It's not possible at this time for YOU to do it.So it's not possible?
Actually this may be helpful. Thanks.Would this work?
1. Combine the 3 sets of data, making sure to add an indicator next to each record to identify which set the row of data came from
2. Do a "countif" on the whole set of data for each record to determine if the records have duplicates on a new column
3. Filter that new column on records that have >1 on the countif; remove these rows
4. Unfilter, and break data back into the 3 groups
might be better to ask here: http://forums.anandtech.com/forumdisplay.php?f=10
also, i might be able to tell you what function to use if i had a better idea of what you are working with and what you want to see as a result. you can do a simple true false function to just see ones that dont match. but without knowing more i cant help much.
Would this work?
1. Combine the 3 sets of data, making sure to add an indicator next to each record to identify which set the row of data came from
2. Do a "countif" on the whole set of data for each record to determine if the records have duplicates on a new column
3. Filter that new column on records that have >1 on the countif; remove these rows
4. Unfilter, and break data back into the 3 groups
Would this work?
1. Combine the 3 sets of data, making sure to add an indicator next to each record to identify which set the row of data came from
2. Do a "countif" on the whole set of data for each record to determine if the records have duplicates on a new column
3. Filter that new column on records that have >1 on the countif; remove these rows
4. Unfilter, and break data back into the 3 groups
