Cleaning up strings
In this lesson, we learned some basics of "regex," or regular expressions, which allow us to capture general patterns. We've covered two notations:
Expression | Does this |
---|---|
. |
matches any character |
* |
zero or more times |
For example, ".*science " would match "data science " in the string "data science rocks!"
Let's use what we've learned to change the response_var
in the dataset you created in the previous lesson, gathered_data
.
This exercise is part of the course
Categorical Data in the Tidyverse
Exercise instructions
- Use
str_remove
to remove everything before and including "rude to " (with the space at the end) in theresponse_var
column. - Use
str_remove
to remove "on a plane" from theresponse_var
column.
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
gathered_data %>%
# Remove everything before and including "rude to " (with that space at the end!)
mutate(response_var = ___(response_var, ___)) %>%
# Remove "on a plane"
mutate(response_var = ___(response_var, ___))