Slices in R Programming Language

R doesn’t have a direct equivalent to slices, but we can use vectors and lists to achieve similar functionality. Here’s how we can implement the concepts in R:

# In R, we use vectors and lists instead of slices

# Create an empty vector
s <- character(0)
cat("uninit:", s, "is null:", is.null(s), "length is 0:", length(s) == 0, "\n")

# Create a vector of length 3
s <- character(3)
cat("emp:", s, "len:", length(s), "\n")

# Set and get elements
s[1] <- "a"
s[2] <- "b"
s[3] <- "c"
cat("set:", s, "\n")
cat("get:", s[3], "\n")

# Get the length of the vector
cat("len:", length(s), "\n")

# Append elements to the vector
s <- c(s, "d")
s <- c(s, "e", "f")
cat("apd:", s, "\n")

# Copy a vector
c <- s
cat("cpy:", c, "\n")

# Slice a vector
l <- s[3:5]
cat("sl1:", l, "\n")

l <- s[1:5]
cat("sl2:", l, "\n")

l <- s[3:length(s)]
cat("sl3:", l, "\n")

# Declare and initialize a vector in one line
t <- c("g", "h", "i")
cat("dcl:", t, "\n")

# Compare vectors
t2 <- c("g", "h", "i")
if (all(t == t2)) {
  cat("t == t2\n")
}

# Create a list of vectors (similar to 2D slice)
twoD <- list()
for (i in 1:3) {
  innerLen <- i
  twoD[[i]] <- integer(innerLen)
  for (j in 1:innerLen) {
    twoD[[i]][j] <- i + j - 1
  }
}
cat("2d: ", toString(twoD), "\n")

In R, vectors are the primary data structure and can be used similarly to slices in many cases. Here are some key differences and explanations:

1. R uses 1-based indexing, unlike Go’s 0-based indexing.
2. We use c() to create and combine vectors, which is similar to append() in Go.
3. R doesn’t have a built-in append() function for vectors, but we can use c() to achieve the same result.
4. Slicing in R is done with [start:end] syntax, similar to Go.
5. R doesn’t have a direct equivalent to Go’s make() function. Instead, we can create vectors of a specific length using functions like character() or integer().
6. For multi-dimensional structures, R uses lists of vectors instead of slices of slices.

When you run this R script, you’ll see output similar to the Go example, demonstrating the various operations on vectors and lists in R.

R’s vectors and lists provide powerful and flexible ways to work with sequences of data, similar to slices in Go. While the syntax and some specific operations differ, the general concepts of creating, manipulating, and accessing sequential data structures are present in both languages.