If you use Google Analytics, you will often come across regular expressions or Regex when analyzing data. Regular expressions allow you to gather specific data, but you may be confused about how to use them with seemingly complex strings. If you read this post, you will understand regular expressions, and you can use them to analyze data in Google Analytics and Google Data Studio more easily.
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1. What is a regular expression (Regex)?
2. Regular expression patterns and special characters
3. Regular expression tests and examples
4.Recommendation of regular expression sites
What is a regular expression Regex?
A regular expression, or regular expression, expresses a string of specific rules within a wide range of data and finds and matches detailed patterns. In other words, a regular expression is a formal language used to express a set of strings with specific rules. Regular expressions are very useful for data mining because they allow you to quickly find detailed patterns by filtering through strings. Items that use regular expressions in Google Analytics Construction Email List include audiences, content groups, goals, view filters, segments, and channel groups. Google regular expressions have a different syntax from regular expressions used in Python and Java.
Regular expression patterns and special characters
Regular expressions include Wild Cards, Anchors, Groups, and Escapes.
When you want to express with characters other than regular expressions
? as a non-regex character
g Match any character and multiple lines
i English case insensitive match
m match multiple lines
y 1 match only at the index specified by the lastIndex property
Regular expression tests and examples
Sites where you can test regular expressions
We looked at regular expressions that help simplify data analysis. Using regular expressions, you can find data quickly by efficiently filtering only the strings you want. For those of you who have had a hard time filtering out all of them when Therefore CMO Email List analyzing in Google Analytics or Data Studio, I highly recommend using regular expressions.