A function that pretty much let's you do anything in the tidypivot space, is carefully crafted, and is adapted to make the other functions easy to use

A function that pretty much let's you do anything in the tidypivot space, is carefully crafted, and is adapted to make the other functions easy to use

pivot_helper(
  data,
  rows = NULL,
  cols = NULL,
  value = NULL,
  wt = NULL,
  within = NULL,
  fun = NULL,
  pivot = T,
  wrap = F
)

Arguments

data	A data frame, data frame extension (e.g. a tibble), or a lazy data frame (e.g. from dbplyr or dtplyr). See Methods, below, for more details.
rows	a character vector of items
cols	a character vector of items
pivot	logical: should wide table be returned - col categories as columns (TRUE), or left long and tidy (FALSE)?

Value

Examples

tidy_titanic %>% pivot_helper(rows = sex, cols = survived, fun = length) # pivot_count
#> # A tibble: 2 × 3
#>   sex       No   Yes
#>   <fct>  <int> <int>
#> 1 Male    1364   367
#> 2 Female   126   344
flat_titanic %>% pivot_helper(rows = sex, value = freq, fun = mean) # pivot_calc
#> # A tibble: 2 × 2
#>   sex    value
#>   <fct>  <dbl>
#> 1 Male   108. 
#> 2 Female  29.4
flat_titanic %>% pivot_helper(rows = sex, value = freq, fun = sum) # pivot_count (weighted sum)
#> # A tibble: 2 × 2
#>   sex    value
#>   <fct>  <dbl>
#> 1 Male    1731
#> 2 Female   470
nar <- function(x) return(NA)
flat_titanic %>% pivot_helper(rows = sex, cols = survived, fun = nar); #pivot_null
#> # A tibble: 2 × 3
#>   sex    No    Yes  
#>   <fct>  <lgl> <lgl>
#> 1 Male   NA    NA   
#> 2 Female NA    NA   
sample1 <- function(x) sample(x, 1)
flat_titanic %>% pivot_helper(rows = sex, cols = survived, fun = sample1, value = freq); #pivot_sample1
#> # A tibble: 2 × 3
#>   sex       No   Yes
#>   <fct>  <dbl> <dbl>
#> 1 Male       0   192
#> 2 Female     3     1
samplen <- function(x, n) paste(sample(x, 5, replace = F), collapse = ", ")
flat_titanic %>% pivot_helper(rows = sex, cols = survived, fun = samplen, value = freq); #pivot_samplen
#> # A tibble: 2 × 3
#>   sex    No                Yes               
#>   <fct>  <chr>             <chr>             
#> 1 Male   0, 0, 670, 387, 0 14, 192, 57, 13, 0
#> 2 Female 0, 13, 0, 3, 89   1, 140, 20, 76, 13
paste_collapse <- function(x) paste (x, collapse = ", ")
flat_titanic %>% pivot_helper(rows = sex, fun = paste_collapse, value = freq) #pivot_list
#> # A tibble: 2 × 2
#>   sex    value                                                         
#>   <fct>  <chr>                                                         
#> 1 Male   0, 0, 35, 0, 118, 154, 387, 670, 5, 11, 13, 0, 57, 14, 75, 192
#> 2 Female 0, 0, 17, 0, 4, 13, 89, 3, 1, 13, 14, 0, 140, 80, 76, 20