Introduction

Format: unified framework

codes
its results
prose commentary

features

.Rmd files: Develop your code and ideas side-by-side in a single document. Run code as individual chunks or as an entire document
Dynamic Documents · Knit together plots, tables, and results with narrative text. Render to a variety of formats like HTML, PDF, MS Word, or MS Powerpoint.
Reproducible Research · Upload, link to, or attach your report to share. Anyone can read or run your code to reproduce your work.

Advantages:

reproducible
support dozens of output formats, like html, PDFs, Word files, slideshows, and more.

Guidance for R Markdown

R Markdown cheat sheet: https://drive.google.com/drive/u/0/folders/1AiImxk_SL6lJ1jTfOPU93BOunIwGk8TF
R Mardow reference: https://drive.google.com/drive/u/0/folders/1AiImxk_SL6lJ1jTfOPU93BOunIwGk8TF
https://rstudio.com/resources/cheatsheets/.

R Markdown basic

1. This is an R Markdown file, a plain text file that has the extension .Rmd:

title: “Diamond sizes” date: 2016-08-25 output: html_document —

We have data about 53940 diamonds. Only 126 are larger than 2.5 carats. The distribution of the remainder is shown below:

It contains three important types of content:
- An (optional) YAML header surrounded by —s.
- Chunks of R code surrounded by ```.

To produce and share a complete report

click “Knit” or press Cmd/Ctrl + Shift + K. The report will display the report in the viewer pane, and create a self-contained HTML file that you can share with others.
When you knit the document, R Markdown sends the .Rmd file to knitr, http://yihui.name/knitr/, which executes all of the code chunks and creates a new markdown (.md) document which includes the code and its output. The markdown file generated by knitr is then processed by pandoc, http://pandoc.org/, which is responsible for creating the finished file. The advantage of this two step workflow is that you can create a very wide range of output formats, as you’ll learn about in R markdown formats.

Text formatting with Markdown

https://drive.google.com/drive/u/0/folders/1AiImxk_SL6lJ1jTfOPU93BOunIwGk8TF

Code chunk

to insert a chunk
- The keyboard shortcut Cmd/Ctrl + Alt + I
- The “Insert” button icon in the editor toolbar
- By manually typing the chunk delimiters {r} and
run code in a chunk
- Cmd/Ctrl + Shift + Enter or button green on the right side: run all codes in a chunk
- Cmd/Ctrl + Enter: continue to run the code
{r chunk name, followed by comma separated options}. The chunk end is indicated by a final.

*chunk options: + include = FALSE runs the code, but doesn’t show the code or results in the final document. Use this for setup code that you don’t want cluttering your report. + echo = FALSE prevents code, but not the results from appearing in the finished file. Use this when writing reports aimed at people who don’t want to see the underlying R code. + message = FALSE or warning = FALSE prevents messages or warnings from appearing in the finished file. + results = ‘hide’ hides printed output; fig.show = ‘hide’ hides plots. + error = TRUE causes the render to continue even if code returns an error.

Table

mtcars[1:5, ]

##                    mpg cyl disp  hp drat    wt  qsec vs am gear carb
## Mazda RX4         21.0   6  160 110 3.90 2.620 16.46  0  1    4    4
## Mazda RX4 Wag     21.0   6  160 110 3.90 2.875 17.02  0  1    4    4
## Datsun 710        22.8   4  108  93 3.85 2.320 18.61  1  1    4    1
## Hornet 4 Drive    21.4   6  258 110 3.08 3.215 19.44  1  0    3    1
## Hornet Sportabout 18.7   8  360 175 3.15 3.440 17.02  0  0    3    2

knitr::kable(
  mtcars[1:5, ], 
  caption = "A knitr kable."
)

A knitr kable.
	mpg	cyl	disp	hp	drat	wt	qsec	vs	am	gear	carb
Mazda RX4	21.0	6	160	110	3.90	2.620	16.46	0	1	4	4
Mazda RX4 Wag	21.0	6	160	110	3.90	2.875	17.02	0	1	4	4
Datsun 710	22.8	4	108	93	3.85	2.320	18.61	1	1	4	1
Hornet 4 Drive	21.4	6	258	110	3.08	3.215	19.44	1	0	3	1
Hornet Sportabout	18.7	8	360	175	3.15	3.440	17.02	0	0	3	2

Caching

cache = TRUE. When set, this will save the output of the chunk to a specially named file on disk. On subsequent runs, knitr will check to see if the code has changed, and if it hasn’t, it will reuse the cached results.

rawdata <- mtcars
rawdata

##                      mpg cyl  disp  hp drat    wt  qsec vs am gear carb
## Mazda RX4           21.0   6 160.0 110 3.90 2.620 16.46  0  1    4    4
## Mazda RX4 Wag       21.0   6 160.0 110 3.90 2.875 17.02  0  1    4    4
## Datsun 710          22.8   4 108.0  93 3.85 2.320 18.61  1  1    4    1
## Hornet 4 Drive      21.4   6 258.0 110 3.08 3.215 19.44  1  0    3    1
## Hornet Sportabout   18.7   8 360.0 175 3.15 3.440 17.02  0  0    3    2
## Valiant             18.1   6 225.0 105 2.76 3.460 20.22  1  0    3    1
## Duster 360          14.3   8 360.0 245 3.21 3.570 15.84  0  0    3    4
## Merc 240D           24.4   4 146.7  62 3.69 3.190 20.00  1  0    4    2
## Merc 230            22.8   4 140.8  95 3.92 3.150 22.90  1  0    4    2
## Merc 280            19.2   6 167.6 123 3.92 3.440 18.30  1  0    4    4
## Merc 280C           17.8   6 167.6 123 3.92 3.440 18.90  1  0    4    4
## Merc 450SE          16.4   8 275.8 180 3.07 4.070 17.40  0  0    3    3
## Merc 450SL          17.3   8 275.8 180 3.07 3.730 17.60  0  0    3    3
## Merc 450SLC         15.2   8 275.8 180 3.07 3.780 18.00  0  0    3    3
## Cadillac Fleetwood  10.4   8 472.0 205 2.93 5.250 17.98  0  0    3    4
## Lincoln Continental 10.4   8 460.0 215 3.00 5.424 17.82  0  0    3    4
## Chrysler Imperial   14.7   8 440.0 230 3.23 5.345 17.42  0  0    3    4
## Fiat 128            32.4   4  78.7  66 4.08 2.200 19.47  1  1    4    1
## Honda Civic         30.4   4  75.7  52 4.93 1.615 18.52  1  1    4    2
## Toyota Corolla      33.9   4  71.1  65 4.22 1.835 19.90  1  1    4    1
## Toyota Corona       21.5   4 120.1  97 3.70 2.465 20.01  1  0    3    1
## Dodge Challenger    15.5   8 318.0 150 2.76 3.520 16.87  0  0    3    2
## AMC Javelin         15.2   8 304.0 150 3.15 3.435 17.30  0  0    3    2
## Camaro Z28          13.3   8 350.0 245 3.73 3.840 15.41  0  0    3    4
## Pontiac Firebird    19.2   8 400.0 175 3.08 3.845 17.05  0  0    3    2
## Fiat X1-9           27.3   4  79.0  66 4.08 1.935 18.90  1  1    4    1
## Porsche 914-2       26.0   4 120.3  91 4.43 2.140 16.70  0  1    5    2
## Lotus Europa        30.4   4  95.1 113 3.77 1.513 16.90  1  1    5    2
## Ford Pantera L      15.8   8 351.0 264 4.22 3.170 14.50  0  1    5    4
## Ferrari Dino        19.7   6 145.0 175 3.62 2.770 15.50  0  1    5    6
## Maserati Bora       15.0   8 301.0 335 3.54 3.570 14.60  0  1    5    8
## Volvo 142E          21.4   4 121.0 109 4.11 2.780 18.60  1  1    4    2

processed_data <- rawdata %>% 
  filter(!is.na(mpg)) %>% 
  mutate(new_variable = mpg+1)

Caching the processed_data chunk means that it will get re-run if the dplyr pipeline is changed, but it won’t get rerun if the read_csv() call changes. You can avoid that problem with the dependson chunk option:

’‘{r processed_data, cache = TRUE, dependson = “raw_data”} processed_data <- rawdata %>% filter(!is.na(import_var)) %>% mutate(new_variable = complicated_transformation(x, y, z))’’

dependson should contain a character vector of every chunk that the cached chunk depends on. Knitr will update the results for the cached chunk whenever it detects that one of its dependencies have changed.
Note that the chunks won’t update if a_very_large_file.csv changes, because knitr caching only tracks changes within the .Rmd file. If you want to also track changes to that file you can use the cache.extra option. A good function to use is file.info(): it returns a bunch of information about the file including when it was last modified. Then you can write: {r raw_data, cache.extra = file.info("a_very_large_file.csv")} rawdata <- readr::read_csv("a_very_large_file.csv")
As your caching strategies get progressively more complicated, it’s a good idea to regularly clear out all your caches with knitr::clean_cache().
global chung options: knitr::opts_chunk$set()

inline code

To embed R code into an R Markdown document (tex) directly r (example diamond)
To set number of digits

comma <- function(x) format(x, digits = 2, big.mark = ",")
comma(3452345.123) # why does it not produce 3,452,345.12

## [1] "3,452,345"

comma(.12358124331)

## [1] "0.12"

YAML header

Parameters
output: html_document params: my_class: “suv” — ’’{r , include = FALSE} library(ggplot2) library(dplyr)

class <- mpg %>% filter(class == params$my_class)’’

Rmd_R in Data Science

Nguyen Truong

2023-04-01

Introduction

R Markdown basic

1. This is an R Markdown file, a plain text file that has the extension .Rmd:

Text formatting with Markdown

Code chunk

Parameters