For this example, we will use the Iris dataset. Iris is built into R installations and is available directly. Let's just pull in the data, gather some simple statistics, and plot the data. This will show R accessing a dataset in Jupyter, using an R built-in package, as well as some available statistics (since we have R), and the interaction with R graphics.
The script we will use is as follows:
data(iris)
summary(iris)
plot(iris)
If we enter this small script into a new R Notebook, we get an initial display that looks like the following:
![](https://static.packt-cdn.com/products/9781789137408/graphics/assets/480d5a96-0550-467e-869d-5bc3d99b2698.png)
I would expect the standard R statistical summary as output, and I know that the Iris plot is pretty interesting. We can see exactly what happened in the following screenshot:
![](https://static.packt-cdn.com/products/9781789137408/graphics/assets/ff9e8afc-27c0-4da1-8b99-10db79932a59.png)
The plot continues in the following screenshot, as it wouldn't fit into a single page:
![](https://static.packt-cdn.com/products/9781789137408/graphics/assets/a8166b67-6e45-4f13-8595-92a6ebeb0515.png)