R Functions Explained

Learn key R functions Explained: like sort(), search(), subset(), sample(), all(), and any() with practical examples. Discover how to check if an element exists in a vector and understand the differences between all() and any(). Perfect for R beginners!” learn Q&A guide on sort(), search(), subset(), sample(), all(), any(), and element checks in vectors. Boost your R skills today!”

Which function is used for sorting in the R Language?

Several functions in R can be used for sorting data. The most commonly used R functions for sorting are:

• sort(): Sorts a vector in ascending or descending order. The general syntax is sort(x, decreasing = FALSE, na.last = NA)
• order(): Returns the indices that would sort a vector (it is useful for sorting data frames). The general syntax of order() is order(x, decreasing = FALSE, na.last = TRUE)
• arrange(): It sorts a data frame (however, it requires dplyr package). The general syntax is: arrange(.data, …, .by_group = FALSE)

# sort() Function
vec <- c(3, 1, 4, 1, 5)
sort(vec)                		# Ascending (default): 1 1 3 4 5
sort(vec, decreasing = TRUE)  	# Descending: 5 4 3 1 1

# order() Function
df <- data.frame(name = c("Ali", "Usman", "Umar"), age = c(25, 20, 30))
df[order(df$age), ]  # Sort data frame by age (ascending)

# arrange() Function from dplyr package
library(dplyr)
df %>% arrange(age)               # Ascending
df %>% arrange(desc(age))         # Descending

Why search() function used?

In R language, the search() function is used to display the current search path of R objects (such as functions, datasets, variables, etc.). This shows the order in which R looks for objects when you reference them.

What Does search() function do?

• Lists all attached packages and environments in the order R searches them.
• Helps diagnose issues when multiple packages have functions with the same name (name conflicts).
• Shows where R will look when you call a function or variable.

What is the use of subset() and sample() functions in R?

In R language, subset() and sample() are two useful functions for data manipulation and sampling:

• subset(): is used to extract subsets of data frames or vectors based on some condition. The general syntax is subset(x, subset, select, …)
• sample(): is used for random sampling from a dataset with or without replacement. The general system is: sample(x, size, replace = FALSE, prob = NULL).

The examples of subset() and sample() are describe below

# Example data frame
df <- data.frame(
  name = c("Ali", "Usman", "Aziz", "Daood"),
  age = c(25, 30, 22, 28),
  salary = c(50000, 60000, 45000, 70000)
)

# Filter rows where age > 25
subset(df, age > 25)

# Filter rows and select specific columns
subset(df, salary > 50000, select = c(name, salary))

# Randomly sample 3 numbers from 1 to 10 without replacement
sample(1:10, 3)

# Sample with replacement (possible duplicates)
sample(1:5, 10, replace = TRUE)

# Sample rows from a data frame
df[sample(nrow(df), 2), ]  # Picks 2 random rows

What is the use of all() and any()?

In R language, the all() and any() functions are logical functions used to evaluate conditions across vectors or arrays.

• all() function: checks if all elements of a logical vector are TRUE. It returns TRUE only if every element in the input is TRUE, otherwise, it returns FALSE. The general syntax is all(..., na.rm=FALSE)
• any() Function: checks if at least one element of a logical vector is TRUE. It returns TRUE if any element is TRUE and FALSE only if all are FALSE. The general syntax is any(..., na.rm = FALSE)

The examples of all() and any() functions are:

x <- c(TRUE, TRUE, FALSE)
all(x)  # FALSE (not all elements are TRUE)

y <- c(5, 10, 15)
all(y > 3)  # TRUE (all elements are greater than 3)

x <- c(TRUE, FALSE, FALSE)
any(x)  # TRUE (at least one element is TRUE)

y <- c(2, 4, 6)
any(y > 5)  # TRUE (6 is greater than 5)

Note that if NA is present and na.rm = FALSE, any() returns NA unless a TRUE value exists.

What are the key differences between all() and any()?

The key differences between all() and any() are:

What is the R command to check if element 15 is present in a vector $x$?

One can check if the element (say) 15 is present in a vector x using either

• %in% Operator
• any() with logical comparison
• which() to find the position of 15

# %in%
x <- c(10, 15, 20, 25)
15 %in% x  # Returns TRUE
30 %in% x  # Returns FALSE

# any()
x <- c(5, 10, 15)
any(x == 15)  # TRUE
any(x == 99)  # FALSE

# Which()
x <- c(10, 15, 20, 15)
which(x == 15)  # Returns c(2, 4)

Try Normal Distribution Quiz