5 Approaches to Identify Blank Columns in SAS Datasets
5 Approaches to Identify Blank Columns in SAS Datasets 5 Approaches to Identify Blank Columns in SAS Datasets Author: Sarath Date: September 5, 2024 When working with large datasets in SAS, it’s crucial to ensure the integrity of your data. One common task is identifying columns that are completely blank, meaning they contain no non-missing values. In this article, we'll explore five different methods to efficiently find blank columns in SAS datasets, along with examples for each approach. 1. Using PROC MEANS or PROC SUMMARY The simplest way to identify blank columns is by using PROC MEANS or PROC SUMMARY . These procedures provide a summary of missing values for both numeric and character variables. You can quickly determine which columns are fully blank by checking the output for variables with 100% missing values. proc means data=your_dataset nmiss; var _numeric_; /* For numeric variables */ run; proc me...