Histograms, though similar in appearance to bar charts, are used to display the frequency of data items in relation to other items within the dataset. Each of the following examples using GRAL will use the DataTable class to initially hold the data to be displayed. In this example, we will read data from a sample file called AgeofMarriage.csv. This comma-separated file holds a list of ages at which people were first married.

We will create a new class, called HistogramExample, which extends the JFrame class and contains the following code within its constructor. We first create a DataReader object to specify that the data is in CSV format. We then use a try-catch block to handle IO exceptions and call the DataReader class's read method to place the data directly into a DataTable object. The first parameter of the read method is a FileInputStream object, and the second specifies the type of data expected from within the file:

DataReader readType=
  DataReaderFactory.getInstance().get("text/csv"); 
String fileName = "C://AgeofMarriage.csv"; 
try { 
    DataTable histData = (DataTable) readType.read( 
        New FileInputStream(fileName), Integer.class); 
    ... 
} 
 

Next, we create a Number array to specify the ages for which we expect to have data. In this case, we expect the ages of marriage will range from 19 to 30. We use this array to create our Histogram object. We include our DataTable from earlier and specify the orientation as well. Then we create our DataSource, specify our starting age, and specify the spacing along our X axis:

 
Number ageRange[] = {19,20,21,22,23,24,25,26,27,28,29,30}; 
Histogram sampleHisto = new Histogram1D( 
    histData, Orientation.VERTICAL, ageRange); 
DataSource sampleHistData = new EnumeratedData(sampleHisto, 19,
  1.0); 
 

We use the BarPlot class to create our histogram from the data we read in earlier:

 
BarPlot testPlot = new BarPlot(sampleHistData); 
 

The next few steps serve to format various aspects of our histogram. We use the setInsets method to specify how much space to place around each side of the graph within the window. We can provide a title for our graph and specify the bar width:

testPlot.setInsets(new Insets2D.Double(20.0, 50.0, 50.0, 20.0)); 
testPlot.getTitle().setText("Average Age of Marriage"); 
testPlot.setBarWidth(0.7);

We also need to format our X and Y axes. We have chosen to set our range for the X axis to closely match our expected age range but to provide some space on the side of the graph. Because we know the amount of sample data, we set our Y axis to range from 0 to 10. In a business application, these ranges would be calculated by examining the actual dataset. We can also specify whether we want tick marks to show and where we would like the axes to intersect:

testPlot.getAxis(BarPlot.AXIS_X).setRange(18, 30.0); 
testPlot.getAxisRenderer(BarPlot.AXIS_X).setTickAlignment(0.0); 
testPlot.getAxisRenderer(BarPlot.AXIS_X).setTickSpacing(1); 
testPlot.getAxisRenderer(BarPlot.AXIS_X).setMinorTicksVisible(false  ); 
                
testPlot.getAxis(BarPlot.AXIS_Y).setRange(0.0, 10.0); 
testPlot.getAxisRenderer(BarPlot.AXIS_Y).setTickAlignment(0.0); 
testPlot.getAxisRenderer(BarPlot.AXIS_Y).setMinorTicksVisible(false  ); 
testPlot.getAxisRenderer(BarPlot.AXIS_Y).setIntersection(0); 
 

We also have a lot of flexibility with the color and values displayed on the graph. In this example, we have chosen to display the frequency value for each age and set our graph color to black:

 
PointRenderer renderHist = 
    testPlot.getPointRenderers(sampleHistData).get(0); 
renderHist.setColor(GraphicsUtils.deriveWithAlpha(Color.black,
  128)); 
renderHist.setValueVisible(true); 
 

Finally, we set several properties for how we want our window to display:

InteractivePanel pan = new InteractivePanel(testPlot); 
pan.setPannable(false); 
pan.setZoomable(false); 
add(pan); 
setSize(1500, 700); 
this.setVisible(true); 
 

When the application is executed, the following graph is displayed: