Aan de slagGa gratis aan de slag

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.

Deze oefening maakt deel uit van de cursus

Categorical Data in the Tidyverse

Cursus bekijken

Oefeninstructies

  • Use str_remove to remove everything before and including "rude to " (with the space at the end) in the response_var column.
  • Use str_remove to remove "on a plane" from the response_var column.

Praktische interactieve oefening

Probeer deze oefening eens door deze voorbeeldcode in te vullen.

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, ___))
Code bewerken en uitvoeren