1 R Markdown

R Markdown is a format for writing reproducible, dynamic reports with R. Use it to embed R code and results into slideshows, PDFs, HTML documents, Word files and more.

2 Structure

YAML Header
Text Area
Code chunk

3 Workflow

Open – Open a file that uses the .Rmd extension.
Write – Write content with the easy-to-use R Markdown syntax.
Embed – Embed R code that creates output to include in the report.
Render – Replace R code with its output and transform the report into a slideshow, PDF, HTML or MS Word file.

4 Text Area Formatting Tools:

Plain text
End a line with two spaces to start a new paragraph italics and italics bold and bold superscript² ~~strikethrough~~ Hyperlink: [CCIDM]

5 Header 1

5.1 Header 2

5.1.1 Header 3

5.1.1.1 Header 4

5.1.1.1.1 Header 5

5.1.1.1.1.1 Header 6

endash: – emdash: — inline equation: \(A = \pi r^2\) slide break:

Block quote

Ordered list 1
Ordered list 2
- sub-item 1
- sub-item 2

Table Header	Second Header
Table Cell	Cell 2
Cell 3	Cell 4

6 YAML Header

YAML header is a set of key: value pairs at the start of your file. Begin and end the header with a line of three dashes (—). (From the Rmd cheatsheet

https://www.rstudio.com/wp-content/uploads/2015/02/rmarkdown-cheatsheet.pdf)

You will notice that my YAML header is different from the default one Rmd file automatically created. That is because I customized output option as above. This setting dictates how your HTML file that will be knitted will look like.

date: ‘2026-01-25 20:41:40’
- This allows to print the current time each time you knit the file.
- Can be customized in various ways
  - date-time: ‘2026-01-25 20:41:40.765384’
  - Day, Month, date, Year (e.g., Sunday, January 25, 2026): ‘Sun, Jan, 25, 2026’
  - m/d/Y (e.g., 01/25/2026): ‘01/25/2026’

toc: yes
- I turned the table of contents on. This will have hyperlinks in HTML and allow readers to navigate to the desired sections faster.

toc_depth: 4
- I want to see up to four levels of headings.
toc_float: true
- This allows to move from the front end of the document to a left side floating when you scroll down.
- By default, the floating toc headings are collapsed, not showing all headings. We can turn it off using the following.
```
toc_float:
collapsed: false
```
- highlight: espresso
- I want to see espresso style: black background of codes area.
theme: journal
- Choose the style you like.
number_sections: yes
- Turned on automatic section numbering, which is why I didn’t add numbering manually below.
- Notice how this will nicely turn your HTML report much more organized.
- Try this and other options and see which one you like the most in your HTML file.

7 Embed Codes

7.1 Code chunk

7.1.1 Sample

Ctrl + Alt + I

# use Ctrl + Enter simultaneous to execute a line
# Use # to comment out a code

# install.packages("tidyverse")
library(tidyverse)

## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ dplyr     1.1.4     ✔ readr     2.1.6
## ✔ forcats   1.0.1     ✔ stringr   1.6.0
## ✔ ggplot2   4.0.1     ✔ tibble    3.3.1
## ✔ lubridate 1.9.4     ✔ tidyr     1.3.2
## ✔ purrr     1.2.1     
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag()    masks stats::lag()
## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors

# install.packages("palmerpenguins")
library(palmerpenguins)

## 
## Attaching package: 'palmerpenguins'
## 
## The following objects are masked from 'package:datasets':
## 
##     penguins, penguins_raw

# install.packages("skimr")
library(skimr)

penguins

## # A tibble: 344 × 8
##    species island    bill_length_mm bill_depth_mm flipper_length_mm body_mass_g
##    <fct>   <fct>              <dbl>         <dbl>             <int>       <int>
##  1 Adelie  Torgersen           39.1          18.7               181        3750
##  2 Adelie  Torgersen           39.5          17.4               186        3800
##  3 Adelie  Torgersen           40.3          18                 195        3250
##  4 Adelie  Torgersen           NA            NA                  NA          NA
##  5 Adelie  Torgersen           36.7          19.3               193        3450
##  6 Adelie  Torgersen           39.3          20.6               190        3650
##  7 Adelie  Torgersen           38.9          17.8               181        3625
##  8 Adelie  Torgersen           39.2          19.6               195        4675
##  9 Adelie  Torgersen           34.1          18.1               193        3475
## 10 Adelie  Torgersen           42            20.2               190        4250
## # ℹ 334 more rows
## # ℹ 2 more variables: sex <fct>, year <int>

dim(penguins)

## [1] 344   8

skimr::skim(penguins)

Data summary
Name	penguins
Number of rows	344
Number of columns	8
_______________________
Column type frequency:
factor	3
numeric	5
________________________
Group variables	None

Variable type: factor

skim_variable	n_missing	complete_rate	ordered	n_unique	top_counts
species	0	1.00	FALSE	3	Ade: 152, Gen: 124, Chi: 68
island	0	1.00	FALSE	3	Bis: 168, Dre: 124, Tor: 52
sex	11	0.97	FALSE	2	mal: 168, fem: 165

Variable type: numeric

skim_variable	n_missing	complete_rate	mean	sd	p0	p25	p50	p75	p100	hist
bill_length_mm	2	0.99	43.92	5.46	32.1	39.23	44.45	48.5	59.6	▃▇▇▆▁
bill_depth_mm	2	0.99	17.15	1.97	13.1	15.60	17.30	18.7	21.5	▅▅▇▇▂
flipper_length_mm	2	0.99	200.92	14.06	172.0	190.00	197.00	213.0	231.0	▂▇▃▅▂
body_mass_g	2	0.99	4201.75	801.95	2700.0	3550.00	4050.00	4750.0	6300.0	▃▇▆▃▂
year	0	1.00	2008.03	0.82	2007.0	2007.00	2008.00	2009.0	2009.0	▇▁▇▁▇

# sex distribution
penguins%>%
  count(sex) %>%
  ggplot(aes(sex,n)) +
  geom_col()

# Number of male
sum(penguins$sex == "male", na.rm = TRUE)

## [1] 168

# Total observation
nrow(penguins)

## [1] 344

# Percent of Males
m_per = round((sum(penguins$sex == "male", na.rm = TRUE) / nrow(penguins)) * 100, digits = 1)

# Percent of Females
f_per = round((sum(penguins$sex == "female", na.rm = TRUE) / nrow(penguins)) * 100, digits = 1)

7.1.2 Code chunk options

For more details visit https://yihui.org/knitr/options

7.2 Inline coding

Sample characteristics:
There are 344 penguins in the data, 48.8 % of which are males and 48 % of which are females.

9 Expectations for Organizing your assignment report with Rmd file

9.1 M01-1 Principle Assignment

10 References

R Markdown cheatsheet
https://www.rstudio.com/wp-content/uploads/2015/02/rmarkdown-cheatsheet.pdf

How to create a reproducible reporting HTML file using Rmd file

Nicole BewleyHudson

2026-01-25 20:41:40.729593