Capture groups are simply sections of the regex that you wrap in parenthesis. We’ll create capture groups containing each name, quantity, and item. By using capture groups, we can return a matrix where each column contains a specific piece of information. ![]() Now this is a big step up from where we started, but we don’t really care about the word “has”, and we want to be able to make a data frame out of the quantities. You can see in the output each row of the matrix is a character string with the details for each person. We can also write this quantifier and omit the upper bound like \\s\\w+). Match a group of characters: We can find all of the vowels in our string by putting every vowel in brackets, for example,.There are multiple things we can do with character sets: Character SetsĬharacter sets represent options inside of brackets, with regex matching only one of the options. This is not an exhaustive list, but is plenty to help us hit the ground running. There are several concepts that drive regex: There is a time and place for them, but what if we want to know how many total food items there are at the picnic? Who are all the people with items? What if we need this data in a data frame for further analysis? This is where you will start to see the benefits of regex. "Drew has 3 watermelons, Shawn has 4 hamburgers, Karina has 12 tamales, and Anna has 6 soft pretzels" The resulting string will show that Shawn now has 4 hamburgers. If I want to pull every instance of one person’s name from this string, I would simply pass the name and basic_string to str_extract_all(): We can use it to demonstrate the basic usage of the regex functions: basicString <- "Drew has 3 watermelons, Alex has 4 hamburgers, Karina has 12 tamales, and Anna has 6 soft pretzels" Here’s an example string with what everyone is bringing to the picnic. Think back to the times before social distancing and imagine a nice picnic in the park, like the image above. They have pretty straightforward applications without adding regex. You may have already used these functions. str_replace_all(string, pattern, replacement): This function returns string with instances of pattern in string replaced with replacement. ![]()
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