How do you find duplicates in SAS dataset?
When you use nodupkey and dupout in PROC SORT, you will remove the first of each set of duplicates in the output data set. That’s why each duplicated value has a frequency in dups that is one less than its frequency in test. To obtain ALL duplicates of a data set, you can take advantage of first. variable and last.
How do you compare two sets of data in SAS?
Here’s how to check if two datasets in SAS are the same:
- Start the comparison procedure with the PROC COMPARE statement.
- Use the BASE=-option to specify the name of the first dataset.
- Use the COMPARE=-option to specify the name of the second dataset.
- Finish and execute the procedure with the RUN statement.
How do you extract duplicates in SAS?
The first method, and one that is popular with SAS professionals everywhere, uses PROC SORT to remove duplicates. The SORT procedure supports three options for the removal of duplicates: DUPOUT=, NODUPRECS, and NODUPKEYS.
How do you compare observations in SAS?
- Declare the PROCLIB SAS library.
- Set the SAS system options.
- Sort the data sets by the ID variable.
- Specify the data sets to compare.
- Create the Result output data set and include all unequal observations and their differences.
- Specify the ID variable.
How do you sort and remove duplicates in SAS?
In SAS, you can not only use the PROC SORT procedure to order a data set, but also to remove duplicate observations. To do so you add the keyword NODUPKEY to the sort clause. Depending on which duplicates you want to remove, you need to modify the BY statement.
What does Proc Compare do in SAS?
The COMPARE procedure compares the contents of two SAS data sets, selected variables in different data sets, or variables within the same data set. PROC COMPARE compares two data sets: the base data set and the comparison data set. The procedure determines matching variables and matching observations.
How do you remove duplicates in SQL SAS?
How do I compare two SAS codes?
How to compare SAS programs in SAS Enterprise Guide
- Install a file comparison tool. I like WinMerge.
- Set your File Comparison options in SAS Enterprise Guide. Select Tools->Options, then the File Comparison tab.
- Select the two files that you want to compare.
How do you avoid duplicates in SAS?
The Sort Procedure with the NODUPKEY option is the simplest and most common way of removing duplicate values in SAS. Simply specify the NODUPKEY option in the PROC SORT statement. In the BY statement, specify the variables by which you want to remove duplicates.
How do you count duplicates in SAS?
Re: Fastest way to count number of duplicates proc sort data=have(keep=key1 key2) out=_null_ dupout=dups nodupkey; by key1 key2; run; After which WORK. DUPS will hold at least one of each duplicate key pair (the first value is written to the OUT= data set, which we drop in this case).
Which is the right way to obtain duplicates in SAS?
The Right Way to Obtain Duplicates in SAS. To obtain ALL duplicates of a data set, you can take advantage of first.variable and last.variable. Here is the code to do it with the above example data set of test; you will get both the single observations and the duplicate observations.
When to use proc compare to find duplicates?
If PROC COMPARE finds two successive observations with the same ID values in a data set, then it uses the duplicate observations in the base data set and the comparison data set to compare the observations on a one-to-one basis. When the data sets are not sorted, PROC COMPARE detects only those duplicate observations that occur in succession.
How to merge two datasets in SAS 1.2?
1. 2. And the code piece below is one single step to arrive at your final result, to have MASTER dataset have the updates from WEEKLY without the need to merge them seperately after refining the MASTER dataset. ***But remember that to use DATA MERGE statements, your sas datasets need to be in sorted order by application_id field.
How to identify duplicate variables in a data set?
One way to identify duplicate variables is with PROC COMPARE, which is commonly used to compare two data sets, but can also compare variables in the same data set. It can accept a list of variable pairs to compare and determine which variable pairs are identical.