Control Flow

temperature <- 28

if (temperature > 30) {
  print("It's hot!")
} else if (temperature > 20) {
  print("It's warm.")
} else {
  print("It's cool.")
}
# "It's warm."

# Inline ifelse (vectorized)
x <- c(5, 15, 25)
ifelse(x > 10, "big", "small")
# "small" "big" "big"

# Basic for loop
for (i in 1:5) {
  print(i)
}

# Loop over a vector
fruits <- c("apple", "banana", "cherry")
for (fruit in fruits) {
  print(paste("I like", fruit))
}

# Loop with index
for (i in seq_along(fruits)) {
  print(paste(i, fruits[i]))
}

count <- 1
while (count <= 5) {
  print(count)
  count <- count + 1
}

# repeat runs forever until break is called
x <- 1
repeat {
  print(x)
  x <- x + 1
  if (x > 5) break
}

# next is R's equivalent of "continue" in other languages
for (i in 1:10) {
  if (i %% 2 == 0) next  # Skip even numbers
  print(i)
}
# 1 3 5 7 9

# sapply - apply a function to each element, simplify result
sapply(1:5, function(x) x^2)
# 1  4  9 16 25

# lapply - like sapply but always returns a list
lapply(1:3, function(x) x * 10)
# [[1]] 10  [[2]] 20  [[3]] 30

# apply - apply function over matrix rows (1) or columns (2)
mat <- matrix(1:12, nrow = 3)
apply(mat, 1, sum)   # Row sums
apply(mat, 2, mean)  # Column means

# tapply - apply by group
scores <- c(85, 90, 78, 92, 88)
groups <- c("A", "B", "A", "B", "A")
tapply(scores, groups, mean)
# A: 83.67  B: 91.00

# AVOID: loop to square each element
nums <- 1:1000000
result <- numeric(length(nums))
for (i in seq_along(nums)) {
  result[i] <- nums[i]^2
}

# PREFER: vectorized operation
result <- nums^2  # Same result, much faster!

# More vectorized examples
x <- c(1, 2, 3, 4, 5)
x > 3                    # FALSE FALSE FALSE TRUE TRUE
sum(x > 3)               # 2 (count of TRUE values)
x[x > 3]                 # 4 5 (filtering)
cumsum(x)                 # 1 3 6 10 15