tidyeval

问题 I've trying to use Tidy Eval and Stringr togheter inside a mutate pipe, but every time I run it it gives me an undesirable result. Instead of changing the letter 'a' for the letter 'X', it overwrite the entire vector with the column name, as you can see in the example below, that uses the IRIS dataset. text_col="Species" iris %>% mutate({{text_col}} := str_replace_all({{text_col}}, pattern = "a", replacement = "X")) result: structure(list(Sepal.Length = c(5.1, 4.9, 4.7, 4.6, 5, 5.4, 4.6, 5, 4

问题 I'm trying to write a custom case_when function to use inside dplyr. I've been reading through the tidyeval examples posted in other questions, but still can't figure out how to make it work. Here's a reprex: df1 <- data.frame(animal_1 = c("Horse", "Pig", "Chicken", "Cow", "Sheep"), animal_2 = c(NA, NA, "Horse", "Sheep", "Chicken")) translate_title <- function(data, input_col, output_col) { mutate(data, !!output_col := case_when( input_col == "Horse" ~ "Cheval", input_col == "Pig" ~ "Рorc",

问题 I am trying to recode several variables but with different recode schemes. The recoding scheme is saved in a list where each element is a named vector of the form old = new . Each element is the recoding scheme for each variable in the data frame I am using the mutate_at function and the recode . I think that the problem is that I cannot extract the variable name to use it to get the correct recoding scheme from the list I tried deparse(substitute(.)) as in here and also this didn;t help Also

问题 I am trying to recode several variables but with different recode schemes. The recoding scheme is saved in a list where each element is a named vector of the form old = new . Each element is the recoding scheme for each variable in the data frame I am using the mutate_at function and the recode . I think that the problem is that I cannot extract the variable name to use it to get the correct recoding scheme from the list I tried deparse(substitute(.)) as in here and also this didn;t help Also

问题 So I want to make a function with unite() from tidyr, but it does not seem to work.. library(dplyr, warn.conflicts = FALSE) library(tidyr, warn.conflicts = FALSE) library(stringr, warn.conflicts = FALSE) mtcars %>% as_tibble() %>% select(mpg , cyl) %>% mutate_all(as.character) %>% unite(col = hello, sep = "/") %>% mutate(hello = str_replace(hello, "/", "")) #> # A tibble: 32 x 1 #> hello #> <chr> #> 1 216 #> 2 216 #> 3 22.84 #> 4 21.46 #> 5 18.78 #> 6 18.16 #> 7 14.38 #> 8 24.44 #> 9 22.84 #>

问题 So I want to make a function with unite() from tidyr, but it does not seem to work.. library(dplyr, warn.conflicts = FALSE) library(tidyr, warn.conflicts = FALSE) library(stringr, warn.conflicts = FALSE) mtcars %>% as_tibble() %>% select(mpg , cyl) %>% mutate_all(as.character) %>% unite(col = hello, sep = "/") %>% mutate(hello = str_replace(hello, "/", "")) #> # A tibble: 32 x 1 #> hello #> <chr> #> 1 216 #> 2 216 #> 3 22.84 #> 4 21.46 #> 5 18.78 #> 6 18.16 #> 7 14.38 #> 8 24.44 #> 9 22.84 #>

问题 So I want to make a function with unite() from tidyr, but it does not seem to work.. library(dplyr, warn.conflicts = FALSE) library(tidyr, warn.conflicts = FALSE) library(stringr, warn.conflicts = FALSE) mtcars %>% as_tibble() %>% select(mpg , cyl) %>% mutate_all(as.character) %>% unite(col = hello, sep = "/") %>% mutate(hello = str_replace(hello, "/", "")) #> # A tibble: 32 x 1 #> hello #> <chr> #> 1 216 #> 2 216 #> 3 22.84 #> 4 21.46 #> 5 18.78 #> 6 18.16 #> 7 14.38 #> 8 24.44 #> 9 22.84 #>

问题 I'm trying to develop a deeper understanding of using the dot (".") with dplyr and using the .data pronoun with dplyr . The code I was writing that motivated this post, looked something like this: cat_table <- tibble( variable = vector("character"), category = vector("numeric"), n = vector("numeric") ) for(i in c("cyl", "vs", "am")) { cat_stats <- mtcars %>% count(.data[[i]]) %>% mutate(variable = names(.)[1]) %>% rename(category = 1) cat_table <- bind_rows(cat_table, cat_stats) } # A tibble:

问题 I'm trying to develop a deeper understanding of using the dot (".") with dplyr and using the .data pronoun with dplyr . The code I was writing that motivated this post, looked something like this: cat_table <- tibble( variable = vector("character"), category = vector("numeric"), n = vector("numeric") ) for(i in c("cyl", "vs", "am")) { cat_stats <- mtcars %>% count(.data[[i]]) %>% mutate(variable = names(.)[1]) %>% rename(category = 1) cat_table <- bind_rows(cat_table, cat_stats) } # A tibble:

问题 I'm trying to develop a deeper understanding of using the dot (".") with dplyr and using the .data pronoun with dplyr . The code I was writing that motivated this post, looked something like this: cat_table <- tibble( variable = vector("character"), category = vector("numeric"), n = vector("numeric") ) for(i in c("cyl", "vs", "am")) { cat_stats <- mtcars %>% count(.data[[i]]) %>% mutate(variable = names(.)[1]) %>% rename(category = 1) cat_table <- bind_rows(cat_table, cat_stats) } # A tibble: