# Using R to process Google Analytics

# Setting Up Your Environment

Before you can start using R, you'll need to install it. Here's how to install R on a Mac using Homebrew

# Dataframes

What makes R really powerful is this concept of Dataframes. Dataframes the objects used to represent tables including *observations* and *variables* (aka rows and columns). Within a Dataframe, you can store different types of data including dates, integers, floating point numbers and text.

## Create a Dataframe object

```
media <- list("Film" = c("The Matrix", "John Wick", "Babes In Toyland"), "Music" = c("Dogstar"), "Television" = c("The Continental") )
```

### Get Films

Get all films using an index.

```
media[1]
```

Get all films using a variable.

```
media$Film
```

Get the first object within the ``Film``` column.

```
media$Film[1]
```

## Other Objects

The other objects are a bit more standard including: Strings, Floating Numbers, Integers, Boolean Variables, and dates ("2018/08/08").

## Custom Functions

You can also write custom functions.

```
sumMultiply <- function(x, y, z){
final = (x+y) * z
return(final)
}
```

## Custom Objects

- If you want to plot each value of
`y`

sequentially, then you'll use single dimension vectors. - If you want to create a scatterplot, then you'll use two-dimensional matrices.
- Regression Models
- Time series data