# Intermediate Data Visualization With ggplot2

Dive deeper into ggplot2 and learn how to make a variety of different types of visualizations

Start## Key Concepts

Review core concepts you need to learn to master this subject

Histograms In R

Boxplots In R

The Fill Argument

The stat Parameter

The Position Argument

Error Bars In R

Customizing Discrete Axes In R

Customizing Continuous Axes In R

Histograms In R

Histograms In R

```
# Creates a histogram of the Ozone feature from the dataset airquality. In this case, each bin will have a width of 10.
airquality_histogram_binwidth <-
ggplot(airquality, aes(x = Ozone)) +
geom_histogram(binwidth = 10)
```

In R, the `geom_histogram()`

function from the `ggplot2`

library will create a histogram. The `binwidth`

argument sets the width of the bins in the histogram.

If the `binwidth`

argument is not used, the histogram will create 30 bins by default of equal size. It is recommended to use the `binwidth`

argument to make the histogram smoother.

Histograms are used to visualize the distribution of a continuous variable.

## What you'll create

Portfolio projects that showcase your new skills

## How you'll master it

Stress-test your knowledge with quizzes that help commit syntax to memory