2 R Basics

3 R as a Calculator

1 + 1

[1] 2

3 * (4 + 5)

[1] 27

4 Objects & Assignment

x <- 10
y <- 3.5
x + y

[1] 13.5

5 object naming rules

R variable names can contain letters, numbers, periods, and underscores. However, they cannot start with a number or underscore. R is case-sensitive, so age, Age, and AGE would be considered different variables.
R variable names should be descriptive and meaningful. Avoid using reserved words or function names as variable names.
A variable can have a short name (like x and y) or a more descriptive name (age, carname, total_volume). Rules for R variables are:
A variable name must start with a letter and can be a combination of letters, digits, period(.) and underscore(_). If it starts with period(.), it cannot be followed by a digit.
A variable name cannot start with a number or underscore (_) Variable names are case-sensitive (age, Age and AGE are three different variables) Reserved words cannot be used as variables (TRUE, FALSE, NULL, if…)
Variable names should not contain spaces. Use underscore (_) or period (.) to separate words in a variable name.
Variable names should be meaningful and descriptive. Avoid using single-letter variable names except for temporary variables in loops or functions.

6 Basic Operations in R

R supports various basic operations, including: * Arithmetic Operations: Addition (+), subtraction (-), multiplication (*), division (/), and exponentiation (^). Example:

a <- 10
b <- 5
sum <- a + b
diff <- a - b
prod <- a * b
quot <- a / b
exp <- a ^ b
sum; diff; prod; quot; exp

[1] 15

[1] 5

[1] 50

[1] 2

[1] 1e+05

Comparison Operations: Equal to (==), not equal to (!=), greater than (>), less than (<), greater than or equal to (>=), and less than or equal to (<=). Example:

x <- 10
y <- 5
eq <- x == y
neq <- x != y
gt <- x > y
lt <- x < y
gte <- x >= y
lte <- x <= y
eq; neq; gt; lt; gte; lte

[1] FALSE

[1] TRUE

[1] TRUE

[1] FALSE

[1] TRUE

[1] FALSE

Logical Operations: AND (&), OR (|), and NOT (!). Example:

p <- TRUE
q <- FALSE
and <- p & q
or <- p | q
not <- !p
and; or; not

[1] FALSE

[1] TRUE

[1] FALSE

7 Comments in R

Comments in R are created using the # symbol. Anything following the # on the same line is considered a comment and is ignored by R during execution. Example:

# This is a comment
x <- 10  # Assigning value to x
y <- 5   # Assigning value to y
sum <- x + y  # Calculating the sum of x and y
sum  # Output the sum

[1] 15

8 Getting Help in R

R provides several ways to get help and documentation for functions and packages: * ?function_name: Displays the documentation for a specific function. Example:

?mean

help(function_name): Another way to access the documentation for a function. Example:

help(mean)

help.search("keyword"): Searches for help topics related to a specific keyword. Example:

help.search("regression")

example(function_name): Shows examples of how to use a specific function. Example:

example(mean)


mean> x <- c(0:10, 50)

mean> xm <- mean(x)

mean> c(xm, mean(x, trim = 0.10))
[1] 8.75 5.50

vignette("package_name"): Opens the vignette (detailed documentation) for a specific package. Example:

vignette("dplyr")

starting httpd help server ... done

??keyword: Searches for help topics related to a specific keyword (similar to help .search). Example:

??regression

9 Installing and Loading Packages in R

R has a vast ecosystem of packages that extend its functionality. To use a package, you need to install it first and then load it into your R session. * Installing a Package: Use the install.packages("package_name") function to install a package from CRAN. Example:

install.packages("ggplot2")

Loading a Package: Use the library(package_name) function to load an installed package into your R session. Example:

library(ggplot2)

# Now you can use functions from the ggplot2 package

9.0.1 Saving and Loading Workspaces in R

You can save your R workspace (all objects in memory) to a file and load it later * Saving Workspace: Use the save.image("file_name.RData") function to save the entire workspace to a file. Example:

save.image("my_workspace.RData")

Loading Workspace: Use the load("file_name.RData") function to load a saved workspace from a file. Example:

load("my_workspace.RData")

10 Working Directory

getwd()

[1] "/home/runner/work/r4sas/r4sas"

# setwd("/path/you/want") # avoid in reproducible code; prefer here::here() for projects

11 Vectors (Atomic)

nums <- c(1, 2, 3, 4)
chars <- c("a", "b", "c")
logical <- c(TRUE, FALSE, TRUE)
typeof(nums); typeof(chars); typeof(logical)

[1] "double"

[1] "character"

[1] "logical"

12 Exercises

Create an object z that stores (5^2 + 7)/3.
Use ?seq and create a sequence from 0 to 1 by 0.1.
Inspect typeof() for a few objects you create.

--- title: "R Basics" --- # R as a Calculator ```{r} 1 + 1 3 * (4 + 5) ``` # Objects & Assignment ```{r} x <- 10 y <- 3.5 x + y ``` # object naming rules - R variable names can contain letters, numbers, periods, and underscores. However, they cannot start with a number or underscore. R is case-sensitive, so `age`, `Age`, and `AGE` would be considered different variables. - R variable names should be descriptive and meaningful. Avoid using reserved words or function names as variable names. - A variable can have a short name (like x and y) or a more descriptive name (age, carname, total_volume). Rules for R variables are: - A variable name must start with a letter and can be a combination of letters, digits, period(.) and underscore(\_). If it starts with period(.), it cannot be followed by a digit. - A variable name cannot start with a number or underscore (\_) Variable names are case-sensitive (age, Age and AGE are three different variables) Reserved words cannot be used as variables (TRUE, FALSE, NULL, if...) - Variable names should not contain spaces. Use underscore (\_) or period (.) to separate words in a variable name. - Variable names should be meaningful and descriptive. Avoid using single-letter variable names except for temporary variables in loops or functions. # Basic Operations in R R supports various basic operations, including: \* Arithmetic Operations: Addition (`+`), subtraction (`-`), multiplication (`*`), division (`/`), and exponentiation (`^`). Example: ```{r} a <- 10 b <- 5 sum <- a + b diff <- a - b prod <- a * b quot <- a / b exp <- a ^ b sum; diff; prod; quot; exp ``` - Comparison Operations: Equal to (`==`), not equal to (`!=`), greater than (`>`), less than (`<`), greater than or equal to (`>=`), and less than or equal to (`<=`). Example: ```{r} x <- 10 y <- 5 eq <- x == y neq <- x != y gt <- x > y lt <- x < y gte <- x >= y lte <- x <= y eq; neq; gt; lt; gte; lte ``` - Logical Operations: AND (`&`), OR (`|`), and NOT (`!`). Example: ```{r} p <- TRUE q <- FALSE and <- p & q or <- p | q not <- !p and; or; not ``` # Comments in R Comments in R are created using the `#` symbol. Anything following the `#` on the same line is considered a comment and is ignored by R during execution. Example: ```{r} # This is a comment x <- 10 # Assigning value to x y <- 5 # Assigning value to y sum <- x + y # Calculating the sum of x and y sum # Output the sum ``` # Getting Help in R R provides several ways to get help and documentation for functions and packages: \* `?function_name`: Displays the documentation for a specific function. Example: ```{r} ?mean ``` - `help(function_name)`: Another way to access the documentation for a function. Example: ```{r} help(mean) ``` - `help.search("keyword")`: Searches for help topics related to a specific keyword. Example: ```{r} help.search("regression") ``` - `example(function_name)`: Shows examples of how to use a specific function. Example: ```{r} example(mean) ``` - `vignette("package_name")`: Opens the vignette (detailed documentation) for a specific package. Example: ```{r} vignette("dplyr") ``` - `??keyword`: Searches for help topics related to a specific keyword (similar to `help .search`). Example: ```{r} ??regression ``` # Installing and Loading Packages in R R has a vast ecosystem of packages that extend its functionality. To use a package, you need to install it first and then load it into your R session. \* Installing a Package: Use the `install.packages("package_name")` function to install a package from CRAN. Example: ```{r eval=FALSE} install.packages("ggplot2") ``` - Loading a Package: Use the `library(package_name)` function to load an installed package into your R session. Example: ```{r} library(ggplot2) # Now you can use functions from the ggplot2 package ``` ### Saving and Loading Workspaces in R You can save your R workspace (all objects in memory) to a file and load it later \* Saving Workspace: Use the `save.image("file_name.RData")` function to save the entire workspace to a file. Example: ```{r eval=FALSE} save.image("my_workspace.RData") ``` - Loading Workspace: Use the `load("file_name.RData")` function to load a saved workspace from a file. Example: ```{r eval=FALSE} load("my_workspace.RData") ``` # Working Directory ```{r} getwd() # setwd("/path/you/want") # avoid in reproducible code; prefer here::here() for projects ``` # Vectors (Atomic) ```{r} nums <- c(1, 2, 3, 4) chars <- c("a", "b", "c") logical <- c(TRUE, FALSE, TRUE) typeof(nums); typeof(chars); typeof(logical) ``` # Exercises 1. Create an object `z` that stores `(5^2 + 7)/3`. 2. Use `?seq` and create a sequence from 0 to 1 by 0.1. 3. Inspect `typeof()` for a few objects you create.