This works as expected: library(dplyr) f <- function(x = c(am, vs)) mtcars %>% select({{x}}) How would I rewrite the function (let's call it f2) such that f2 selects only the first elem...

I'm having this error when trying to attach package tidyselect and when trying to call tidyselect::any_function. The error happens in Rstudio or command line alike, in RStudio it is triggered as so...

I'm dealing with a big dataframe that has a number of columns I want to group by. I'd like to do something like this: output <- df %>% group_by(starts_with("GEN", ignore.case=TRUE...

I attempt to use read_csv from {readr} to read a CSV file into R. To demonstrate my real issue, I reset the argument guess_max to 5 at first (default is 1000) library(readr) formals(read_csv)$guess...

I would like to obtain a generic formula to arrange dataframes with a varying number of columns. For example, in this case the dataframe contains "categ_1, categ_2, points_1, points_2": ...

I have a .csv file like this (except that the real .csv file has many more columns): library(tidyverse) tibble(id1 = c("a", "b"), id2 = c("c", "d"), ...

I am generating data frames of 1s and 0s as follows: library(tidyverse) library(glue) num_var <- 3 rep(list(c(0L, 1L)), num_var) %>% set_names(glue("var_{seq_len(num_var)}")) %>% ex...

Suppose I have a data frame with a bunch of columns where I want to do the same NA replacement: dd <- data.frame(x = c(NA, LETTERS[1:4]), a = rep(NA_real_, 5), b = c(1:4, NA)) For example, in t...

I have started to receive a warning when using selecting functions within tidyverse packages. Example: library(dplyr) set.seed(123) df = data.frame( "id" = c(rep("G1", 3), rep(...

library(tidyverse) df <- tibble(Date = c(rep(as.Date("2020-01-01"), 3), NA), col1 = 1:4, thisCol = c(NA, 8, NA, 3), thatCol = 25:28, col999 = rep(99, 4)) #> # A tibble: 4 x 5 #> Date c...

Here's a simplified version of a function I have in a package that uses the ... argument and tidyselect to select variables: # this toy function just selects the ... variables foo <- function(d...

library(tidyverse) iris %>% as_tibble() %>% select(everything()) #> # A tibble: 150 x 5 #> Sepal.Length Sepal.Width Petal.Length Petal.Width Species #> <dbl> <dbl> <d...

library(tidyverse) df <- tibble(x1 = c("A", "A", "A", "B", "B", "B"), x2 = c(NA, 8, NA, NA, NA, 5), x3 = c(3, 6, 5, 9, 1, 9)) #> # A tibble: 6 x 3 #> x1 x2 x3 #> <chr> <dbl&g...

I have a helper function (say foo()) that will be run on various data frames that may or may not contain specified variables. Suppose I have library(dplyr) d1 <- data_frame(taxon=1,model=2,z=3...

Let's say I have a tibble where I need to take multiple variables and mutate them into new multiple new variables. As an example, here is a simple tibble: tb <- tribble( ~x, ~y1, ~y2, ~y3, ~...

I am trying to filter specific rows of my tibble using the dplyr::filter() function. Here is part of my tibble head(raw.tb): A tibble: 738 x 4 geno ind X Y <chr> <chr> <int> ...