# Vectors, Recycling and Indexing — R Programming

Source: https://www.geekswithgeeks.com/en/r-programming/d-vectors

> Create and index vectors, and understand recycling and vectorised operations.

## Everything is a vector

An **atomic vector** holds elements of one type, created with `c()`, sequences (`1:10`, `seq(0, 1, by = 0.25)`) or `rep()`. If you combine types, R **coerces** to the most flexible one: `c(1, "a")` becomes character. Operations are **vectorised**: `prices * 1.18` multiplies every element. When two vectors of different lengths meet, R **recycles** the shorter one; this is convenient for scalars but can hide bugs, and R warns only when the longer length is not a multiple of the shorter. **Indexing starts at 1**. Index with positive integers (`x[c(1, 3)]`), **negative** integers to exclude (`x[-1]` drops the first element, it does not count from the end), **logical** vectors (`x[x > 50]`), or **names** (`x["Pune"]`) for named vectors. Useful functions: `length`, `sum`, `mean`, `max`, `which`, `which.max`, `cumsum`, `rev`, `sort`, `order`, `unique`, `table`, `%in%` and `ifelse` for vectorised conditionals.

## Vectorised operations

An operation applies element by element across a whole vector, recycling a shorter operand.

![Two rows of boxes aligned vertically with arrows between each pair, producing a third row of result boxes.](assets/figures/r-programming/section-2-map.svg) — Figure 2.1 — Element-wise operations and recycling.

## Vector operations and indexing

Logical indexing and named vectors are everyday R tools.

```r
prices <- c(pen = 49.5, notebook = 120, ink = 199, eraser = 15)

prices * 1.18                       # GST on every item
prices["ink"]                       # by name
prices[c(1, 3)]                     # by position (1-based)
prices[-1]                          # everything except the first
prices[prices > 100]                # logical indexing

names(which.max(prices))            # "ink"
sort(prices, decreasing = TRUE)

category <- ifelse(prices >= 100, "premium", "basic")   # vectorised if
table(category)                     # counts per category

"ink" %in% names(prices)            # TRUE

c(1, 2, 3, 4) + c(10, 20)           # recycling: 11 22 13 24
c(1, 2, 3) + c(10, 20)              # works, but with a warning (3 is not a multiple of 2)
```

## Negative indices exclude

In Python, `x[-1]` is the last element. In R, `x[-1]` removes the first element. Use `x[length(x)]` or `tail(x, 1)` for the last element.

**Quiz:** In R, what does x[-2] return for x <- c(10, 20, 30)?

- [ ] 20
- [ ] 30
- [x] c(10, 30)
- [ ] An error

*Answer:* c(10, 30). Negative indices exclude elements, so the second element is dropped.