**The objectives of this tutorial are to:**

- Learn how to make common data visualisations in R using ggplot2, including how to:
- Make a scatterplot
- Add a line of best fit to a scatterplot
- Add categorical information to a scatterplot
- Create a set of related scatterplots using facet_wrap()

- Make a boxplot
- add additional data to a boxplot
- add color to a boxplot

- Make a bar chart
- add color to a bar chart
- add additional data to a bar chart

- Make a scatterplot

One particularly powerful aspect of R is that it enables one visualize data in a variety of ways. Additionally, it gives users a wide variety of customization options. We will work below on a number of common data visualizations. But rememeber, once you get the hang of the basics, the sky is the limit! Note that this tutorial is a simplified version of [this one] (https://r4ds.had.co.nz/data-visualisation.html). For more details on what is possible, check out the source webpages!

To get started, lets load ggplot and look at one of the datasets that comes with ggplot:

```
library(ggplot2)
summary(mpg)
```

```
## manufacturer model displ year
## Length:234 Length:234 Min. :1.600 Min. :1999
## Class :character Class :character 1st Qu.:2.400 1st Qu.:1999
## Mode :character Mode :character Median :3.300 Median :2004
## Mean :3.472 Mean :2004
## 3rd Qu.:4.600 3rd Qu.:2008
## Max. :7.000 Max. :2008
## cyl trans drv cty
## Min. :4.000 Length:234 Length:234 Min. : 9.00
## 1st Qu.:4.000 Class :character Class :character 1st Qu.:14.00
## Median :6.000 Mode :character Mode :character Median :17.00
## Mean :5.889 Mean :16.86
## 3rd Qu.:8.000 3rd Qu.:19.00
## Max. :8.000 Max. :35.00
```