Language itself
R is a free software environment for statistical computing and graphics.
It's a compiled language.
R is a dynamicallytyped,that means the type of a variable is determined at runtime, and that variables do not have to be explicitly declared with a specific type.
R is weaklytyped, which means that it will automatically convert between types when necessary, without the need for explicit type casting.
R is a garbagecollected language. This means the R runtime system automatically manages the memory used by the program.
R is both a functional an object oriented language but it doesn't support inheritance, polymorphism, and encapsulation.
In R, functions call by value. This means that when a function is called, the values of the arguments passed to the function are passed to the function's local scope, and any changes made to the arguments within the function do not affect the original values of the arguments outside the function. 
Language environment
To code in R you can install the extension in your IDE like VSC or install its own IDE R Studio :
R for Windows
R for Linux
Then to run it you can run it with the IDE if you don't have one you can use R Studio server, which is a webbased version of R Studio that can be accessed through a web browser. The command for R Studio is Rscript myscript.R .
When installed R Studio it would have a minimal impact impact on the local machine but if you runs large R scripts or using R for data analysis and machine learning tasks, which require a lot of memory,it may have a bigger impact on the local machine. But in the end it does not modify something in your machine that would block you in it's use. 
Library
Code
install.packages('dplyr') : Download and install a package from CRAN.
library(dplyr') : Load the package into the file.
dplyr::select : Use a function from the package
Commonly used library
stringr for string manipulation
dplyr for data frame manipulation
ggplot2 for plotting graphs
lubridate for date 
To go further
R is an integrated suite of software facilities for data manipulation, calculation and graphical display. It includes:
An effective data handling and storage facility,
A suite of operators for calculations on arrays, in particular matrices,
A large, coherent, integrated collection of intermediate tools for data analysis,
Graphical facilities for data analysis and display either onscreen or on hardcopy, and
A welldeveloped, simple and effective programming language which includes conditionals, loops, userdefined recursive functions and input and output facilities.
The people who mainly use R are data scientist / engineer 


Syntax and data structures
Variable Assignment
a < 'bonjour' : string
a < 6 : integer
Loop
For loop :
for (variable in sequence){ Do something }
While loop :
while (condition){ Do something }
Condition
if (condition){ Do something } else { Do something different }
a == b : Are equal
a > b : Greater than
a >= b : Greater than or equal to
is.na(a) : Is missing
a != b : Not equal
a < b : Less than
a <= b : Less than or equal to
is.null(a) : Is null
Functions
function_name < function (var){ Do something return (new_variable) }
Maths Functions
log(x) : Natural log / sum(x) : Sum
exp(x) : Exponential / mean(x) : Mean
max(x) : Largest element / median(x) : Median
min(x) : Smallest element / quantile(x) : Percentage quantiles
round(x, n) : Round to n decimal places
rank(x) : Rank of elements
signif(x, n) : Round to n significant figures
var(x) : The variance / cor(x, y) : Correlation
sd(x) : The standard deviation
Lists
l < list(x = 1:5, y = c('a', 'b')) : A list is collection of elements which can be of diﬀerent types.
l[[2]] : second element of l
l[1] : new list with only the first element
l$x : element named x
l['y'] : new list with only element named y
String
paste(x, y, sep = ' ') : Join multiple vectors together.
paste(x, collapse = ' ') : Join elements of a vector together.
grep(pattern, x) : Find regular expression matches in x.
gsub(pattern, replace, x) : Replace matches in x with a string.
toupper(x) : Convert to uppercase.
tolower(x) : Convert to lowercase.
nchar(x) : Number of characters in a string.
Matrixes
m < matrix(x, nrow = 3, ncol = 3) : Create a matrix from x.
df[ , 2] : Select a column .
df[2, ] : Select a row.
df[2, 2] : Select an element.
Data Frames
df < data.frame(x = 1:3, y = c('a', 'b', 'c')) : A special case of a list where all elements are the same length.
View(df) : See the full data frame.
head(df) :See the first 6 rows.
nrow(df) : Number of rows.
ncol(df) : Number of columns.
dim(df) : Number of columns and rows.
As the same sub settings as matrixes and lists
Ploting
plot(x) : plot values of x in order
plot(x, y) : plot values of x against y
Reading and writing data
df < read.table('file.txt') / df < read.csv('file.csv') / Read a file text or a csv
write.table(df, ‘file.txt’) / write.csv(df, ‘file.csv’) / Write a file text or a csv 

Created By
Metadata
Comments
No comments yet. Add yours below!
Add a Comment
Related Cheat Sheets
More Cheat Sheets by Todin