You can also make use of Data Step to import data from csv or text file.Įxample: Import data from a csv file using data step, assuming values are separated by comma(,).Ībove, we looked at multiple methods to load data set in SAS. After that, names of the columns would get stored as VAR1 to VARn.
If first row is not the column name, then we would change getnames=yes to getnames=no. It is assumed that the first row of the data set contains column names. If your data file is a simple text file, you can use following commands: Importing raw text file (Txt) using PROC Import: To disassociate a libref, use a LIBNAME statement and specify the libref and the CLEAR option. If SAS has a libref assigned to an Excel workbook, the workbook cannot be opened in Excel. Worksheet name appears with a dollar sign at the end of the name). We can also create a library from excel files using Libname statement (Each worksheet in the Excel workbook is treated as a SAS data set. For importing CSV file, use CSV for dbms line.xlsx file, simply change xls to xlsx in both the datafile and the dbms line. Importing XLS/ CSV file using PROC Import: Let’s look at the commands to load data from each dataset type mentioned above: In SAS, we can use multiple methods to load data from these sources. The sources of input data sets can be in various formats (.XLS. Part 1: How to load data file(s) into SAS Data set? How to merge / join data set effectively?.How to drop and rename variables in a data set?.How to impute missing values and outliers?.How to recognize missing values and outliers?.How to group variables in SAS to calculate count, average, sum?.
How to remove duplicate values of a variable?.How to generate frequency tables in SAS?.How to create plots (Histogram, Scatter, Box Plot) in SAS?.How to convert a variable to different data type?.How to load data file(s) into SAS Data set?.Since this is an exhaustive guide, it is a good idea to list down all the things I’ll cover: I am hoping that this guide can act as a ready reference for our followers trying to navigate SAS on their own. Let’s get down to work! I will also perform some exercises that will help you understand the concept better. You can look at this article as practical implementation of my previous articles (in SAS). In this guide, I will take a step ahead and show all these steps to explore data sets practically in SAS. These articles featured: variable identification, Univariate and Bivariate analysis, Missing and Outlier identification and treatment and feature engineering. I would like to extend my sincere gratitude to our readers for their overwhelming response on my previous articles on data exploration.
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