Craige's answer is probably the easiest. We often need a square version of the graph with the axes spanning the entire range. One way to do that is to determine the min and max values and set both axes to the same values.
g = Bivariate( Y( :height ), X( :weight ) );
minaxis = Min( Col Min( :height ), Col Min( :weight ) );
maxaxis = Max( Col Max( :height ), Col Max( :weight ) );
(Report( g )[axisbox( 1 )]) << {Min( minaxis ), Max( maxaxis )};
(Report( g )[axisbox( 2 )]) << {Min( minaxis ), Max( maxaxis )};
(Report( g )[framebox( 1 )]) << Frame Size( 320, 320 );
The resulting graph:
I sometimes add a 45-degree line to this graph to indicate X=Y. This graph is useful if X and Y represent the same property or characteristic (not height and weight). If X and Y represented values of the same characteristic measured by measurement devices X and Y, this graph would tell us that there is a problem between the two measurement devices.
Some points are on the edge of the graph. This can be fixed by using a "weighted combination" of min and max values to widen the axes:
minaxis = 1.05 * Min( Col Min( :height ), Col Min( :weight ) ) - 0.05 * Max( Col Max( :height ), Col Max( :weight ) );
maxaxis = -0.05 * Min( Col Min( :height ), Col Min( :weight ) ) + 1.05 * Max( Col Max( :height ), Col Max( :weight ) );
Good luck!
Howard