using purrr map

tidyverse
#1

hi here is my code:

my_function <- function(df, group_var, summary_var) { 
df %>% 
group_by(!!sym(group_var)) %>% 
summarize(total = sum(!!sym(summary_var))) %>%
ungroup()

}

data_loop <- purrr::map(.f = my_function, df = my_data, group_var = var_list[3:4], summary_var = var_list[3:4])

error: argument .x is missing, with no default

anyone can assist me please when I try to run the loop thank you!

#2

You are missing the .x argument. You want to map over something (such as the list of column names). Perhaps provide an example dataset to make it clearer.

1 Like
#3

I want to loop over the list of column names. hence, why I have var_list[3:4].. but I want to use that for both arguments. it only works if I set group_var or summary_var

#4 
data_loop <- purrr::map(.f = my_function, df = my_data, group_var = "color", .x = var_list[3:4])

this works but I want to loop across group_var too

#5

How does that work? There is no .x argument.

Again, a reproducible example would be good if you want to make it easier for people to help you.

1 Like
#6 
structure(list(animal = c("rhino", "rhino", "monkey", "cat", 
"cat", "giraffe"), pink = c(TRUE, FALSE, FALSE, FALSE, TRUE, 
FALSE), count = c(44, 11, 223, 1233, 23, 88), happiness_point = c(1, 
3, 2, 3, 2, 3)), row.names = c(NA, -6L), class = c("tbl_df", 
"tbl", "data.frame"))

my_function <- function(df,  count_var, group_var) { 
df %>% 
count(!!sym(count_var)) %>%
group_by(!!sym(group_var)) %>% 
mutate(percent = n/sum(n)) %>%
ungroup()

}
var_list <- c("dog", "blue", "pink", "animal")

data_loop <- purrr::map(.f = my_function, df = my_data, group_var = var_list[3:4], summary_var = var_list[3:4])

here is the data above. sometimes count_var and group_var will be different but in this situation its the same I know. I just want to have them as Different inputs. thank u so much !

#7

What are you trying to do in your function?

# A tibble: 6 x 4
  animal  pink  count happiness_point
  <chr>   <lgl> <dbl>           <dbl>
1 rhino   TRUE     44               1
2 rhino   FALSE    11               3
3 monkey  FALSE   223               2
4 cat     FALSE  1233               3
5 cat     TRUE     23               2
6 giraffe FALSE    88               3

Your my_function() doesn't work with this data. Are you trying to filter then count? None of the examples in var_list are in my_data.

#8

sorry. I am trying to essentially count by a variable I select (pink) and then group by a variable I select (pink) and then calculate percent. I then want to run a loop and run this same thing for "animal". I count by "animal" and then group by "animal". and then it makes a list with 2 elements

#9 
structure(list(animal = c("rhino", "rhino", "monkey", "cat", 
"cat", "giraffe"), pink = c(TRUE, FALSE, FALSE, FALSE, TRUE, 
FALSE), count = c(44, 11, 223, 1233, 23, 88), happiness_point = c(1, 
3, 2, 3, 2, 3)), row.names = c(NA, -6L), class = c("tbl_df", 
"tbl", "data.frame"))

my_function <- function(df,  count_var, group_var) { 
df %>% 
count(!!sym(count_var)) %>%
group_by(!!sym(group_var)) %>% 
mutate(percent = n/sum(n)) %>%
ungroup()

}
var_list <- c("dog", "blue", "pink", "animal")

data_loop <- purrr::map(.f = my_function, df = my_data, count_var = var_list[3:4], group_var = var_list[3:4])
#10

No idea if this is what you are after, but this works.

my_func <- function(dataset, col_name){
  
  dataset %>% 
    group_by(.data[[col_name]]) %>% 
    summarise(count = n()) %>% 
    mutate(pct = count / sum(count))
}

# for one
my_func(my_data, "pink") 


# for many
variables <- c("animal", "pink")

map(variables %>% 
      set_names(),
    ~my_func(my_data, .x))

# # output -------------
# $animal
# # A tibble: 4 x 3
# animal  count   pct
# <chr>   <int> <dbl>
#   1 cat         2 0.333
# 2 giraffe     1 0.167
# 3 monkey      1 0.167
# 4 rhino       2 0.333
# 
# $pink
# # A tibble: 2 x 3
# pink  count   pct
# <lgl> <int> <dbl>
#   1 FALSE     4 0.667
# 2 TRUE      2 0.333

Otherwise, create a function that works for one, then turn it in to a purrr function.

#11

I want to have two inputs however is the thing here

#12

I want to run a loop with two input variables

my_function <- function(df,  count_var, group_var) { 
df %>% 
count(!!sym(count_var)) %>%
group_by(!!sym(group_var)) %>% 
mutate(percent = n/sum(n)) %>%
ungroup()

}

however

map(variables %>% 
      set_names(),
    ~ my_function(my_data, .x))

does not work when there is 2 input

#13

But your function doesn't work anyway. Make it work first.

You can use map2() for two inputs and pmap() for more than two.

#14

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