight Findings
08:23
7
Declutter
07:53
8
Add Descriptive Labels to Your Plots
09:18
9
Use Titles to Highlight Findings
08:30
10
Use Annotations to Explain
06:35
11
Quiz
12
Week 9 Coworking Session (Spring 2026)
13
Week 9 Live Session (Spring 2026)
59:10
1
Advanced Markdown
07:10
2
Tables
15:48
3
Advanced YAML and Code Chunk Options
05:42
4
Inline R Code
03:42
5
Making Your Reports Shine: Word Edition
05:08
6
Making Your Reports Shine: PDF Edition
07:37
7
Making Your Reports Shine: HTML Edition
06:08
8
Presentations
11:12
9
Dashboards
06:20
10
Websites
08:11
11
Publishing Your Work
02:37
12
Quarto Extensions
06:38
13
Parameterized Reporting, Part 1
07:02
14
Parameterized Reporting, Part 2
04:03
15
Parameterized Reporting, Part 3
06:22
16
Quiz
17
Week 12 Coworking Session (Spring 2026)
18
Week 12 Live Session (Spring 2026)
57:26
1
Working with labelled data
05:35
2
Understanding Documentation Pages
05:20
3
Factors in R
11:18
4
Add citations to Quarto documents
10:42
5
Change titles of facet plots
08:16
6
Population pyramid plot
04:24
7
Why use Git - example case
06:13
8
How to access data not on GitHub
13:46
9
Dealing with merge conflicts in GitHub Desktop
03:22
10
Crosstabs
06:58
11
Difference between == and %in%
03:17
12
Quarto - rendering and working directories
13:05
13
Using Function Arguments
13:06
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Alberto Cabrera • March 24, 2026
I have problems rendering a Quarto document unless I include the full file path.
This R script. penguins <- readr::read_csv(here::here("Data_raw", "penguins.csv")). Prompts the following error when I render the document. However, it works fine if I run it as Run Cell.
Error: ! '/Users/albertocabrera/Documents/2026 R in 3 Months/R_scripts/Data_raw/penguins.csv' does not exist.
Instead, Quarto does render the document if I display the full path as follows: penguins <- readr::read_csv("/Users/albertocabrera/Documents/2026 R in 3 Months/Data_raw/penguins.csv")