How to remove duplicate legend in R ggplot

Question

My map is producing two legends for my DMA boundaries. The one seen at the bottom of my figure is correct, but the at the top (placed above the "Frequency of Mentions") is incorrect and I'd like removed. However, when I remove it, it messes up other features in my map. Apologies for the likely simple fix, my brain is tired!

# Filter out zero counts and apply binning
ok_cities_correct_clean <- ok_cities_correct_clean %>%
  filter(COUNT > 0) %>%
  mutate(
    color_gradient = cut(
      COUNT,  # Cut the COUNT values into the specified ranges
      breaks = c(0, 10, 20, 30, Inf),  # Include 0 as the lower bound for first bin
      labels = c("1 - 10", "11 - 20", "21 - 30", "> 30"),  # Correct number of labels
      right = TRUE  # Ensure the upper bound is included in each bin
    )
  )

# Define color palettes
cities_urban <- c("lightblue", "lightskyblue", "dodgerblue", "darkblue")
names(cities_urban) <- labels


cities_rural <- c("lightpink", "lightcoral", "firebrick", "darkred")
names(cities_rural) <- labels



ggplot() +
  
  # Add OK counties
  geom_sf(
    data = ok_counties_reproj,
    fill = "#f5f5f5",
    color = "black",
    size = 0
  ) +
  
  # Add DMA 
  geom_sf(
    data = ok_DMA,
    aes(fill = DMA, color = DMA),
    linewidth = 1.5,
    alpha = 0.75,
    show.legend = c(fill = TRUE, color = FALSE)
  ) +
  
  # OK counties (border, no fill)
  geom_sf(
    data = ok_counties_reproj,
    fill = NA,
    color = "black",
    size = 1
  ) +
  
  # Set fill colors for DMA
  scale_fill_manual(
    values = c(
      "Tulsa, OK" = "#4575b4",
      "Oklahoma City, OK" = "#5ab4ac"
    ),
    aesthetics = c("fill", "color"),
    guide = guide_legend(override.aes = list(
      color = c("#5ab4ac", "#4575b4")
    ))
  ) +
  
  new_scale_color() +
  
  # Add cities with color_gradient based on urban/rural classification
  geom_sf(
    data = ok_cities_correct_clean %>%
      filter(COUNT > 0, CLASSIF == "Urban"),
    aes(size = COUNT, color = color_gradient)
  ) +
  
  scale_color_manual(
    values = cities_urban, na.value = "gray", name = "Urban"
  ) +
  
  new_scale_color() +
  
  # Add cities with color g radient based on urban/rural classification
  geom_sf(
    data = ok_cities_correct_clean %>%
      filter(COUNT > 0, CLASSIF == "Rural"),
    aes(size = COUNT, color = color_gradient)
  ) +
  
  scale_color_manual(
    values = cities_rural, na.value = "gray", name = "Rural"
  ) +
  
  scale_size_continuous(
    range = c(1, 10),
    name = "Frequency of Mentions"
  )

Figure:

P.S. Please ignore the map clutter -- the final product will utilize a facet_wrap to declutter what you currently see.

Answer 1

As I already mentioned in my answer on your previous question the issue with the duplicated legend seems to be related to the use of ggnewscale. The fix I proposed there works for new_scale_fill. But as you use new_scale_color instead we have to switch fill and color in the fix, i.e. use show.legend = c(fill = FALSE, color = TRUE) and guide_legend(override.aes = list(fill = c("#5ab4ac", "#4575b4")):

Using an adapted version of the minimal reproducible example from your previous question:

library(tidyverse)
library(ggnewscale)

## Make example data
set.seed(123)

nc_counties <- sf::st_read(system.file("shape/nc.shp", package = "sf"), quiet = TRUE)

dma <- sample(nrow(nc_counties), 20)

ok_counties_reproj <- nc_counties

ok_DMA <- nc_counties[dma, ]
ok_DMA$DMA <- c("Tulsa, OK", "Oklahoma City, OK")

ok_cities_correct_clean <- nc_counties
ok_cities_correct_clean <- sf::st_centroid(ok_cities_correct_clean)
ok_cities_correct_clean$CLASSIF <- sample(
  c("Urban", "Rural"),
  nrow(ok_cities_correct_clean),
  replace = TRUE
)
ok_cities_correct_clean$COUNT <- sample(
  seq(0, 40),
  nrow(ok_cities_correct_clean),
  replace = TRUE
)
###

breaks <- c(-Inf, 10, 20, 30, Inf)
labels <- labels <- c("1 - 10", "11 - 20", "21 - 30", "> 30")

## Bin the COUNT variable
ok_cities_correct_clean$color_gradient <- cut(
  ok_cities_correct_clean$COUNT, breaks, labels
)

## Define color palettes
cities_urban <- c("lightblue", "lightskyblue", "dodgerblue", "darkblue")
names(cities_urban) <- labels

cities_rural <- c("lightpink", "lightcoral", "firebrick", "darkred")
names(cities_rural) <- labels

ggplot() +
  # Add OK counties
  geom_sf(
    data = ok_counties_reproj,
    fill = "#f5f5f5",
    color = "black",
    size = 0
  ) +
  # Add DMA
  geom_sf(
    data = ok_DMA,
    aes(fill = DMA, color = DMA),
    linewidth = 1.5,
    alpha = 0.75,
    show.legend = c(fill = FALSE, color = TRUE)
  ) +
  # OK counties (border, no fill)
  geom_sf(
    data = ok_counties_reproj,
    fill = NA,
    color = "black",
    size = 1
  ) +
  # Set fill colors for DMA
  scale_fill_manual(
    values = c(
      "Tulsa, OK" = "#4575b4",
      "Oklahoma City, OK" = "#5ab4ac"
    ),
    aesthetics = c("color", "fill"),
    guide = guide_legend(override.aes = list(
      fill = c("#5ab4ac", "#4575b4")
    ))
  ) +
  new_scale_color() +
  # Add cities with color_gradient based on urban/rural classification
  geom_sf(
    data = ok_cities_correct_clean %>%
      filter(COUNT > 0, CLASSIF == "Urban"),
    aes(size = COUNT, color = color_gradient)
  ) +
  scale_color_manual(
    values = cities_urban, na.value = "gray", name = "Urban"
  ) +
  new_scale_color() +
  # Add cities with color g radient based on urban/rural classification
  geom_sf(
    data = ok_cities_correct_clean %>%
      filter(COUNT > 0, CLASSIF == "Rural"),
    aes(size = COUNT, color = color_gradient)
  ) +
  scale_color_manual(
    values = cities_rural, na.value = "gray", name = "Rural"
  ) +
  scale_size_continuous(
    range = c(1, 10),
    name = "Frequency of Mentions"
  )