Reference one color column based on another

Question

I have a dataset with several columns, but a specific column is reference for the colors of the chart, as I can reference this column in scale_fill_manua ggplot automatically?

Obs. The same color can be used in more than one reference.

In the case manual would only create c("BIF"="#543005", "BRE"="#bf812d", ...), but since it’s a lot of data there would be a way to automate this?

My dataset:

> dput(dataset)
structure(list(INI = c(0, 0, 0, 0, 0.9, 15.85, 20.95, 23.05, 
27.3, 32.2, 41.5, 41.75, 45.7, 50, 72.6, 74.3, 82.65, 104.45, 
105.2, 106.15, 107.05, 121.8, 123.2, 124.7, 126.7, 128.4, 136.4, 
139.7, 151.95, 154.35, 168.2, 172.2, 174.75, 177.35, 178.3, 179.85, 
235.2, 237.1, 246.45, 249, 254.75, 255.65, 256.55, 258.1, 258.55, 
259.85, 261.6, 261.85, 261.85, 268.7, 270.4, 273.45, 275.5, 277.6, 
294.9, 295.4, 308.9, 310.3, 312.3, 321.95, 327.85, 328.9, 330.3, 
332.15, 361.65, 368.15, 372.7, 380.7, 385.4, 386, 387.7, 389.2, 
392.2, 394.55, 395.7, 396.85, 398, 400, 400.6, 402, 402.9, 405.7, 
410.95, 414.7, 435.35, 436.35, 442.85, 443.5, 457.45, 457.75, 
465.35, 468.4, 474.5, 475.6, 478.65, 480.1, 483.7, 485.6, 498.8, 
501.05, 514.2, 522), FIM = c(0.9, 15.85, 27.3, 41.5, 20.95, 72.6, 
23.05, 41.75, 32.2, 82.65, 45.7, 50, 151.95, 104.45, 74.3, 105.2, 
121.8, 107.05, 106.15, 168.2, 123.2, 295.4, 124.7, 126.7, 128.4, 
136.4, 139.7, 246.45, 154.35, 254.75, 172.2, 174.75, 177.35, 
178.3, 179.85, 235.2, 237.1, 258.55, 249, 255.65, 258.1, 256.55, 
261.85, 261.6, 259.85, 261.85, 294.9, 268.7, 270.4, 327.85, 273.45, 
275.5, 277.6, 328.9, 310.3, 308.9, 312.3, 386, 321.95, 330.3, 
332.15, 361.65, 385.4, 368.15, 400, 372.7, 380.7, 389.2, 387.7, 
405.7, 395.7, 392.2, 394.55, 396.85, 398, 400.6, 402.9, 414.7, 
402, 410.95, 436.35, 457.45, 422.45, 435.35, 442.85, 443.5, 457.75, 
454.75, 465.35, 468.4, 514.2, 474.5, 475.6, 478.65, 480.1, 483.7, 
485.6, 498.8, 501.05, 522, 537.4, 526.7), UNIDADES = structure(c(2L, 
4L, 3L, 1L, 2L, 4L, 2L, 2L, 3L, 3L, 1L, 2L, 1L, 2L, 4L, 4L, 3L, 
2L, 4L, 4L, 2L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 4L, 4L, 4L, 
4L, 4L, 4L, 4L, 4L, 2L, 2L, 1L, 2L, 2L, 1L, 4L, 4L, 1L, 4L, 2L, 
4L, 2L, 2L, 2L, 2L, 1L, 3L, 3L, 1L, 3L, 3L, 4L, 2L, 3L, 4L, 2L, 
4L, 4L, 4L, 3L, 1L, 3L, 4L, 4L, 4L, 3L, 4L, 3L, 2L, 4L, 4L, 3L, 
1L, 4L, 2L, 2L, 3L, 2L, 3L, 1L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 1L, 2L), .Label = c("UND-0001", "UND-0012", "UND-0042", 
"UND-0075"), class = "factor"), REF = structure(c(8L, 5L, 5L, 
4L, 3L, 3L, 4L, 3L, 9L, 5L, 5L, 6L, 4L, 3L, 4L, 4L, 1L, 3L, 4L, 
4L, 3L, 5L, 5L, 3L, 4L, 4L, 4L, 3L, 5L, 4L, 4L, 3L, 4L, 4L, 4L, 
4L, 5L, 3L, 5L, 3L, 5L, 5L, 3L, 5L, 5L, 3L, 4L, 5L, 5L, 3L, 5L, 
4L, 5L, 4L, 5L, 5L, 5L, 4L, 7L, 5L, 5L, 5L, 5L, 4L, 4L, 5L, 3L, 
5L, 5L, 4L, 5L, 3L, 5L, 5L, 5L, 7L, 5L, 5L, 5L, 5L, 5L, 5L, 7L, 
4L, 5L, 5L, 4L, 2L, 1L, 5L, 4L, 5L, 3L, 5L, 4L, 5L, 3L, 5L, 3L, 
5L, 1L, 3L), .Label = c("BRE", "GAB", "GRA", "GRN", "HID", "RIO", 
"RIU", "SOL", "UNK"), class = "factor"), COLOR = c(26265L, 0L, 
0L, 4737279L, 215L, 215L, 4737279L, 215L, 0L, 0L, 0L, 5014527L, 
4737279L, 215L, 4737279L, 4737279L, 5014527L, 215L, 4737279L, 
4737279L, 215L, 0L, 0L, 215L, 4737279L, 4737279L, 4737279L, 215L, 
0L, 4737279L, 4737279L, 215L, 4737279L, 4737279L, 4737279L, 4737279L, 
0L, 215L, 0L, 215L, 0L, 0L, 215L, 0L, 0L, 215L, 4737279L, 0L, 
0L, 215L, 0L, 4737279L, 0L, 4737279L, 0L, 0L, 0L, 4737279L, 7602234L, 
0L, 0L, 0L, 0L, 4737279L, 4737279L, 0L, 215L, 0L, 0L, 4737279L, 
0L, 215L, 0L, 0L, 0L, 7602234L, 0L, 0L, 0L, 0L, 0L, 0L, 7602234L, 
4737279L, 0L, 0L, 4737279L, 8454016L, 5014527L, 0L, 4737279L, 
0L, 215L, 0L, 4737279L, 0L, 215L, 0L, 215L, 0L, 5014527L, 215L
)), class = "data.frame", row.names = c(NA, -102L))
> 

Entree:

library("ggplot2")
library("broman")

dataset$COLOR = paste0("#",convert2hex(dataset$COLOR))
color = unique(dataset$COLOR)
aux = unique(dataset$REF)

ggplot(dataset, aes(UNIDADES, (INI + FIM)/2*-1, fill= REF)) +
  geom_tile(aes(height = (INI - FIM)*-1, width = 0.6), colour="black", size=0.1) +
  theme_classic() +
  labs(x = "UNIDADES", y = "TOTAL") +
  labs(fill = "REF")  +
  scale_fill_manual (values =dataset$COLOR)

Exit:

> color = unique(dataset$COLOR)
> aux = unique(dataset$REF)
> color
[1] "#006699" "#000000" "#4848ff" "#0000d7" "#4c83ff" "#74003a" "#80ff80"
> aux
[1] SOL HID GRN GRA UNK RIO BRE RIU GAB
Levels: BRE GAB GRA GRN HID RIO RIU SOL UNK

Answer 1

As pointed out by @Rui-Arradas in the comments, you can use setNames to associate the color names with the hexa code, you only need to do this as a list and ensure that the names are associated with the correct codes.

I also understood by the title you want to order the bars in the order of REF. For this you can use reorder.

As you have not provided your complete data set, I am creating some simpler data.

# Dados
dataset <- structure(list(REF = structure(c(3L, 5L, 3L, 1L, 3L, 3L, 3L,
4L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 2L), .Label = c("BRE", "GAB",
"HID", "RIU", "UNK"), class = "factor"), COLOR = structure(c(3L,
2L, 3L, 4L, 3L, 3L, 3L, 1L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 5L
), .Label = c("#01665e", "#4d4d4d", "#80cdc1", "#bf812d", "#f6e8c3"
), class = "factor")), class = "data.frame", row.names = c(NA,
-17L))
set.seed(99)
dataset$UNIDADES <- LETTERS[1:nrow(dataset)]
dataset$var <- sample(1:100, nrow(dataset))
dataset$peso <- sample(1:100, nrow(dataset))
#------------------------------------------------------------

library(ggplot2)

cores <- setNames(
  as.list(as.character(unique(dataset$COLOR))),
  unique(dataset$REF))

ggplot(dataset, aes(reorder(UNIDADES, as.numeric(REF)), var)) +
  geom_tile(aes(height = peso, fill = REF), width = .6) +
  theme_classic() +
  labs(x = "UNIDADES", y = "TOTAL") +
  scale_fill_manual(values = cores)

Answer 2

Apparently one of the problems is the possibility of having equal colors for different references. The function fun below solves this problem by creating a color array in which the names are unique values of ref and the values of cor correspondent.

fun <- function(ref, cor){
  cor <- as.character(cor)
  x <- unique(ref)
  i <- match(x, ref)
  setNames(cor[i], ref[i])
}

To test the function, a data set is created dataset2 with two new REF, of values BRC and BRD. The colors are those of BRE.

dataset2 <- rbind(dataset, data.frame(REF = c("BRC", "BRD"), COLOR = rep("#bf812d", 2)))
dataset2$REF <- factor(as.character(dataset2$REF))

Now assign colors using the function fun.

cores <- with(dataset2, fun(REF, COLOR))

And the rest of the code is the same as the Reply by @Carlos Eduardo Lagosta, only changes the basis.

The chart will be as follows, note the repeated color.

---

Link code above.

set.seed(99)
dataset2$UNIDADES <- LETTERS[1:nrow(dataset2)]
dataset2$var <- sample(1:100, nrow(dataset2))
dataset2$peso <- sample(1:100, nrow(dataset2))

library(ggplot2)

ggplot(dataset2, aes(reorder(UNIDADES, as.numeric(REF)), var)) +
  geom_tile(aes(height = peso, fill = REF), width = .6) +
  theme_classic() +
  labs(x = "UNIDADES", y = "TOTAL") +
  scale_fill_manual(values = cores)