Code Chunks
This lesson is called Code Chunks, part of the R in 3 Months (Spring 2026) course. This lesson is called Code Chunks, part of the R in 3 Months (Spring 2026) course.
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---
title: My Penguins Report!
author: David Keyes
format: html
execute:
echo: false
warning: false
message: false
---
```{r}
library(tidyverse)
penguins <- read_csv("penguins.csv")
```
# Funders
1. The International Society of Penguin Enthusiasts and Waddle Admirers
1. The Coalition of People Who Are Definitely Not Anti-Penguin
1. The International Coalition for the Appreciation and Ethical Treatment of Penguins
They are **very** excited about this report and they *really* hope you are too.
# Introduction
This report is about **three** species of penguins
1. Adele
1. Gentoo
1. Chinstrap
You'll learn *so* much about the penguins. I hope you're ready!
## Results
Here is a chart showing the average bill length for penguins, grouped by island and sex.
```{r}
penguin_bill_length_by_island_and_sex <-
penguins |>
drop_na(sex) |>
group_by(island, sex) |>
summarize(mean_bill_length = mean(bill_length_mm))
ggplot(
data = penguin_bill_length_by_island_and_sex,
mapping = aes(
x = island,
y = mean_bill_length,
fill = sex
)
) +
geom_col(position = "dodge")
```
Learn More
To learn about the various options for code chunks, check out the Quarto website.
Have any questions? Put them below and we will help you out!
Course Content
144 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)
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)
1
All videos from R in 3 Months (Spring 2026)
2
Working with labelled data
05:35
3
Understanding Documentation Pages
05:20
4
Factors in R
11:18
5
Add citations to Quarto documents
10:42
6
Change titles of facet plots
08:16
7
Population pyramid plot
04:24
8
Why use Git - example case
06:13
9
How to access data not on GitHub
13:46
10
Dealing with merge conflicts in GitHub Desktop
03:22
11
Crosstabs
06:58
12
Difference between == and %in%
03:17
13
Quarto - rendering and working directories
13:05
14
Using Function Arguments
13:06
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