How to Control Label Color Depending on Fill Darkness of Bars

How to control label color depending on fill darkness of bars?

Two ways to solve this issue by playing with geom_bar color or size:

Data$LabelColor <- as.factor(Data$LabelColor)
p <- ggplot(Data, aes(x = Year, y = Frequency, fill = Category, label = Frequency, colour = LabelColor)) +
              geom_bar(stat = "identity", color = "black") +
              geom_text(size = 3, position = position_stack(vjust = 0.5)) +
              scale_fill_manual(values = colorsPerCat) +  
              scale_colour_manual(values = levels(Data$LabelColor)) +
              guides(colour = FALSE)

Data$LabelColor <- as.factor(Data$LabelColor)
p <- ggplot(Data, aes(x = Year, y = Frequency, fill = Category, label = Frequency, colour=LabelColor)) +
              geom_bar(stat = "identity", size = 0) +
              geom_text(size = 3, position = position_stack(vjust = 0.5)) +
              scale_colour_manual(values = levels(Data$LabelColor)) +
              scale_fill_manual(values = colorsPerCat) +  
              guides(colour = FALSE)

How to automatically change label color depending on relative values (maximum/minimum)?

you can set the colors using replace(rep('white', nrow(df)), which.max(df$perc), 'black').

ggplot(df, aes(x = "", y = perc, fill = review_star)) +
  geom_col(color = "black") +
  geom_label(aes(label = labels), 
             color = replace(rep('white', nrow(df)), which.max(df$perc), 'black'),
             position = position_stack(vjust = 0.5),
             show.legend = FALSE) +
  guides(fill = guide_legend(title = "Answer")) +
  scale_fill_viridis_d() +
  coord_polar(theta = "y") + 
  theme_void()

Change font color of one stacked bar

OP, try to provide a full representative example in the future. Regardless, here's your plot pretty much replicated:

library(ggplot2)

df <- data.frame(
  value=c(12, 17, 14, 46, 41, 66, 14, 14, 14, 27, 28, 7),
  category=rep(LETTERS[1:4], each=3),
  gender=rep(c("Male", "Female", "Other"), 4)
)

ggplot(df, aes(x=gender, y=value)) +
  geom_col(aes(fill=category), position=position_stack(vjust=0.5, reverse = TRUE)) +
  geom_text(
    aes(label=paste(value,"%")), size=5,
    position=position_stack(vjust=0.5)) +
  scale_fill_viridis_d()

To apply the different color based on a criteria, you can just specify that criteria directly to the color= aesthetic in geom_text(). Here, I'm just going to use an ifelse() function to define when to change the color. This works, but doing it this way means that we're calculating on the fly, rather than mapping the result to our original data. Since the color is selected in a way that is not tied to a column in our data, you need to define this color outside of the aes() function. As such, the geom_text() function is modified accordingly:

geom_text(
    aes(label=paste(value,"%")), size=5,
    color=ifelse(df$category=="A", 'white', 'black'),
    position=position_stack(vjust=0.5))

Once again note - I define color= outside of aes(). The other way to do this would be to map the color of text to category, then define the colors manually with scale_color_manual(). It's actually more straightforward here to just use ifelse() outside aes(). (plus, position_stack() is very wonky when working with text geoms...).

How to map geom_text color to a variable

To be explicit about the colours, pass them as a named vector.

A couple of other points here:

1. A geom_bar with stat = "identity" is just a long way of writing geom_col
2. You don't need to hand code y positions for text. Just use position_stack(vjust = 0.5) inside geom_text to have central bar labels
3. If your layers all use the same data and x, y variables, pass them via the initial ggplot call and let the layers inherit them

mechanism.colors <- c(hot = "red", dry = "blue", urban = "tan4")
text.colors <- c(hot = "black", dry = "white", urban = "gray50")

ggplot(data = m.data, aes(x = m.model, y = bar.height)) +
   geom_col(aes( fill = factor(mechanism, levels = mechanism.order))) +
   geom_text(aes(label = bar.height, color = mechanism),
             position = position_stack(vjust = 0.5), size = 8) +
   scale_fill_manual(values = mechanism.colors) +
   scale_color_manual(values = text.colors) +
   labs(fill = "mechanism") +
   guides(color = guide_none())

Conditionally color bars in ggplot

Here is a solution that generates the desired plot. The main trick is to code the "local manager" column into the desired categories: "yes", "no", "mixed" using summarise. In this example df is your dataframe, except I shortened the name of "sum by bins" column to simply "sum".

library(dplyr)
library(ggplot2)

df |>
  # Group by bins
  group_by(bins) |>
  # Summarise to get yes, no, mixed classes
  summarise(n = length(unique(localmanager)),
            class = ifelse(n == 1, unique(localmanager), "mixed"),
            y = unique(sum)) |>
  # ggplot
  ggplot(aes(x = bins, 
             y = y,
             fill = class)) +
  # columns plot
  geom_col() +
  # Change fill colors according to class values
  scale_fill_manual(values = c("mixed" = "orange",
                               "no" = "firebrick3",
                               "yes" = "forestgreen"))

Contrast between label and background: determine if color is light or dark

Here's a strategy to implement picking a text color of black vs white based on the intensity scale in the (second) link provided by @MrFlick.

The blog cited a W3C publication: a standard formula for calculating the perceived brightness of a color that used an algorithm for RGB encoded colors:

 ((Red value X 299) + (Green value X 587) + (Blue value X 114)) / 1000

The col2rgb function delivers a 3-row matrix which I multiply by the factors offered in that webpage. I used an example of "red" as a background color and the chosen text would then be "white"

 c( "black", "white")[  1+(sum( col2rgb("red") *c(299, 587,114))/1000 < 123) ]
[1] "white"

Implemented as a function:

isDark <- function(colr) { (sum( col2rgb(colr) * c(299, 587,114))/1000 < 123) }
isDark("red")
[1] TRUE

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