In R, ‘letters’ is a built-in constant that contains all the lowercase letters of the English alphabet. It is a vector of 26, each element being a single lowercase letter from ‘a’ to ‘z’.
This constant can be very helpful for generating labels, iterating over alphabetic sequences, or other tasks where you need a sequence of letters.
Syntax
letters
Visual representation
Example 1: Basic usage
print(letters)
Output
[1] "a" "b" "c" "d" "e" "f" "g" "h" "i" "j" "k" "l" "m" "n" "o" "p" "q" "r" "s"
[20] "t" "u" "v" "w" "x" "y" "z"
You can see from the output that it returns lowercase character vectors of the alphabet.
To print specific letters in the sequence, say if you want only g, h & i. use the following code.
letters[7:9]
Output
[1] "g" "h" "i"
Example 2: Extracting characters
To extract the first specific part of the object, use the “head()” function.
cat("First 6 characters from letters", "\n")
head(letters)
Output
First 6 characters from letters
[1] "a" "b" "c" "d" "e" "f"
And we get the first 10 uppercase letters in the output using the head() function.
Example 3: Extracting last specific parts
To extract the last specific parts of the object in R, use the tail() function.
cat("Last 10 characters from letters", "\n")
tail(letters, 10)
Output
Last 10 characters from letters
[1] "q" "r" "s" "t" "u" "v" "w" "x" "y" "z"
Example 4: Using with the paste() function
To concate strings, use the paste() function. You can create a custom sequence of letters using the paste() function.
paste("millie_", letters, sep = "")
Output
[1] "millie_a" "millie_b" "millie_c" "millie_d" "millie_e" "millie_f"
[7] "millie_g" "millie_h" "millie_i" "millie_j" "millie_k" "millie_l"
[13] "millie_m" "millie_n" "millie_o" "millie_p" "millie_q" "millie_r"
[19] "millie_s" "millie_t" "millie_u" "millie_v" "millie_w" "millie_x"
[25] "millie_y" "millie_z"
Example 5: Looping over letters
for (letter in letters) {
print(letter)
}
This loop will print each letter from ‘a’ to ‘z’.
Krunal Lathiya is a seasoned Computer Science expert with over eight years in the tech industry. He boasts deep knowledge in Data Science and Machine Learning. Versed in Python, JavaScript, PHP, R, and Golang. Skilled in frameworks like Angular and React and platforms such as Node.js. His expertise spans both front-end and back-end development. His proficiency in the Python language stands as a testament to his versatility and commitment to the craft.