library(R6)
pivot_helper <- function (data, rows = NULL, cols = NULL, value = NULL, wt = NULL,
within = NULL, withinfun = NULL, fun = NULL, pivot = NULL, wrap = F)
{
# cols_quo <- rlang::enquo(cols)
# value_quo <- rlang::enquo(value)
# wt_quo <- rlang::enquo(wt)
# within_quo <- rlang::enquo(within)
if (is.null(fun)) {
fun <- sum
}
grouped <- data %>% dplyr::group_by(dplyr::across(c({{cols}}, {{rows}})), .drop = FALSE)
if (is.null(value)) {
summarized <- grouped %>% dplyr::mutate(value = 1) %>%
dplyr::summarise(value = fun(value))
}
else {
if(is.numeric(value)){
summarized <- grouped %>% dplyr::summarise(value = fun(value))}else{
summarized <- grouped %>% dplyr::summarise(value = fun(grouped[value]))
}
}
if (is.null(within)) {
withined <- summarized
}
else {
withined <- summarized %>% dplyr::group_by(dplyr::across(c({
{
within
}
})), .drop = FALSE)
}
arranged <- withined
ungrouped <- arranged %>% dplyr::ungroup()
tidy <- ungrouped
if(is.null(pivot)){pivot <- TRUE}
if (pivot == F | is.null(cols)) {
tidy
}
else {
tidy %>% tidyr::pivot_wider(names_from = {
{
cols
}
})
}
}
Tidypivot <- R6Class("Tidypivot",
public = list(
# objects
data = NULL,
rows = NULL,
cols = NULL,
fun = NULL,
value = NULL,
wt = NULL,
within = NULL,
withinfun = NULL,
pivot = NULL,
wrap = NULL,
out = NULL,
# functions
update = function(data = NULL, rows = NULL, cols = NULL,
fun = NULL, value = NULL, wt = NULL, pivot = NULL){ # a method
# updating
if(!is.null(data)){self$data <- data}
if(!is.null(rows)){self$rows <- rows}
if(!is.null(cols)){self$cols <- cols}
if(!is.null(fun)){self$fun <- fun}
# if(!is.null(wt)){self$wt <- wt}
if(!is.null(value)){self$value <- value}
if(!is.null(pivot)){self$pivot <- pivot}
# displaying
self$out <- pivot_helper(data = self$data,
rows = self$rows,
cols = self$cols,
fun = self$fun,
# wt = self$wt,
value = self$value,
pivot = self$pivot
)
invisible(self) #returns
},
print = function() { # print method; default is to print everything
# str(self)
print(self$out)
}
)
)library(tidytitanic)
library(magrittr)
tidy_titanic %>%
tidypivot::pivot_helper(cols = sex, pivot = F)## # A tibble: 2 × 2
## sex value
## <fct> <dbl>
## 1 Male 1731
## 2 Female 470flat_titanic %>%
tidypivot::pivot_helper(cols = sex, value = freq, fun = sum, pivot = F)## # A tibble: 2 × 2
## sex value
## <fct> <dbl>
## 1 Male 1731
## 2 Female 470my_tp <- Tidypivot$new()
my_tp## NULLmy_tp$update(data = tidy_titanic, cols = "sex")
my_tp$out## # A tibble: 1 × 2
## Male Female
## <dbl> <dbl>
## 1 1731 470my_tp$update(rows = "class")## `summarise()` has grouped output by 'sex'. You can override using the `.groups`
## argument.my_tp$out## # A tibble: 4 × 3
## class Male Female
## <fct> <dbl> <dbl>
## 1 1st 180 145
## 2 2nd 179 106
## 3 3rd 510 196
## 4 Crew 862 23# wrap and pipe
tp_init <- function(data = NULL, rows = NULL, cols = NULL, fun = NULL,
value = NULL, wt = NULL, pivot = NULL
){
my_pivot <- Tidypivot$new()
my_pivot$update(data = data, rows = rows, cols = cols, fun = fun,
value = value, wt = wt, pivot = pivot)
my_pivot
}
tp_advance <- function(pivot_input, data = NULL, rows = NULL, cols = NULL, fun = NULL,
value = NULL, wt = NULL, pivot = NULL){
my_pivot <- pivot_input
my_pivot$update(data = data, rows = rows, cols = cols, fun = fun,
value = value, wt = wt, pivot = pivot)
my_pivot
}tp_init(data = tidy_titanic) ->
pivot0; pivot0## # A tibble: 1 × 1
## value
## <dbl>
## 1 2201pivot0 %>%
tp_advance(cols = "sex") ->
pivot1; pivot1## # A tibble: 1 × 2
## Male Female
## <dbl> <dbl>
## 1 1731 470pivot1 %>%
tp_advance(rows = "class") ->
pivot2; pivot2## # A tibble: 4 × 3
## class Male Female
## <fct> <dbl> <dbl>
## 1 1st 180 145
## 2 2nd 179 106
## 3 3rd 510 196
## 4 Crew 862 23pivot2 %>%
tp_advance(cols = c("sex", "age")) ->
pivot3; pivot3## # A tibble: 4 × 5
## class Male_Child Male_Adult Female_Child Female_Adult
## <fct> <dbl> <dbl> <dbl> <dbl>
## 1 1st 5 175 1 144
## 2 2nd 11 168 13 93
## 3 3rd 48 462 31 165
## 4 Crew 0 862 0 23pivot3 %>%
tp_advance(pivot = F) ->
pivot4; pivot4## # A tibble: 16 × 4
## sex age class value
## <fct> <fct> <fct> <dbl>
## 1 Male Child 1st 5
## 2 Male Child 2nd 11
## 3 Male Child 3rd 48
## 4 Male Child Crew 0
## 5 Male Adult 1st 175
## 6 Male Adult 2nd 168
## 7 Male Adult 3rd 462
## 8 Male Adult Crew 862
## 9 Female Child 1st 1
## 10 Female Child 2nd 13
## 11 Female Child 3rd 31
## 12 Female Child Crew 0
## 13 Female Adult 1st 144
## 14 Female Adult 2nd 93
## 15 Female Adult 3rd 165
## 16 Female Adult Crew 23tp_init(data = flat_titanic)## # A tibble: 1 × 1
## value
## <dbl>
## 1 32tp_init(data = flat_titanic) %>%
tp_advance(cols = "sex") %>%
# tp_advance(value = "freq") %>%
tp_advance(rows = "class") %>%
tp_advance(cols = c("sex", "age")) %>%
tp_advance(pivot = F)## # A tibble: 16 × 4
## sex age class value
## <fct> <fct> <fct> <dbl>
## 1 Male Child 1st 2
## 2 Male Child 2nd 2
## 3 Male Child 3rd 2
## 4 Male Child Crew 2
## 5 Male Adult 1st 2
## 6 Male Adult 2nd 2
## 7 Male Adult 3rd 2
## 8 Male Adult Crew 2
## 9 Female Child 1st 2
## 10 Female Child 2nd 2
## 11 Female Child 3rd 2
## 12 Female Child Crew 2
## 13 Female Adult 1st 2
## 14 Female Adult 2nd 2
## 15 Female Adult 3rd 2
## 16 Female Adult Crew 2Tidypivot2 <- R6Class("Tidypivot2",
public = list(
# objects
data = NULL,
rows = NULL,
cols = NULL,
fun = NULL,
value = NULL,
wt = NULL,
within = NULL,
withinfun = NULL,
pivot = T,
wrap = F,
out = NULL,
# functions
update = function(data = NULL, rows = NULL, cols = NULL,
fun = NULL, value = NULL, wt = NULL){ # a method
# updating
if(!is.null(data)){self$data <- data}
# if(!is.null(rows)){self$rows <- rows}
if(!is.null(cols)){self$cols <- cols}
# if(!is.null(fun)){self$fun <- fun}
# if(!is.null(wt)){self$wt <- wt}
# if(!is.null(value)){self$value <- value}
# displaying
self$out <- tidypivot::pivot_helper(data = self$data,
# rows = self$rows,
cols = self$cols#,
# ,
# fun = self$fun,
# wt = self$wt,
# value = self$value
)
invisible(self) #returns
},
print = function() { # print method; default is to print everything
# str(self)
print(self$out)
}
)
)```