# Pictorial displays

Pictorial displays are among the most important techniques that help you describing and analyzing your data. The R graphics system is very powerful and lets you produce professional-looking graphics. There are high-level plotting functions that are best suited for simple graphs, while low-level functions provide you with advanced tools to edit details and add annotations.

These examples are based on the high-level plotting functions. Most of
the times getting the right result is a matter of playing with some of
the many graphical parameters. General graphical options are handled by
the `par()`

function, while each specific function has its own
parameters.

## Barcharts

Barcharts are good if you have to depict a non-numeric variable, such as
nominal and ordinal variables. Bars in the graph are physically
**separated** meaning that this is not a cartesian graph.

```
> barplot(table(Cond))
```

```
> barplot(table(Mat,Cond), beside=FALSE)
```

```
> barplot(table(Mat,Cond), beside=TRUE)
```

## Histograms

Histograms are as much different from barcharts as ratio variables differ from nominal. An histogram represents the density distribution of values on a continuous axis.

```
> hist(Socle, freq=TRUE)
```

## Boxplots

These are known also as "box-and-whisker plots", because of their shape. Boxplots are useful to compare visually the same variable in different datasets because they provide a quick way to represent the most common measures of position (mean, quartiles, outliers).

```
> boxplot(Socle)
```

In this graph the central line in the box represents the average mean value, the alone point is an outlier.

## Stem-and-leaf plots

Stem-and-leaf plots are useful if you need not only to represent the distribution of your variable, but also to keep your original data available without losing too much space.

```
> stem(Socle)
The decimal point is at the |
2 | 40114455
4 | 23556812489
6 | 01466258
8 | 011466726
10 | 2
12 | 5
14 | 4
```

```
> stem(Socle, scale=2)
The decimal point is at the |
2 | 4
3 | 0114455
4 | 235568
5 | 12489
6 | 01466
7 | 258
8 | 0114667
9 | 26
10 | 2
11 |
12 |
13 | 5
14 | 4
```

## Scatterplots

Scatterplots are a mean to compare one variable against another, plotting on a cartesian surface. The values of one variable are used as X values, and the otherâ€™s as Y values.

```
> plot(Maxwi,Maxle, col=Mat, pch=19)
```

```
> plot(Maxwi,Maxle, col=Mat, pch=Mat)
```