![]() # Newly created variables are available immediately starwars %>% select ( name, mass ) %>% mutate ( mass2 = mass * 2, mass2_squared = mass2 * mass2 ) #> # A tibble: 87 × 4 #> name mass mass2 mass2_squared #> #> 1 Luke Skywalker 6 #> 2 C-3PO 0 #> 3 R2-D2 32 64 4096 #> 4 Darth Vader 14 #> 5 Leia Organa 49 98 9604 #> 6 Owen Lars 10 #> 7 Beru Whitesun lars 0 #> 8 R5-D4 32 64 4096 #> 9 Biggs Darklighter 4 #> 10 Obi-Wan Kenobi 6 #> # ℹ 77 more rows # As well as adding new variables, you can use mutate() to # remove variables and modify existing variables. ![]() Should appear (the default is to add to the right hand side). ![]() "none" doesn't retain any extra columns from. This is useful if you generate new columns, but no longer need "unused" retains only the columns not used in. This is useful for checking your work, as it displays inputs Forĭetails and examples, see ?dplyr_by.keepĬontrol which columns from. Group by for just this operation, functioning as an alternative to group_by(). The name gives the name of the column in the output.Ī vector of length 1, which will be recycled to the correct length.Ī vector the same length as the current group (or the whole data frameĪ data frame or tibble, to create multiple columns in the output.
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