{"id":11814,"date":"2018-03-27T04:50:07","date_gmt":"2018-03-26T23:20:07","guid":{"rendered":"https:\/\/data-flair.training\/blogs\/?p=11814"},"modified":"2021-05-09T13:16:42","modified_gmt":"2021-05-09T07:46:42","slug":"sas-concatenate-datasets","status":"publish","type":"post","link":"https:\/\/data-flair.training\/blogs\/sas-concatenate-datasets\/","title":{"rendered":"Different Cases of SAS Concatenate Data Sets with SET Statement"},"content":{"rendered":"

Previously, we studied SAS Functions<\/strong>, now we will move on to a very easy and interesting method to combine two data sets in SAS programming i.e. SAS concatenate data sets.<\/p>\n

After the end of this tutorial, you will be able to understand SAS concatenate datasets and different cases of concatenating data sets.<\/p>\n

What is SAS Concatenate Data Sets?<\/h3>\n

We come across different types of SAS datasets<\/strong> and many times we would want to combine two data sets to have a clear idea about our analysis. The SET statement<\/strong> is used to concatenate two datasets in SAS.<\/p>\n

If there are two data sets, say one has 2 observations and the other has 3 observations, then, our SAS concatenate dataset will have 5 observations. The order of observations is sequential. All observations from the first data set are followed by all observations from the second data set, and so on.<\/p>\n

Below is the syntax of a SET statement in SAS<\/p>\n

SET data-set 1 data-set 2 data-set 3.....;<\/pre>\n
Data-set 1, data-set 2 and data-set 3 are names of the data sets we wish to combine.<\/p>\n
For example<\/strong> – suppose the data set\u00a0store1<\/em>\u00a0contains three variables,\u00a0store<\/em>\u00a0(number),\u00a0day\u00a0<\/em>(of the week), and\u00a0sales<\/em>\u00a0(in dollars):<\/p>\n
Store\u00a0 \u00a0 \u00a0 \u00a0 Day\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0Sales
\n1\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0M\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a01200
\n1\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0T\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 1435
\n1\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0W\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a01712
\n1\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0R\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 1529
\n1\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0F\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 1920
\n1\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0S\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 2325<\/p>\n
and the data set\u00a0store2<\/em>\u00a0contains the same three variables:<\/p>\n
Store\u00a0 \u00a0 \u00a0 \u00a0 \u00a0Day\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0Sales
\n2\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 M\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 2215
\n2\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 T\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a02458
\n2\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 W\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 1798
\n2\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 R\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a01692
\n2\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 F\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a02105
\n2\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 S\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a02847<\/p>\n
For SAS concatenate data sets, you simply specify a list of data set names in\u00a0one<\/em>\u00a0SET statement.<\/p>\n
DATA store1;\r\n\u00a0\u00a0\u00a0\u00a0\u00a0 input Store Day $ Sales;\r\n\u00a0\u00a0\u00a0\u00a0\u00a0 DATALINES;\r\n1\u00a0   M\u00a0   1200\r\n1\u00a0   T\u00a0\u00a0  1435\r\n1\u00a0   W  \u00a0 1712\r\n1\u00a0\u00a0  R\u00a0   1529\r\n1\u00a0\u00a0  F\u00a0\u00a0  1920\r\n1\u00a0\u00a0  S\u00a0\u00a0  2325\r\n;\r\nRUN;\r\nDATA store2;\r\n\u00a0\u00a0\u00a0\u00a0\u00a0 input Store Day $ Sales;\r\n\u00a0\u00a0\u00a0\u00a0\u00a0 DATALINES;\r\n2\u00a0   M\u00a0  2215\r\n2\u00a0   T\u00a0\u00a0 2458\r\n2\u00a0   W\u00a0  1798\r\n2\u00a0\u00a0  R\u00a0  1692\r\n2\u00a0\u00a0  F\u00a0\u00a0 2105\r\n2\u00a0\u00a0  S\u00a0\u00a0 2847\r\n;\r\nRUN;\r\nDATA bothstores;\r\n\u00a0\u00a0\u00a0\u00a0 \u00a0set store1 store2;\r\nRUN;\r\nPROC PRINT data = bothstores;\r\n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 title \u2018 The bothstores dataset\u2019;\r\nRUN;<\/pre>\n
The output of the above program will look like:
\nStore\u00a0 \u00a0 \u00a0 Day\u00a0 \u00a0 \u00a0 \u00a0 Sales
\n1\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0M\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a01200
\n1\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0T\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a01435
\n1\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0W\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 1712
\n1\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0R\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a01529
\n1\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0F\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a01920
\n1\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0S\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a02325
\n2\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0M\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a02215
\n2\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0T\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a02458
\n2\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0W\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 1798
\n2\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0R\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a01692
\n2\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0F\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 2105
\n2\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0S\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a02847<\/p>\n
Different Cases of Concatenating Data Sets<\/h2>\n
In the above example, we saw that both datasets had three variables so it was easy to concatenate them. But, what happens if the variables are different, or of different lengths or of different names? Let us understand this from SAS Concatenate Datasets in different\u00a0cases.<\/p>\n
\"SAS<\/a><\/p>\n
1. Different Names of Variables<\/h3>\n
In this case, both the data sets have different names for their variables. So, when we try and concatenate, an error might get displayed.<\/p>\n
In order to overcome this, when we concatenate the datasets, we will rename the variables so that their name appears as one in the concatenated data set. Let us look at how we can do this.<\/p>\n
Example:<\/strong><\/p>\n
In the below example data set x1 has the variable name x1inc whereas the data set x2 has the variable name x2inc. But both of these variables represent the same type(numeric). We apply the RENAME function in the SET statement as shown below:<\/p>\n
DATA x1;\r\nINPUT empid name $ x1inc ;\r\nDATALINES;\r\n2 Art\u00a0 22000\r\n1 Bill 30000\r\n3 Paul 25000\r\n;\r\nRUN;\u00a0\r\nDATA x2;\r\nINPUT empid name $ x2inc ;\r\nDATALINES;\r\n1 Bess 15000\r\n3 Pat\u00a0 50000\r\n2 Amy\u00a0 18000\r\n;\r\nRUN;\u00a0\r\nDATA x3;\u00a0\r\nSET x1(RENAME=(x1inc=inc))x2(RENAME=(x2inc=inc));\r\nRUN;\u00a0\r\nPROC PRINT DATA=x3;\r\nRUN;<\/pre>\n
Output-<\/strong><\/p>\n
OBS\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0EMPID\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 NAME\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0INC
\n1\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a02\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 Art\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 22000
\n2\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a01\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 Bill\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 30000
\n3\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a03\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 Paul\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a025000
\n4\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a01\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 Bess\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 15000
\n5\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a03\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 Pat\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 50000
\n6\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a02\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 Amy\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 18000<\/p>\n
2. Different Variable Attributes<\/h3>\n
We talked about variable attributes in earlier classes which are a type, length, label, etc. Now, what happens if these differ. Again, while combining datasets, we can specify the length in our SET statement, that we want to keep or the data type of the variables.<\/p>\n
Let us look at an example:<\/p>\n
In the below example, the variable name is of length 3 in the first data set and 4 in the second. When concatenating, we apply the LENGTH statement in\u00a0SAS concatenate data set to set the name length to 7 or the sum of two lengths.<\/p>\n
DATA x1; \u00a0\u00a0\r\nINPUT empid name $3. inc;\r\nDATALINES;\u00a0 \u00a0\r\n2 Art\u00a0 22000 \u00a0\r\n1 Bob\u00a0 30000 \u00a0\r\n3 Tom\u00a0 25000 \u00a0\r\nRUN;\r\nDATA x2;\u00a0\u00a0\r\nINPUT empid name $4. inc;\r\nDATALINES;\u00a0 \u00a0\r\n1 Bess 15000\u00a0 \u00a0\r\n3 Rory 50000\u00a0 \u00a0\r\n2 Jane 18000\u00a0\r\nRUN;\u00a0 \u00a0\r\nDATA x3; \u00a0\r\nSET x1 x2;\r\nRUN;\r\nPROC PRINT DATA=x1andx2;\r\nRUN;<\/pre>\n
Output-<\/strong>
\nOBS\u00a0 \u00a0 \u00a0 \u00a0 empID\u00a0 \u00a0 \u00a0 \u00a0 \u00a0NAME\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0INC
\n1\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 2\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 Art\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a022000
\n2\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 1\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 Bob\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 30000
\n3\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 3\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 Tom\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 25000
\n4\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 1\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 Bes\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 15000
\n5\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 3\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 Ror\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 50000
\n6\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 2\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 Jan\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 18000<\/p>\n
3. Different Number of Variables<\/h3>\n
If one of the two datasets has more number of variables than the other, then the data set which has less number of variables shows missing values in place of that extra variable.<\/p>\n
Summary<\/h2>\n
Today we learned what is concatenation in SAS, how SAS concatenate data sets in SAS programming. We also discussed different cases of concatenating data sets in SAS.<\/p>\n
Hope you find the explanation helpful. If you have any queries, feel free to ask in the comment section.<\/p>\n","protected":false},"excerpt":{"rendered":"
Previously, we studied SAS Functions, now we will move on to a very easy and interesting method to combine two data sets in SAS programming i.e. SAS concatenate data sets. After the end of...<\/p>\n","protected":false},"author":6,"featured_media":11821,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[59],"tags":[19748,11964,11965],"class_list":["post-11814","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-sas","tag-concatenating-data-sets-cases","tag-sas-concatenate","tag-sas-concatenate-datasets"],"yoast_head":"\nDifferent Cases of SAS Concatenate Data Sets with SET Statement - DataFlair<\/title>\n<meta name=\"description\" content=\"SAS Concatenate Datasets Tutorial covers the explanation of data sets concatenation and Different cases of Concatenating data sets in SAS. 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