- 01Setting up (what you'll need)
- 02Your first output (print)
- 03Using variables
- 04Branching (the if statement)
- 05Repeating (the for loop)
- 06Writing your own function
- 07Working with vectors
- 08Repeating (the while loop)
- 09Structured data with lists
- 10Error handling (tryCatch)
- 11Sorting a vector
- 12Recursive functions
- 13Using the handy built-in functions
- 14The switch() function
- 15Applying a condition across a vector with ifelse()
- 16Applying a function across data with sapply()
- 17Writing comments
- 18Logical operators (&&, ||, !)
- 19Constants (the upper-case convention)
- 20Splitting and joining strings (strsplit and paste)
- 21Writing NULL-safe code
- 22Searching a vector (%in%)
- 23Transforming a vector with sapply (the map equivalent)
- 24Tabular data with matrices
- 25Creating your own condition
- 26Default arguments
- 27Set operations (union, intersect, setdiff)
- 28Checking correctness with stopifnot (a first step towards testing)
- 29Higher-order functions (passing a function as an argument)
- 30Stacks and queues (the basics of data structures)
- 31The basics of type conversion (casting)
- 32An introduction to regular expressions (pattern matching)
- 33The binary search algorithm
- 34Building a Caesar cipher (a letter-shifting cipher)
- 35Understanding how bubble sort works
- 36Assembling and displaying a date
- 37Writing several tests together (multiple test cases)
- 38Speeding up calculation with memoization (caching)
- 39Normalizing strings (trimws and case)
- 40Shallow copies versus deep copies
- 41factor, R's equivalent of an enum
- 42Flattening a list
- 43Reversing a string and testing for a palindrome
- 44Pairing up two vectors (the zip operation)
- 45Rounding numbers (floor, ceiling, round)
- 46Assembling multi-line text
- 47Returning several values from a function (lists)
- 48Finding the GCD and LCM (the Euclidean algorithm)
- 49Formatting numbers (aligning digits and decimal places)
- 50Cleaning up with tryCatch's finally
- 51Type-agnostic general functions
- 52The basics of reading and writing files
- 53Generating random numbers
- 54Bitwise operations (bitwAnd, bitwOr, bitwXor, shifts)
- 55Receiving command-line arguments
- 56Pausing for a set time (Sys.sleep)
- 57Watch out for floating-point error
- 58Reading a value from standard input
- 59FizzBuzz (the classic exercise)
- 60Testing whether a number is prime
- 61Set operations (union, intersection, difference)
- 62Converting between bases (binary and hexadecimal)
- 63Checking that brackets match (an application of stacks)
- 64Testing whether two words are anagrams
- 65Testing whether a year is a leap year
- 66Converting temperatures (Celsius and Fahrenheit)
- 67Finding the prime factors
- 68[Project] Build a simple inventory system
Working with vectors
This lesson covers the basics of using vectors in R, with the aim of handling several pieces of data together.
A vector is like a shelf of numbered drawers. The c() function creates one. It is the basic unit of data handling in R and its single most important data structure.
The sample code builds a vector with fruits <- c("apple", "orange", "grape") and displays each element with a number using for (i in 1:length(fruits)). Note that R vectors are indexed from 1.
A common early stumble is exactly that: indexes start at 1, not 0. Most other languages (Python, JavaScript) start at 0, so the difference trips people up on arriving at R.
In professional work, vectors are R's most basic tool, used to gather experimental or observational data for aggregation and analysis.
๐งช This site can't compile or run R directly, so it checks on the spot whether what you typed matches the reference code (scoring happens entirely in your browser โ nothing is sent anywhere).