NOTE: Transforms are a part of the underlying language that is not directly accessible to users. This content is maintained for reference purposes only.Removes exact duplicate rows from your dataset. Duplicate rows are identified by exact, case-sensitive matches between values.
For example, two strings with different capitalization do not match.
Output: Rows that are exact duplicates of previous rows are removed from the dataset.
There are no parameters for this transform.
Matches and non-matches for Deduplicate Transform
For example, your dataset looks like the following, which contains three sets of very similar records. The second row of each set is different in one column than the previous one.
|Jane Jackson||February 3, 2004||77|
If you use
deduplicate on this dataset, no rows are previewed. This preview indicates that no rows will be removed as duplicates. You might need to clean up the data before you can remove any duplicate rows.
Your first step should be get your capitalization consistent. Try the following:
set col:Name value:PROPER(Name)
All entries in the
Name column now appear as proper names. Next, you can clean up the score column by normalizing numeric values to the same format. Try the following:
set col:Score value:NUMFORMAT(Score, '##.00')
The above transform normalizes the numeric formats to include two-digits after the decimal point always, which forces all numbers to be the same format. You can use the
## format string here, too.
Use the following to fix the Date column:
replace col:Date with:'2/3/04' on:'February 3, 2004'
Now, you can execute the