Is there a way to match the colors of a column in a ggplot bar chart to a different ggplot bar chart-CodePudding

Let's say I have a dataset that I am going to analyze using an RShiny App.

The columns are: State, City, GDP, Year.

The first plot is:

ggplot(aes(x = Year, y = GDP, fill = State))   
geom_col()

Then the second plot has a Select Input which will be the State.

The second plot code is:

ggplot(aes(x = Year, y = GDP, fill = City))   
geom_col()

So basically, if the state of Illinois is green in the first plot, I would like the cities of Illinois to be shades of green on the second plot. Is there a way I can do this?

Thank you.

CodePudding user response：

Sure could that be achieved. You simply have to create a state color palettes which assign a color to each state and a city color palette which assigns to each city a shade of the state color. The hard work is to create these color palettes for which I make use of dplyr and colorspace::lighten to create the shades.

Using some fake example data:

library(ggplot2)
library(dplyr, warn = FALSE)
library(tibble)
library(colorspace)

# Make color palettes
pal <- dat |> 
  distinct(State, City) |> 
  mutate(state_fill = ifelse(State == "Illinois", "darkgreen", "steelblue")) |> 
  group_by(State, state_fill) |> 
  summarise(City = City, 
            city_fill = colorspace::lighten(state_fill, seq(0.05, .5, length.out = n())), .groups = "drop")

state_pal <- distinct(pal, State, state_fill) |> deframe()
city_pal <- distinct(pal, City, city_fill) |> deframe()

dat$City <- factor(dat$City, unique(dat$City))

ggplot(dat, aes(x = Year, y = GDP, fill = State))   
  geom_col()  
  scale_fill_manual(values = state_pal)  
  labs(title = "State")

  
ggplot(dat, aes(x = Year, y = GDP, fill = City))   
  geom_col()  
  scale_fill_manual(values = city_pal)  
  labs(title = "City")

DATA

dat <- data.frame(
  Year = 2016:2020,
  State = c(rep("Illinois", 15), rep("Missouri", 10)),
  City = rep(c("Chicago", "Rockford", "Springfield", "Kansas City", "St. Louis"), each = 5),
  GDP = 1:25
)