# Accessing Built-in Datasets in R

R comes with many built-in datasets which are quite useful while learning R. To begin learning the basics of data visualization in R, we will make use of some of these datasets.

### Datasets in the 'datasets' package

Many datasets are included in a package called `datasets`

which is distributed with R so these datasets are instantly available to you for use. For example, two datasets namely `cars`

and `pressure`

are included in this default datasets package. So, you can access their data by using functions such as `head(cars)`

, `summary(cars)`

, etc.

The following examples show results of calls to these functions:

```
> head(cars)
speed dist
1 4 2
2 4 10
3 7 4
4 7 22
5 8 16
6 9 10
>
```

```
> summary(cars)
speed dist
Min. : 4.0 Min. : 2.00
1st Qu.:12.0 1st Qu.: 26.00
Median :15.0 Median : 36.00
Mean :15.4 Mean : 42.98
3rd Qu.:19.0 3rd Qu.: 56.00
Max. :25.0 Max. :120.00
>
```

```
> head(pressure)
temperature pressure
1 0 0.0002
2 20 0.0012
3 40 0.0060
4 60 0.0300
5 80 0.0900
6 100 0.2700
>
```

```
> summary(pressure)
temperature pressure
Min. : 0 Min. : 0.0002
1st Qu.: 90 1st Qu.: 0.1800
Median :180 Median : 8.8000
Mean :180 Mean :124.3367
3rd Qu.:270 3rd Qu.:126.5000
Max. :360 Max. :806.0000
>
```

To learn more about a dataset, you can use the help function as `help(cars)`

.

If you want to get a list of all the datasets, you can do so using the `data()`

function.

### Datasets in Other Packages

Any R package can choose to include datasets. You can access the data from a package using the`data()`

function by using the package argument as follows:

```
data(datasetname, package="packagename")
```

For example, there's a popular package called `MASS`

which contains datasets (such as Cars93). We can access the Cars93 dataset by calling the `data()`

function.

```
> data(Cars93, package="MASS")
```

After this call to `data()`

, the Cars93 dataset is available for use in R.

#### Course Downloads

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As a non-technical professional, learn how software works with simple explanations of tech concepts. Learn more...

- Overview of Data Visualization
- When to Use Bar Chart, Column Chart, and Area Chart
- What is Line Chart and When to Use It
- What are Pie Chart and Donut Chart and When to Use Them
- How to Read Scatter Chart and Bubble Chart
- What is a Box Plot and How to Read It
- Understanding Japanese Candlestick Charts and OHLC Charts
- Understanding Treemap, Heatmap and Other Map Charts
- Visualization in Data Science
- Graphic Systems in R
- Accessing Built-in Datasets in R
- How to Create a Scatter Plot in R
- Create a Scatter Plot in R with Multiple Groups
- Creating a Bar Chart in R
- Creating a Line Chart in R
- Plotting Multiple Datasets on One Chart in R
- Adding Details and Features to R Plots
- Introduction to ggplot2
- Grammar of Graphics in ggplot
- Data Import and Basic Manipulation in R - German Credit Dataset
- Create ggplot Graph with German Credit Data in R
- Splitting Plots with Facets in ggplots
- ggplot2 - Chart Aesthetics and Position Adjustments in R
- Creating a Line Chart in ggplot 2 in R
- Add a Statistical Layer on Line Chart in ggplot2
- stat_summary for Statistical Summary in ggplot2 R
- Facets for ggplot2 Charts in R (Faceting Layer)
- Coordinates in ggplot2 in R
- Changing Themes (Look and Feel) in ggplot2 in R

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