01-setup.Rmd

# R Setup

## Preparing your environment

The Institute and Faculty of Actuaries have provided their [own guide](https://www.actuaries.org.uk/system/files/field/document/R-Guide_technical.pdf) to getting up and running with `R`.

The steps to have `R` working is dependant on your operating system. Thankfully the following resources _should_ allow for your local installation of `R` to be relatively painless:

1. Download and install `R` from [CRAN](https://cran.rstudio.com/)^[CRAN is the The Comprehensive R Archive Network - read more on the [CRAN](https://cran.rstudio.com/) website].
2. Download and install an integrated development environment, I recommend [RStudio Desktop](https://rstudio.com/products/rstudio/download/#download).

## Basic interations with R

`R` prefers **vectorised** operations (over concepts like for loops)

```{r setup-vector-intro}
# This is the syntax for comments in R
(1:10) + 2 # Notice how we add element-wise in R
```

We **assign** values to **variables** using the `<-` *("assignment")* operator^[We can also assign values using the more familiar `=` symbol. In general this is discouraged, listen to [Hadley Wickham](https://style.tidyverse.org/syntax.html#assignment-1).].

```{r setup-vector-variable, collapse=TRUE}
x <- 1:10
y <- x + 2
x <- x + x # Notice that we can re-assign values to variables
z <- x + 2
y
z
```

Even though $z$ is assigned the same way as we assigned $y$, note that $y \neq z$ so execution order matters in `R`

We now add **functions** to the `R` code which has the form `function_name(arguments = "values", ...)`{.R}

```{r setup-function}
# Combine function, used often to create vectors:
x <- c(1:3, 6:20, 21:42) 
# Another function with arguments:
y <- sample(x, size = 3)
y
```

Let's create a **matrix** in `R`

*Note:* **Matrix multiplication** requires the `%*%` syntax

```{r setup-matrix}
first_matrix <- matrix(1:9, byrow = TRUE, nrow = 3)
first_matrix %*% first_matrix
```

A `data.frame` is a very popular data structure used in `R`. Each input variable has to have the same length but can be of different types (*strings, integers, booleans, etc.*).

```{r setup-dataframe}
# Input vectors for the data.frame
name <- c("Mercury", "Venus", "Earth", "Mars", "Jupiter", "Saturn", "Uranus", "Neptune")
surface_gravity <- c(0.38, 0.904, 1, 0.3794, 2.528, 1.065, 0.886, 1.14)
# Create a data.frame from the vectors
solar_system <- data.frame(name, surface_gravity)
str(solar_system)
```

R has built in logic expressions:

| Operator | Description |
|-|-|
| < (<=) | less than (or equal to) |
| > (>=) | greater than (or equal to) |
| == | exactly equal to |
| ! | NOT |
| & | AND (*element-wise*) |
| \| | OR (*element-wise*) |
| != | not equal to |


We can use logical expressions to effectively filter data

Here we **subset** the data using the `[...]`{.R} syntax
```{r setup-subsetting}
x <- 1:10
x[x != 5 & x < 7]
```


We can select objects using the **\$** symbol - see `?Extract`{.R} for more help here

```{r setup-selecting}
#data.frame[rows to select, columns to select]
solar_system[solar_system$name == "Jupiter", c(1:2)]
```

We can extend `R`'s functionality by loading **packages**:

```{r setup-packages}
# Load the ggplot2 package
library(ggplot2)
```

- Did you get an error from `R` trying this?
- To load packages they need to be **installed** first:
- `install.packages("ggplot2")`{.R}