## 1. Introduction and description of data

This module demonstrates how to obtain basic high
resolution graphics using SAS 9.3. This example uses a data file about 26
automobiles
with their make, mpg, repair record, weight, and whether the car was foreign or
domestic. The program below reads the data and creates a temporary data file called
**auto**.
The graphs shown in this module are all performed on this data file called
**auto**.

DATA auto ; INPUT make $ mpg rep78 weight foreign ; CARDS; AMC 22 3 2930 0 AMC 17 3 3350 0 AMC 22 . 2640 0 Audi 17 5 2830 1 Audi 23 3 2070 1 BMW 25 4 2650 1 Buick 20 3 3250 0 Buick 15 4 4080 0 Buick 18 3 3670 0 Buick 26 . 2230 0 Buick 20 3 3280 0 Buick 16 3 3880 0 Buick 19 3 3400 0 Cad. 14 3 4330 0 Cad. 14 2 3900 0 Cad. 21 3 4290 0 Chev. 29 3 2110 0 Chev. 16 4 3690 0 Chev. 22 3 3180 0 Chev. 22 2 3220 0 Chev. 24 2 2750 0 Chev. 19 3 3430 0 Datsun 23 4 2370 1 Datsun 35 5 2020 1 Datsun 24 4 2280 1 Datsun 21 4 2750 1 ; RUN;

## 2. Creating charts with proc gchart

We create vertical Bar Charts with **proc gchart**
and the **vbar** statement. The program below creates a vertical bar
chart for **mpg**.

TITLE 'Simple Vertical Bar Chart '; PROC GCHART DATA=auto; VBAR mpg; RUN;

This program produces the following chart.

The **vbar** statement produces a vertical
bar chart, and while optional the **title** statement allows you to label the
chart. Since **mpg** is a continuous variable the automatic
"binning" of the data into five groups yields a readable chart. The
midpoint of each bin labels the respective bar.

You can control the number of bins for a continuous
variable with the **level=** option on the **vbar** statement.
The program below creates a vertical bar chart with seven bins for
**mpg**.

TITLE 'Bar Chart - Control Number of Bins'; PROC GCHART DATA=auto; VBAR mpg/LEVELS=7; RUN;

This program produces the following chart.

On the other hand, **rep78** has only four
categories and SAS’s tendency to bin into five categories and use midpoints would not do
justice to the data. So when you want to use the actual values of the variable to
label each bar you will want to use the **discrete** option on the
**vbar**
statement.

TITLE 'Bar Chart with Discrete Option'; PROC GCHART DATA=auto; VBAR rep78/ DISCRETE; RUN;

This program produces the following chart.

Notice that only the values in the dataset for **rep78**
appear in the bar chart.

Other charts may be easily produced simply by changing **vbar**.
For example, you can produce a horizontal bar chart by replacing **vbar**
with **hbar**.

TITLE 'Horizontal Bar Chart with Discrete'; PROC GCHART DATA=auto; HBAR rep78/ DISCRETE; RUN;

This program produces the following horizontal bar chart.

Use the **discrete** option to insure that
only the values in the dataset for **rep78** label bars in the bar
chart. With **hbar** you automatically obtain frequency, cumulative
frequency, percent, and cumulative percent to the right of each bar.

You can produce a pie chart by replacing **hbar**
in the above example with **pie**. The **value=**,
**percent=**,
and **slice=** options control the location of each of those labels.

TITLE 'Pie Chart with Discrete'; PROC GCHART DATA=auto; PIE rep78/ DISCRETE VALUE=INSIDE PERCENT=INSIDE SLICE=OUTSIDE; RUN;

This program produces the following pie chart.

Use the **discrete** option to insure that
only the values in the dataset for **rep78** label slices in the pie
chart.

value=insidecauses the frequency count to be placed inside the pie slice.percent=insidecauses the percent to be placed inside the pie slice.slice=outsidecauses the label (value ofrep78) to be placed outside the pie slice.

We have shown only some of the charts and options
available to you. Additionally you can create city block charts (**block**)
and star charts (**star**), and use options and statements to further control
the look of charts.

## 3. Creating Scatter plots with proc gplot

To examine the relationship between two
continuous variables you will want to produce a scattergram using **proc
gplot**, and
the **plot** statement. The program below creates a scatter plot for
**mpg*weight**.
This means that **mpg** will be plotted on the vertical axis, and
**weight**
will be plotted on the horizontal axis.

TITLE 'Scatterplot - Two Variables'; PROC GPLOT DATA=auto; PLOT mpg*weight ; RUN;

This program produces the following scattergram.

You can easily tell that there is a negative
relationship between **mpg** and **weight**. As
**weight**
increases **mpg** decreases.

You may want to examine the relationship between two
continuous variables and see which points fall into one or another category of a third
variable. The program below creates a scatter plot for **mpg*weight**
with each level of **foreign** marked. You specify
**mpg*weight=foreign**
on the** plot** statement to have each level of foreign identified on the
plot.

TITLE 'Scatterplot - Foreign/Domestic Marked'; PROC GPLOT DATA=auto; PLOT mpg*weight=foreign; RUN;

This program produces the following scattergram with each foreign and domestic marked.

You can easily tell which level of **foreign**
you are looking at, as values of zero are in black and values of 1 are in red. Since
the default symbol is plus for both, if this graph is printed in black and white you will
not be able to tell the levels of **foreign** apart. The next
example demonstrates how to use different symbols in scattergrams.

## 4. Customizing with proc gplot and symbol statements

The program below creates a scatter plot for **mpg*weight**
with each level of **foreign** marked. The **proc gplot**
is specified exactly the same as in the previous example. The only difference is the
inclusion of **symbol** statements to control the look of the graph through
the use of the operands **V=**, **I=**, and **C=**.

SYMBOL1 V=circle C=black I=none; SYMBOL2 V=star C=red I=none; TITLE 'Scatterplot - Different Symbols'; PROC GPLOT DATA=auto; PLOT mpg*weight=foreign; RUN;QUIT;

**Symbol1** is used for the lowest value of
**foreign** which is zero (domestic cars), and **symbol2** is used for the
next lowest value which is one (foreign cars) in this case.

V=controls the type of point to be plotted. We requested acircleto be plotted for domestic cars, and astar(asterisk) for foreign cars.I= nonecauses SAS not to plot a line joining the points.C=controls the color of the plot. We requested black for domestic cars, and red for foreign cars. (Sometimes theC=option is needed for any options to take effect.)

This program produces the following scatter plot with each foreign and domestic marked and with different symbols.

You can easily tell which level of **foreign**
you are looking at, as values of zero are marked with circles in black and values of 1 are
marked with asterisks in red. Now if this graph is printed in black and white you
will be able to tell the levels of ** foreign** apart.

At times it is useful to plot a regression line along
with the scatter gram of points. The program below creates a scatter plot for
**mpg*weight**
with such a regression line. The regression line is produced with the
**I=R**
operand on the **symbol** statement.

SYMBOL1 V=circle C=blue I=r; TITLE 'Scatterplot - With Regression Line '; PROC GPLOT DATA=auto; PLOT mpg*weight ; RUN; QUIT;

The **symbol** statement controls color,
the shape of the points, and the production of a regression line.

I=Rcauses SAS to plot a regression line.V=circlecauses a circle to be plotted for each case.C=bluecauses the points and regression line to appear in blue. Always specify theC=option to insure that the symbol statement takes effect.

This program produces the following scattergram with using blue circles and plotting a regression line.

## 5. Problems to look out for

- If SAS seems to be ignoring your
**symbol**statement, then try including a color specification (**C=**). - Avoid using the
**discrete**option in**proc chart**with truly continuous variables, for this causes problems with the number of bars.

## 6. For more information

- For information on Labeling in SAS, see the SAS Learning Module Labeling data, variables, and values.
- A number of helpful hints on using SAS Graph was prepared by Professor Oliver Schabenberger of Virginia Tech, and is available at ATS’s SAS Library: Web Page Resources in the article, An Introduction to Publication Quality Graphics in SAS for Windows.