Use SAS informats to convert text to native data types. Let's map these steps to the SAS programming language: For this stepĭATA step, with parsing functions such as FIND, SCAN, and regular expressions via PRXMATCH. This applies to those web sites that serve up lots of information in paginated form, and you want to collect all available pages of data. If necessary, repeat for subsequent pages.

Process the source content of the page - usually HTML source code - and parse/save the data fields you need.Fetch the contents of the target web page.New SAS users often ask whether there are similar packages available in the SAS language, perhaps not realizing that Base SAS is already well suited to this task - no special bundles necessary. Python and R users have their favorite packages that they use for scraping data from the web. When students/researchers want to apply data science techniques to analyze collect and analyze that data, they often turn to 'data scraping.' What is 'data scraping?' I define it as using a program to fetch the contents of a web page, sift through its contents with data parsing functions, and save its information into data fields with a structure that facilitates analysis. The internet is rich with data, and much of that data seems to exist only on web pages, which - for some crazy reason - are designed for humans to read.