Sometimes rather than specify what columns you want to select from a data frame, it’s easier to state what columns you do not want to select. dplyr‘s select() function also enables you to do just that! Consider a customers data frame that contains biographical information for the customers of your business:
| name | address | phone | age |
|---|---|---|---|
| Martha Jones | 123 Main St. | 234-567-8910 | 28 |
| Rose Tyler | 456 Maple Ave. | 212-867-5309 | 22 |
| Donna Noble | 789 Broadway | 949-123-4567 | 35 |
| Amy Pond | 98 West End Ave. | 646-555-1234 | 29 |
| Clara Oswald | 54 Columbus Ave. | 714-225-1957 | 31 |
You are interested in analyzing where your customers live and how old they are. For your analysis, you do not care about the name and phone associated with a customer, only their address and age. To exclude the columns you do not need:
- the data frame
customersis piped intoselect() - the columns to remove, prepended with a
-, are given as arguments - a new data frame without the
nameandphonecolumns is returned
Instructions
Select all columns of artists except albums using select() and save the result to no_albums. View no_albums.
Select all columns of artists except genre, spotify_monthly_listeners, and year_founded using select() and save the result to df_cols_removed. View df_cols_removed.