I'm sure there are many ways to do this depending on depending on the degree of interaction versus automation (scripting) you want.
One interactive way I can think of is the use Tables:Summary and assign the 12 duped variables as grouping variables and no statistic. It will make a new table listing the number of occurrence of each 12-var combination. The new table is linked to the original, so if you select rows in the new table with NRows more that 1, you'll see dupes selected in the original.
Doing with with Big Class on height and weight, for instance, reveals one duplicated combination: height=64, weight=99.
Data Table( "Big Class" ) << Summary( Group( :height, :weight ) )
I'm sure there are many ways to do this depending on depending on the degree of interaction versus automation (scripting) you want.
One interactive way I can think of is the use Tables:Summary and assign the 12 duped variables as grouping variables and no statistic. It will make a new table listing the number of occurrence of each 12-var combination. The new table is linked to the original, so if you select rows in the new table with NRows more that 1, you'll see dupes selected in the original.
Doing with with Big Class on height and weight, for instance, reveals one duplicated combination: height=64, weight=99.
Data Table( "Big Class" ) << Summary( Group( :height, :weight ) )
I wrote a script recently to check to make sure I wasn't adding duplicate rows to a data table. Maybe this will help.
The script iterates through all the rows in the table (i counter) and each of my 9 columns (k counter) comparing the values to those in the last row. If it finds any rows that are equal, it will delete the last row.
dt << CurrentDataTable;
TotalRows = NRows(dt);
eqFlag = 1;
deleteFlag = 0;
For(i=1, i<TotalRows,i++,
For(k =1, k <=9,k++,
If(Column(dt,k)sqbrack i sqbrack !=Column(dt,k)[TotalRows], eqFlag=0)
);
If(eqFlag == 1, deleteFlag = 1);
eqFlag = 1;
);
If(deleteFlag==1,dt<<SelectRows(TotalRows); dt<<Delete Rows);
Excel has a one-button "Remove Duplicates"
Pandas has a one-liner drop_duplicates https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.drop_duplicates.html
We really have to write a loop and check every value ourselves?
There is a function called Select Duplicate Rows() in JSL, or it can be used interactively under the pull down menus
Rows==>Row Selection==>Select Duplicate Rows