Beginner Question about JSL

shasha_2

I want to save the selected rows in a csv or jmp file using JSL. But I am not able to do it Can anyone tell me how to get it done?

I tried by the following code but the way to save it appears to be wrong:

f = Function( {a},
theRows = Current Data Table() << get selected rows;
Show( theRows );

);

rs = Current Data Table() << make row state handler( f );
filepath = "C:\Users\abc\Desktop\trial";
rs << save( filepath || "\" || "part1.jmp" );

txnelson

I made a mistake in the JSL I provided in my last response.  I have since then corrected my response.

In this response, I have expanded on your provided JSL, and provided a complete example that will save the subsetted table every time a new Select Rows is specified.

The row state handler is also eliminated when the Partition() window is closed.

Names Default To Here( 1 );
dt = Open( "$SAMPLE_DATA\semiconductor capability.jmp" );

tableCount = 0;
theRows = [];

f = Function( {a},
	// Set dupRows to the previously selected rows
	dupRows = theRows;
	// Get the current selected rows
	theRows = Current Data Table() << get selected rows;
	If( N Rows( theRows ) > 0,
		// check to see if there are the same number of rows and if yes
		// then validate the rows are different rows before saving
		If( N Rows( theRows ) == N Rows( dupRows ),
			If( Sum( dupRows == theRows ) != N Rows( theRows ),
				tableCount++;
				dtTemp = dt << subset( invisible, selected rows( 1 ), selected columns( 0 ) );
				filepath = "$TEMP";
				Close(
					dtTemp,
					save( filepath || "\" || "part" || Char( tableCount ) || ".jmp" )
				);
				Current Data Table( dt );
			);
		,
			// If not the same number of selected rows, save the subset
			tableCount++;
			Show( tableCount );
			dtTemp = dt << subset( invisible, selected rows( 1 ), selected columns( 0 ) );
			filepath = "$TEMP";
			Close( dtTemp, save( filepath || "\" || "part" || Char( tableCount ) || ".jmp" ) );
			Current Data Table( dt );
		)
	);
);

rs = Current Data Table() << make row state handler( f );

obj = Partition(
	Y( :NPN1 ),
	X( :PNP1, :PNP2, :PNP3, :PNP4, :NPN2, :NPN3, :NPN4 ),
	Method( "Decision Tree" ),
	Validation Portion( .2 )
);
obj << ShowGraph( 0 );
obj << SplitBest( 4 );
obj << Show Split Count( 1 );
obj << Show Split Prob( 1 );
Wait( .5 );

//obj << Save Predicteds;

obj << on close( Clear Symbols( rs ) );