CODEWITHSUNDEEP
rcolorsggplot2
Ricardo Saporta
Ricardo Saporta

Reputation: 55420

Manually setting group colors for ggplot2

I have a data set from which I have to make several dozen plots. The data consists of 30 Groups and several measurements within each group.

Most plots will not use all the groups at once.

My goal is to have one single color pallete for the set of groups such that any given group is the same color across all graphs. In the example below, this would mean that Group C is the same color in Plot 1 and in Plot 2.

My question is how to go about this.

I've tried several variations of scale_fill_manual (and scal_color_manual, when appropriate). While the colors are chosen from the designated pallete, I cannot seem to index the pallette by the group, or some other way to "skip" over the colors corresponding to a missing group

I also thought to try to add the color information as a column of the data being plotted, but I'm unsure how to then use this column as the color for the group.

Plot Example

library(ggplot2)
library(data.table)

# SAMPLE DATA: 
DT1 <- data.table(Name=c("C_sub1", "A_sub1", "A_sub2"), Value=c(2,5,3), Group=c("C", "A", "A"), key="Group")
DT2 <- data.table(Name=c("A_sub1", "B_sub1", "C_sub1", "C_sub2"), Value=c(4,3,6,3), Group=c("A", "B", "C", "C"), key="Group")

# SAMPLE Color Pallette  
ColorsDT <-  data.table(Group=LETTERS[1:5], Color=c("#333BFF", "#CC6600", "#9633FF", "#E2FF33", "#E3DB71"), key="Group")

# Add a column for Color, according to the Group
DT1[ColorsDT, Color := i.Color]
DT2[ColorsDT, Color := i.Color]

# A Basic Plot
simplePlot <- function(DT, tit) 
  ggplot(DT ,aes(x=Name, y=Value, fill=Group)) +
   geom_bar(stat="identity") + xlab("") + ggtitle(tit)
    # Tried sevearl variations of: 
    #  + scale_fill_manual(values=ColorsDT$Color)


# Plot Them
grid.arrange(ncol=2,  simplePlot(DT1, tit="Plot 1"),  simplePlot(DT2, tit="Plot 2"))

Upvotes: 84

Views: 121653

Answers (2)

Roasty247
Roasty247

Reputation: 731

You can also use scale_fill_brewer() or other variants like scale_colour_brewer() that match your aes(). It doesn't give you such precise control over colour scheme like choosing individual hexcodes, but you can easily choose among numerous pre-set colour schemes with the palette = argument and the colour scheme is consistent on the same gradient between output subplots.

# A Basic Plot
simplePlot <- function(DT, tit) 
  ggplot(DT ,aes(x=Name, y=Value, fill=Group)) +
  geom_bar(stat="identity") + 
  scale_fill_brewer(palette = 1) + # Line added
  xlab("") + ggtitle(tit)
# Tried sevearl variations of: 
#  + scale_fill_manual(values=ColorsDT$Color)


# Plot Them
grid.arrange(ncol=2,  simplePlot(DT1, tit="Plot 1"),  simplePlot(DT2, tit="Plot 2"))

Output plots with consistent colour scheme

Upvotes: 0

alexwhan
alexwhan

Reputation: 16056

You can associate each of your groups with a colour, then pass to the function:

group.colors <- c(A = "#333BFF", B = "#CC6600", C ="#9633FF", D = "#E2FF33", E = "#E3DB71")

simplePlot <- function(DT, tit) 
  ggplot(DT ,aes(x=Name, y=Value, fill=Group)) +
  geom_bar(stat="identity") + xlab("") + ggtitle(tit) +
  #Specify colours
  scale_fill_manual(values=group.colors)

Then using your plots:

grid.arrange(ncol=2,  simplePlot(DT1, tit="Plot 1"), 
  simplePlot(DT2, tit="Plot 2"))

enter image description here

I think the issue with your approach was that the colours weren't named, so scale_fill_manual() can't assoicate them. Compare:

ColorsDT <-  data.table(Group=LETTERS[1:5], Color=c("#333BFF", "#CC6600", "#9633FF", "#E2FF33", "#E3DB71"), key="Group")
ColorsDT
#   Group   Color
#1:     A #333BFF
#2:     B #CC6600
#3:     C #9633FF
#4:     D #E2FF33
#5:     E #E3DB71

with:

ColorsDT.name <-  data.table(A = "#333BFF", B = "#CC6600", C = "#9633FF", D = "#E2FF33", E =  "#E3DB71")
ColorsDT.name
#          A       B       C       D       E
# 1: #333BFF #CC6600 #9633FF #E2FF33 #E3DB71

Upvotes: 103

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