Common object types for use with sas are files and directories. An introduction to the sas system uc berkeley statistics. When you wish to process an already created sas data set instead of raw data, the set. The sortinplace paradigm made the most of the limited resources at the time, and almost every sas program had at least one proc sort in it. If proc freq is required on all the variables of a sas data set.
Taming the proc transpose sas proceedings and more. Proc transpose is a powerful yet underutilized proc in the base sas toolset. The transpose procedure or how to turn it around sas support. We will begin with a small data set with only one variable to be reshaped. The proc transpose is part of the sas language that does not get used as much as it should. The proc transpose can save time and complexity once it is properly explained. You can use the attrib, format, label, and where statements. This article will walk through the different uses of proc transpose, providing a. To create transposed variable, the procedure transposes the values of an observation in the input data set into values of a variable in the output data set. One of the reasons for performing data transformation is that different statistical procedures require different data shapes.
From the first output of proc print, we see that the data now is in long format except that we dont have a numeric variable indicating year. The first step in the process is to alter the dataset so that we can distinguish the. Type is the by variable, and sold, notsold, repaired, and junked are the variables to transpose. Transposing one group of variables for a data set in wide format such as the one below, we can reshape it into long format using proc transpose. So, well need to use different options and statements in proc transpose to create our result. Selects observations from sas data sets that meet a particular condition that is true. Faster processing is possible because inmemory tables are manipulated locally on the server instead of being transferred across a relatively slow network connection. The proc transpose is part of the sas language that does not get used as. Now processing and presentation can be optimized separately from. For a list, see dictionary of sas global statements in sas global statements. Visualizing proc transpose sas proceedings and more.
There are several ways to reshape data from a long to a wide format in sas. Sas statistical analysis system is one of the most popular software for data analysis. These advantages include reduced network traffic, and the potential for faster processing. This tutorial explains the basic and intermediate applications of proc transpose with examples. Proc transpose provides the ability to go from a long dataset where there are multiple rows for a given subject to a wide dataset where there are multiple columns for a subject. It is widely used for various purposes such as data management, data mining, report writing, statistical analysis, business modeling, applications development and data warehousing. This function if achieved in a data step can be much more cumbersome to code. Q1 q2 q3 q4 a 1 2 3 4 b 1 2 3 4 c 1 2 3 d 1 2 e 1 2 3 4 i have data like above and would like to import and reshape the data into what it looks like. Getting your data in shape with proc transpose pharmasug.
Proc transpose can be used to rotate transpose sas data sets. The original variables all had comma sas formats note. Transposing multiple variables in a sas data set within a single macro call. We want to transpose data values within groups into rows. Proc transpose as sas documentation says, the transpose procedure can often eliminate the need to write a lengthy data step to achieve the same result. Learn the basics of proc transpose douglas zirbel, wells fargo and co. Data transposition with proc report midwest sas users group. The simplest possible case of transposing switches the rows and columns of a matrix. For each by group, proc transpose creates one observation for each variable that it transposes. Proc transpose rearranges columns and rows of sas datasets, but its. Proc transpose to issue a warning message and stop. In sas, two commonly used methods for transposing data are using either the tranpose procedure or array processing in the data step. It contains three sample sas input files, a set of basic proc transpose variations, and their output results.
The following will illustrate how to reshape data from long to wide using the data step. Rotated1 created by proc transpose produces report 2. When a by statement is used with proc transpose, a variety of manipulations. The ability to effectively transpose a data set is very important when working with different data structures and different data standards. If applied to a traditional dataset, this would make it so that there was one row per variable, and one column per subject. This paper presents an easy beforeandafter approach to learning proc transpose. An easier and faster way to untranspose a wide file. Its a very powerful procedure when you need to change the shape of the data. If however two or more variables need to be transposed, you need to transpose each variable separately and then merge the transposed data sets, which can be time consuming. For example, you have data in vertical long format and you are asked to change it to horizontal wide format.
So, you need to use proc print, proc report, or some other sas reporting tool if you want to print the output data. However, if you use the let option in the proc transpose statement, then the procedure issues a warning message. When i transpose this dataset it creates a dataset with 2. The procedure pads the output data set with missing values if the number of observations in the input data set and the number of variables it transposes are. To print the output data set from the proc transpose step, use proc print, proc report, or another sas reporting tool. For example, you can reshape your data using proc transpose or reshaping the data in a data step. Sas tutorial for beginners to advanced practical guide. Firstobsn specifies the first observation to process. We begin with a basic example of the proc transpose procedure for those readers not acquainted with the procedure.
Before you can use the s3 procedure, you need an amazon web service aws key id and secret. Example 2 on page 1280 out outputdataset names the output data set. You can find multiple examples in the sashelp library to help illustrate what a long dataset looks like. For reference here and use later, we store the names in character variable origvar. Sas will use the data set naming convention data1, data2, etc. Sometimes you need to reshape your data which is in a long format shown below famid year faminc 1 96 40000 1 97 40500 1 98 4 2 96 45000 2 97 45400 2 98 45800 3 96 75000 3 97 76000 3 98 77000.
Proc freq computes the same information, but does not require sorted data. A concrete example of the start data and the transpose used would help. For more information, see statements with the same function in multiple procedures. In this case, we need to sort the data as we are going to use by processing in proc transpose. Below is an example of using sas proc transpose to reshape the data from a long to a wide format. Sas data set options dropvariables excludes variables from processing. Running proc transpose with cas actions has several advantages over processing within sas. Proc sql a primer for sas programmers jimmy defoor citi card irving, texas the structured query language sql has a very different syntax and, often, a very different method of creating the desired results than the sas data step and the sas procedures. Proc transpose in its simplest form transposes all numeric variables in the. Abstract proc transpose is an extremely powerful tool for making long files wide, and wide files less wide or long, but getting it to do what you need often involves a lot of time, effort, and a substantial knowledge of sas functions and data step processing. Thus, if we run the following simple proc transpose step. Now well use proc transpose to create a wide table. Reshaping data long to wide using the data step sas.
Because the copy statement copies variables directly to the output data set, the number of observations in the output data set is equal to the number of observations in the input data set. Using proc transpose mainly requires grasping the syntax and recognizing how to apply different statements and options in proc transpose to different types of data transposition. One of the reasons that this is done is that it is more efficient to store your data in a vertical format and processing the data is easier in a horizontal. For a data set in wide format such as the one below, we can reshape it into long format using proc transpose. If outputdataset does not exist, proc transpose creates it using the datan naming convention. Instead, for each by group, proc transpose creates one observation for each variable that it transposes. This paper will provide a non technical approach to understanding the transpose procedure by showing the programmer how to visualize the expected output. Transposition with by groups shows what happens when you transpose a data set with by groups. Li, city of hope national medical center, duarte, ca abstract a common data managing task for sas programmers is transposing data. Data transposition is the process of restructuring values of a sas data set by turning selected variables into observations. Base sas, macros, routines, functions, sas data integration studio, sas in mainframes, sas webreport studio, sas enterprise guide, proc compare sas statistical analysis system search web.
The transpose procedure 4 by statement 1273 default. There is a summary sheet at the end of the paper as well for later reference. Transposing this matrix would turn it into a 3x2 matrix 3 rows, 2. How to reshape data wide to long using proc transpose. For more information, see indatabase processing for proc transpose. Daniel boisvert, genzyme corporation, cambridge ma shafi chowdhury, shafi consultancy, london england. Working with variables most of the time, youll need to make modifications to your variables before you can analyze your data. It is very helpful when needing to shift data from rows to columns or vice versa.
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