rlang

Suppose we have a character vector cols_to_select containing some columns we want to select from a dataframe df , e.g. df <- tibble::data_frame(a=1:3, b=1:3, c=1:3, d=1:3, e=1:3) cols_to_select <- c("b", "d") Suppose also we want to use dplyr::select because it's part of an operation that uses %>% so using select makes the code easy to read. There seem to be a number of ways which this can be achieved, but some are more robust than others. Please could you let me know which is the 'correct' version and why? Or perhaps there is another, better way? dplyr::select(df, cols_to_select) #Fails if

Hi following Programming with dplyr I noticed that one can add a name using quo_name. I was wondering how to do this for multiple columns, eg. like a quos_name of sorts. E.g.: my_mutate <- function(df, expr) { expr <- enquo(expr) mean_name <- paste0("mean_", quo_name(expr)) sum_name <- paste0("sum_", quo_name(expr)) mutate(df, !!mean_name := mean(!!expr), !!sum_name := sum(!!expr) ) } becomes my_mutate <- function(df, ...) { exprs <-quos(...) mean_names <- paste0("mean_", quos_name(exprs)) sum_names <- paste0("sum_", quos_name(exprs)) mutate(df, !!!mean_names := mean(!!!exprs), !!!sum_names :=

Trying to write a relatively simple wrapper to produce some plots, but can not work out how to specify tidy evaluation of grouping variables specified as ... an example function that facets variables but doesn't distinguish by grouping... my_plot <- function(df = starwars, select = c(height, mass), ...){ results <- list() ## Tidyeval arguments quo_select <- enquo(select) quo_group <- quos(...) ## Filter, reshape and plot results$df <- df %>% dplyr::filter(!is.na(!!!quo_group)) %>% dplyr::select(!!quo_select, !!!quo_group) %>% gather(key = variable, value = value, !!!quo_select) %>% ## Specify

I am trying to write a function in tidyverse/dplyr that I want to eventually use with lapply (or map ). (I had been working on it to answer this question , but came upon an interesting result/dead-end. Please don't mark this as a duplicate - this question is an extension/departure from the answers that you see there.) Is there 1) a way to get a list of quoted variables to work inside a dplyr function (and not use the deprecated SE_ functions) or is there 2) some way to feed a list of unquoted strings through an lapply or map I have used the Programming in Dplyr vignette to construct what I

I would like to dynamically input a variable name using dplyr programming syntax, however, as many have described this can be quite confusing. I've played around with various combinations of quo/enquo !! etc. to no avail. Here is the simplest form of my code library(tidyverse) df <- tibble( color1 = c("blue", "blue", "blue", "blue", "blue"), color2 = c("black", "black", "black", "black", "black"), value = 1:5 ) num <- 2 df %>% mutate(color3 = !!(paste0("color", num))) #> # A tibble: 5 x 4 #> color1 color2 value color3 #> <chr> <chr> <int> <chr> #> 1 blue black 1 color2 #> 2 blue black 2 color2

I am wrestling with programming using dplyr in R to operate on columns of a data frame that are only known by their string names. I know there was recently an update to dplyr to support quosures and the like and I've reviewed what I think are the relevant components of the new "Programming with dplyr" article here: http://dplyr.tidyverse.org/articles/programming.html . However, I'm still not able to do what I want. My situation is that I know a column name of a data frame only by its string name. Thus, I can't use non-standard evaluation in a call to dplyr within a function or even a script