a more sophisticated version:
Names Default To Here( 1 );
// make a sample data table
dt = New Table( "Data",
add rows( 10000 ),
New Column( "it", Numeric, Ordinal, Format( "Best", 8 ), Formula( Row() ) ),
New Column( "Batch", Numeric, Ordinal, Format( "Best", 8 ), formula( Random Integer( 110 ) ) ),
New Column( "y1", Numeric, Continues, Format( "Best", 8 ), formula( Random Lognormal( :Batch / 10, 5 ) ) ),
New Column( "y2", Numeric, Continues, Format( "Best", 8 ), formula( Random Lognormal( :Batch / 10, 5 ) ) ),
New Column( "Out",
Numeric,
Ordinal,
Format( "Best", 8 ),
Set Property( "Value Colors", {0 = -13977687, 1 = -4222943} ),
Color Cell by Value,
formula( 0 )
),
New Column( "Outy1",
Numeric,
Ordinal,
Format( "Best", 8 ),
Set Property( "Value Colors", {0 = -13977687, 1 = -4222943} ),
Color Cell by Value,
formula( 0 )
),
New Column( "Outy2",
Numeric,
Ordinal,
Format( "Best", 8 ),
Set Property( "Value Colors", {0 = -13977687, 1 = -4222943} ),
Color Cell by Value,
formula( 0 )
),
);
dt << run formulas;
Column( dt, "it" ) << delete formula;
Column( dt, "Batch" ) << delete formula;
Column( dt, "y1" ) << delete formula;
Column( dt, "y2" ) << delete formula;
Column( dt, "Out" ) << delete formula;
Column( dt, "Outy1" ) << delete formula;
Column( dt, "Outy2" ) << delete formula;
// now we get to work
// make a list of batches
byvarlist = Associative Array( dt:Batch ) << get keys;
// make a list of columns
cols = dt << get column names( Continuous ); //List all Numeric columns
// loop through the batches
For( i = 1, i <= N Items( byvarlist ), i++,
// select each batch
dt << select where( dt:Batch == byvarlist[i] );
// subset each batch
subdt = dt << Subset( Selected Rows( 1 ) );
// clear selection for smoth workflow
dt << clear select;
// finde outliers in each variable within each batch
For( ii = 1, ii <= N Items( cols ), ii++,
out = Eval(
Parse(
"subdt << get rows where(
subdt:" || Char( cols[ii] ) || " > Col Quantile( subdt:" || Char( cols[ii] ) ||
", 0.75 ) + 1.5 * (Col Quantile( subdt:" || Char( cols[ii] ) || ", 0.75 ) - Col Quantile( subdt:" || Char( cols[ii] ) ||
", 0.25 )) | subdt:" || Char( cols[ii] ) || " <
Col Quantile( subdt:" || Char( cols[ii] ) ||
", 0.25 ) - 1.5 * (Col Quantile( subdt:" || Char( cols[ii] ) || ", 0.75 ) - Col Quantile( subdt:" || Char( cols[ii] ) ||
", 0.25 )));"
)
)`;
Eval( Parse( "column (subdt, \!"Out" || Char( cols[ii] || "\!" )[" || Char( out ) || "] = 1;" ) ) );
// also indicate the global outlier
Column( subdt, "Out" )[out] = 1;
//wait (0.00001);
);
// update original data table with new information for the batch
subdt << delete columns( "Batch" );
subdt << delete columns( cols );
dt << Update( With( subdt ), Match Columns( :it = :it ) );
Close( subdt, No Save );
//Wait( 0.00001 );
);
dt << color by column( :Out );
