#> 5 3.6 1.4 0.2 setosa By clicking “Post Your Answer”, you agree to our To subscribe to this RSS feed, copy and paste this URL into your RSS reader. #> 1.59 1.10 1.4 0.2 setosa

In tidyverse/dplyr: A Grammar of Data Manipulation. Stack Overflow for Teams is a private, secure spot for you and Description Usage Arguments Value Useful mutate functions Grouped tibbles Methods See Also Examples. The names of the new columns are derived from the names of the disambiguation algorithm are subject to change in dplyr 0.9.0.# All variants can be passed functions and additional arguments,# purrr-style.

#> Dart… 0.795 0.228 none white yellow 41.9 male mascu… #> gold yellow 112 none mascu… #> auburn, w… fair blue-gray 57 male mascu… #> 1.61 1.28 1.4 0.2 setosa

Private self-hosted questions and answers for your enterpriseProgramming and related technical career opportunities #> name height mass hair_color skin_color eye_color birth_year sex gender #> 4.4 2.9 1.4 0.2 setosa _at affects variables selected with a character vector or vars()_if affects variables selected with a predicate function:A predicate function to be applied to the columns #> 1.53 1.22 1.4 0.3 setosa #> 4 3 1 0 setosa

Learn more at tidyverse.org. #> auburn, w… fair blue-gray 57 male mascu… By each element I meant each element in the column. #> black light brown 24 male mascu… #> 4 3 1 0 setosa


New variables overwrite existing variables of the same name. #> 4 3 1 0 setosa
#> brown light brown 19 fema… femin…

#> blond fair blue 19 male mascu…

#> 4 2 1 0 setosa

I'll spare you the details, but recently, not using Note that when testing multiple conditions, the code would be more readable and less error-prone if we use Thanks for contributing an answer to Stack Overflow! When grouping on both teamID and yearID the value(s) for NYA in 2012 are all NA. #> 5.1 3.5 1.4 0.2 setosa - 4.9 3 1.4 0.2 setosa - 4.7 3.2 1.3 0.2 setosa - 4.6 3.1 1.5 0.2 setosa - 5 3.6 1.4 0.2 setosa - 5.4 3.9 1.7 0.4 setosa - 4.6 3.4 1.4 0.3 setosa - 5 3.4 1.5 0.2 setosa - 4.4 2.9 1.4 0.2 setosa - 4.9 3.1 1.5 0.1 setosa -# … with 140 more rows, and 7 more variables: Sepal.Width_scale #> 4 3 1 0 setosa #> # … with 77 more rows, and 5 more variables: homeworld # You can also supply selection helpers to _at() functions but you have #> 4 3 1 0 setosa #> #> 5.1 3.5 1.4 0.2 setosa - 4.9 3 1.4 0.2 setosa - 4.7 3.2 1.3 0.2 setosa - 4.6 3.1 1.5 0.2 setosa - 5 3.6 1.4 0.2 setosa - 5.4 3.9 1.7 0.4 setosa - 4.6 3.4 1.4 0.3 setosa - 5 3.4 1.5 0.2 setosa - 4.4 2.9 1.4 0.2 setosa - 4.9 3.1 1.5 0.1 setosa -# … with 140 more rows, and 7 more variables: Sepal.Width_fn1 mutate() adds new variables and preserves existing ones; transmute() adds new variables and drops existing ones.