I read in this stack overflow question a clever way to simulate setting an aesthetic to panel background using geom_rect.
Conditionally change panel background with facet_grid?
Unfortunately, it doesn't work if you want to put other colors in the plot. The colors mix and the legend gets polluted. Instead, I would prefer that the color only applies to the background and doesn't get mixed. My other question is: is there an approach that would work in polar coordinates?
For a reproducible example, see the code below:
pies <- data_frame(pie = c(rep("hawaiian", 3), rep("pepperoni", 2)),
fraction = c(c(0.3, 0.2, 0.5), c(0.4, 0.6)),
ingredient = c("cheese", "pineapple", "ham",
"peperroni", "cheese"),
deepdish = c(rep(TRUE, 3), rep(FALSE, 2)))
p <- pies %>%
ggplot() +
geom_bar(aes(x = factor(1),
y = fraction,
fill = ingredient),
width = 0.6,
stat = "identity",
position = "fill") +
facet_wrap(~ pie) +
geom_rect(mapping = aes(fill = deepdish),
alpha = 0.1,
xmin = -Inf, xmax = Inf,
ymin=-Inf, ymax=Inf,
show.legend = FALSE)
p
p + coord_polar(theta = "y")
pies <- data_frame(pie = c(rep("hawaiian", 3), rep("pepperoni", 2)),
fraction = c(c(0.3, 0.2, 0.5), c(0.4, 0.6)),
ingredient = c("cheese", "pineapple", "ham",
"peperroni", "cheese"),
deepdish = c(rep(TRUE, 3), rep(FALSE, 2)))
library(ggplot2)
library(dplyr)
p <- pies %>%
ggplot() +
geom_bar(aes(x = factor(1), y = fraction, fill = ingredient),
width = 0.6, stat = "identity", position = "fill") +
facet_wrap(~ pie) + coord_polar(theta = "y")
g <- ggplotGrob(p)
# Set manually the background color for each panel
g$grobs[[2]]$children[[1]]$children[[1]]$gp$fill <- "#88334466"
g$grobs[[3]]$children[[1]]$children[[1]]$gp$fill <- "#44338866"
library(grid)
grid.draw(g)
library(egg)
library(grid)
pies <- data.frame(pie = c(rep("hawaiian", 3), rep("pepperoni", 2)),
fraction = c(c(0.3, 0.2, 0.5), c(0.4, 0.6)),
ingredient = c("cheese", "pineapple", "ham",
"peperroni", "cheese"))
dummy <- data.frame(x = 0, y = 0,
pie = c("hawaiian","pepperoni"),
deepdish = c("green","yellow"), stringsAsFactors = FALSE)
p <- ggplot(pies) +
facet_wrap(~ pie) +
geom_custom(data= dummy, mapping = aes(x = factor(0),
y = y,
data = deepdish),
grob_fun = function(x) rectGrob(gp=gpar(fill=x,col=NA)), inherit.aes = TRUE) +
geom_bar(aes(x = factor(1),
y = fraction,
fill = ingredient),
width = 0.6,
stat = "identity",
position = "fill")
p + coord_polar(theta = "y")
Related
First of all, some data similar to what I am working with.
rawdata <- data.frame(Score = rnorm(1000, seq(1, 0, length.out = 10), sd = 1),
Group = rep(LETTERS[1:3], 10000))
rawdata$Score <- ifelse(rawdata$Group == "A", rawdata$Score+2,rawdata$Score)
rawdata$Score <- ifelse(rawdata$Group == "C", rawdata$Score-2,rawdata$Score)
stdev <- c(10.78,10.51,9.42)
col <- c("#004d8d", "#cc2701", "#e5b400")
Now, the code of my geom_density_ridges with quantile lines, which in this case they will be white.
p <- ggplot(rawdata, aes(x = Score, y = Group)) +
scale_y_discrete() +
geom_rect(inherit.aes = FALSE, mapping = aes(ymin = 0, ymax = Inf, xmin = -0.1 * min(stdev), xmax = 0.1 * max(stdev)),
fill = "grey", alpha = 0.5) +
geom_density_ridges(scale = -0.5, size = 1, alpha=0.5, show.legend = FALSE,
quantile_lines = TRUE, quantiles = c(0.025, 0.975),
vline_color = "white", aes(fill = Group)) +
scale_color_manual(values = col) +
scale_fill_manual(values = col) +
labs(title="Toy Graph", y="Group", x="Value") +
coord_flip(xlim = c(-8, 8), ylim = NULL, expand = TRUE, clip = "on")
p
An we obtain the following plot, which is perfectly adjusted to expectation.
Now I was wondering if there was a way to make only this little white quantile line transparent to the background. I tried first to set the vline_color = "transparent" and leaving the aes(fill = Group) at the end of geom_density_ridges at the logic that options where drew in order but it gets transparent not to the different shades of grey background but to the density fill (so the quantile line disappears), which is not what I am trying to achieve.
Thanks in advance for your ideas!
Colors can be modified with scales::alpha. This can be passed to your color argument.
library(ggridges)
library(ggplot2)
rawdata <- data.frame(Score = rnorm(1000, seq(1, 0, length.out = 10), sd = 1),
Group = rep(LETTERS[1:3], 10000))
rawdata$Score <- ifelse(rawdata$Group == "A", rawdata$Score+2,rawdata$Score)
rawdata$Score <- ifelse(rawdata$Group == "C", rawdata$Score-2,rawdata$Score)
stdev <- c(10.78,10.51,9.42)
col <- c("#004d8d", "#cc2701", "#e5b400")
ggplot(rawdata, aes(x = Score, y = Group)) +
scale_y_discrete() +
geom_rect(inherit.aes = FALSE, mapping = aes(ymin = 0, ymax = Inf, xmin = -0.1 * min(stdev), xmax = 0.1 * max(stdev)),
fill = "grey", alpha = 0.5) +
geom_density_ridges(scale = -0.5, size = 1, alpha=0.5, show.legend = FALSE,
quantile_lines = TRUE, quantiles = c(0.025, 0.975),
### The only change is here
vline_color = alpha("white", .5), aes(fill = Group)) +
scale_color_manual(values = col) +
scale_fill_manual(values = col) +
labs(title="Toy Graph", y="Group", x="Value") +
coord_flip(xlim = c(-8, 8), ylim = NULL, expand = TRUE, clip = "on")
#> Picking joint bandwidth of 0.148
#> Warning: Using the `size` aesthietic with geom_segment was deprecated in ggplot2 3.4.0.
#> ℹ Please use the `linewidth` aesthetic instead.
Created on 2022-11-14 with reprex v2.0.2
No, if you make something transparent you will see what's underneath, which is the density plot.
However, you can replicate the visual effect of "seeing through to the background" by simply setting the line colour to the same as the background.
Your grey rectangle is currently plotted underneath the density plots, therefore the "background" doesn't have a single colour. This can be solved by plotting it on top instead. Instead of a 50% grey with 50% alpha, you can replicate the same effect with a 0% grey (aka black) with a 25% alpha. Move the geom_rect later than the density plots and it will be layered on top.
Finally, your geom_rect is being called once for each row of raw_data, since it inherits the same data as the main plot. You probably don't want that, so specify a (dummy) data source instead.
ggplot(rawdata, aes(x = Score, y = Group)) +
scale_y_discrete() +
geom_density_ridges(scale = -0.5, size = 1, alpha=0.5, show.legend = FALSE,
quantile_lines = TRUE, quantiles = c(0.025, 0.975),
vline_color = "grey90", aes(fill = Group)) +
scale_color_manual(values = col) +
scale_fill_manual(values = col) +
labs(title="Toy Graph", y="Group", x="Value") +
geom_rect(data=data.frame(), inherit.aes = FALSE, mapping = aes(
ymin = 0, ymax = Inf, xmin = -0.1 * min(stdev), xmax = 0.1 * max(stdev)
), fill = "black", alpha = 0.25) +
coord_flip(xlim = c(-8, 8), ylim = NULL, expand = TRUE, clip = "on")
Note: I'm not sure the background colour is really "grey90", I've eyeballed it. You may want to specify it explicitly with theme if you want to be exact.
If you want literal see-through portions of your density curves, you will need to make the gaps yourself:
library(tidyverse)
rawdata %>%
mutate(GroupNum = as.numeric(as.factor(Group))) %>%
group_by(GroupNum, Group) %>%
summarise(yval = first(GroupNum) - density(Score)$y,
xval = density(Score)$x,
q025 = quantile(Score, 0.025),
q975 = quantile(Score, 0.975)) %>%
mutate(Q = ifelse(xval < q025, 'low', ifelse(xval > q975, 'hi', 'mid'))) %>%
ggplot(aes(xval, yval, group = interaction(Group, Q))) +
geom_line(size = 1) +
geom_ribbon(aes(ymax = GroupNum, ymin = yval, fill = Group),
color = NA, alpha = 0.5, outline.type = 'full',
data = . %>% filter(abs(q025 - xval) > 0.03 &
abs(q975 - xval) > 0.03)) +
coord_flip() +
scale_fill_manual(values = col) +
scale_y_continuous(breaks = 1:3, labels = levels(factor(rawdata$Group)),
name = 'Group') +
labs(x = 'Score')
I have code that plots paired points and also graphs half violin and box plots of pretest and posttest scores. I added lines between the paired points, but I am having difficulty with adding an arrow to the lines and changing the color depending on whether the score decreased or increased.
Below is my code and an image of my graph.
f5 <- ggplot(data = d, aes(y = y)) +
#Add geom_() objects
geom_point(data = d %>% filter(x =="1"), aes(x = xj), color = 'dodgerblue', size = 1.5,
alpha = .6) +
geom_point(data = d %>% filter(x =="2"), aes(x = xj), color = 'darkorange', size = 1.5,
alpha = .6) +
geom_line(aes(x = xj, group = id), color = 'lightgray', alpha = .3) +
geom_half_boxplot(
data = d %>% filter(x=="1"), aes(x=x, y = y), position = position_nudge(x = -.25),
side = "r",outlier.shape = NA, center = TRUE, errorbar.draw = FALSE, width = .2,
fill = 'dodgerblue') +
geom_half_boxplot(
data = d %>% filter(x=="2"), aes(x=x, y = y), position = position_nudge(x = .15),
side = "r",outlier.shape = NA, center = TRUE, errorbar.draw = FALSE, width = .2,
fill = 'darkorange') +
geom_half_violin(
data = d %>% filter(x=="1"),aes(x = x, y = y), position = position_nudge(x = -.3),
side = "l", fill = 'dodgerblue') +
geom_half_violin(
data = d %>% filter(x=="2"),aes(x = x, y = y), position = position_nudge(x = .3),
side = "r", fill = "darkorange") +
#Define additional settings
scale_x_continuous(breaks=c(1,2), labels=c("Pre-Test", "Post-Test"), limits=c(0, 3)) +
xlab("Test") + ylab("Score") +
ggtitle("Before and After Scores with box- and violin plots") +
theme_classic()+
coord_cartesian(ylim=c(y_lim_min, y_lim_max))
I am trying to create a plot in R using ggplot that shows the difference between my two bars in a nice way.
I found an example that did part of what I wanted, but I have two major problems:
It is based on comparing groups of bars, but I only have two, so I added one group with both of them.
I would like to draw the arrow in nicer shape. I attached an image.
Code:
transactions <- c(5000000, 1000000)
time <- c("Q1","Q2")
group <- c("A", "A")
data <- data.frame(transactions, time, group)
library(ggplot2)
fun.data <- function(x){
print(x)
return(data.frame(y = max(x) + 1,
label = paste0(round(diff(x), 2), "cm")))
}
ylab <- c(2.5, 5.0, 7.5, 10)
gg <- ggplot(data, aes(x = time, y = transactions, fill = colors_hc[1], label = round(transactions, 0))) +
geom_bar(stat = "identity", show.legend = FALSE) +
geom_text(position = position_dodge(width = 0.9),
vjust = 1.1) +
geom_line(aes(group = group), position = position_nudge(0.1),
arrow = arrow()) +
stat_summary(aes(x = group, y = transactions),
geom = "label",
fun.data = fun.data,
fontface = "bold", fill = "lightgrey",
inherit.aes = FALSE) +
expand_limits(x = c(0, NA), y = c(0, NA)) +
scale_y_continuous(labels = paste0(ylab, "M"),
breaks = 10 ^ 6 * ylab)
gg
The arrows I am aiming for:
Where I am (ignore the ugliness, didn't style it yet):
This works, but you still need to play around a bit with the axes (or rather beautify them)
library(dplyr)
library(ggplot2)
transactions <- c(5000000, 1000000)
time <- c("Q1","Q2")
group <- c("A", "A")
my_data <- data.frame(transactions, time, group)
fun.data <- function(x){
return(data.frame(y = max(x) + 1,
label = as.integer(diff(x))))
}
my_data %>%
ggplot(aes(x = group, y = transactions, fill = time)) +
geom_bar(stat = 'identity', position = 'dodge') +
geom_text(aes(label = as.integer(transactions)),
position = position_dodge(width = 0.9),
vjust = 1.5) +
geom_line(aes(group = group), position = position_nudge(0.1),
arrow = arrow()) +
stat_summary(aes(x = group, y = transactions),
geom = "label",
size = 5,
position = position_nudge(0.05),
fun.data = fun.data,
fontface = "bold", fill = "lightgrey",
inherit.aes = FALSE)
Edit2:
y_limit <- 6000000
my_data %>%
ggplot(aes(x = time, y = transactions)) +
geom_bar(stat = 'identity',
fill = 'steelblue') +
geom_text(aes(label = as.integer(transactions)),
vjust = 2) +
coord_cartesian(ylim = c(0, y_limit)) +
geom_segment(aes(x = 'Q1', y = max(my_data$transactions),
xend = 'Q1', yend = y_limit)) +
geom_segment(aes(x = 'Q2', y = y_limit,
xend = 'Q2', yend = min(my_data$transactions)),
arrow = arrow()) +
geom_segment(aes(x = 'Q1', y = y_limit,
xend = 'Q2', yend = y_limit)) +
geom_label(aes(x = 'Q2',
y = y_limit,
label = as.integer(min(my_data$transactions)- max(my_data$transactions))),
size = 10,
position = position_nudge(-0.5),
fontface = "bold", fill = "lightgrey")
I have the following data structure:
y <- rep(1:10, 2)
group <- rep(c('a', 'b'), each = 10)
dens <- c(c(seq(from = 0, to = 0.8, by = 0.1), 0),
c(seq(from = -0, to = -0.8, by = -0.1), 0))
my_dat <- data.frame(group, dens, y, stringsAsFactors = FALSE )
These are calculated density disributions, in order to make a grouped violin plot, such as in
Split violin plot with ggplot2
# Plot 1:
require(ggplot2)
ggplot(my_dat, aes(x = dens, y = y, fill = group)) +
geom_polygon(color = 'black', show.legend = FALSE)
Now this is simplified, because my data contains hundreds of rows for a smooth outline. (However, there is the central vertical line in my case.) I would now like to remove exactly this vertical central line.
(I guess the problem is removing any specified part of the polygon.)
An idea in my example was to overplot this with a vertical line:
#Plot 2
ggplot(my_dat, aes(x = dens, y = y, fill = group)) +
geom_polygon(color = 'black', show.legend = FALSE) +
geom_segment(x = 0,
xend = 0,
y = min(y) + 0.2,
yend = max(y) - 0.2,
color = '#00BFC4')
But to get the end of the over plotting segment line correct is tricky. (I have purposefully left the line a bit too short for demonstration)
edit
the groups are not distributed in a symmetrical fashion, although my example strongly suggests so.
You can always just plot another polygon on top
x <- with(my_dat, chull(dens, y))
my_dat2 <- my_dat[c(x, x[1L]), ]
ggplot(my_dat, aes(x = dens, y = y, fill = group)) +
geom_polygon(show.legend = FALSE) +
geom_polygon(data = my_dat2, aes(group = 1), size = 1,
fill = 'transparent',
# fill = NA, ## or this
color = 'black')
I think the simpler solution is to first draw all the outlines and then all the filled areas. This should work for any arbitrary polygon shapes.
y <- rep(1:10, 2)
group <- rep(c('a', 'b'), each = 10)
dens <- c(c(seq(from = 0, to = 0.8, by = 0.1), 0),
c(seq(from = -0, to = -0.8, by = -0.1), 0))
my_dat <- data.frame(group, dens, y, stringsAsFactors = FALSE )
require(ggplot2)
ggplot(my_dat, aes(x = dens, y = y)) +
geom_polygon(color = 'black', fill = NA, size = 2) +
geom_polygon(aes(fill = group), color = NA)
I've got a ggplot where I'm mapping factors to both fill and alpha, like this:
set.seed(47)
the_data <- data.frame(value = rpois(6, lambda=20),
cat1 = rep(c("A", "B"), each = 3),
cat2 = rep(c("X", "Y", "Z"), 2))
ggplot(the_data, aes(y = value, x = cat2, alpha = cat1, fill = cat2)) +
geom_bar(stat = "identity", position = "dodge") +
scale_alpha_discrete(range = c(0.5, 1)) +
theme_bw()
The people I'm producing it for don't find the legend for alpha very clear. I think a good alternative would be something like this (which I hacked together in base graphics):
I know I can't generate a legend like that with high-level ggplot commands, but can I do it in grid and put it on top of my plot?
Here is one possible starting point. I create two different plots which have the appropriate legends - a 'bright' and a 'pale'. Extract the legends from the plot objects. Then use grid viewports, one for the plot, and one for each legend, to put the pieces together.
library(grid)
library(gtable)
# create plot with legend with alpha = 1
g1 <- ggplot(the_data, aes(y = value, x = cat2, alpha = cat1, fill = cat2)) +
geom_bar(stat = "identity", position = "dodge") +
scale_alpha_discrete(range = c(0.5, 1)) +
theme_bw() +
guides(fill = guide_legend(title = "A",
title.hjust = 0.4),
alpha = FALSE) +
theme_bw() +
theme(legend.text = element_blank())
g1
# grab legend
legend_g1 <- gtable_filter(ggplot_gtable(ggplot_build(g1)), "guide-box")
# create plot with 'pale' legend
g2 <- ggplot(the_data, aes(y = value, x = cat2, alpha = cat1, fill = cat2)) +
geom_bar(stat = "identity", position = "dodge") +
scale_alpha_discrete(range = c(0.5, 1)) +
guides(fill = guide_legend(override.aes = list(alpha = 0.5),
title = "B",
title.hjust = 0.3),
alpha = FALSE) +
theme_bw()
g2
# grab legend
legend_g2 <- gtable_filter(ggplot_gtable(ggplot_build(g2)), "guide-box")
# arrange plot and legends
# legends to the right
# define plotting regions (viewports)
vp_plot <- viewport(x = 0.4, y = 0.5,
width = 0.8, height = 1)
vp_legend_g1 <- viewport(x = 0.85, y = 0.5,
width = 0.4, height = 0.4)
vp_legend_g2 <- viewport(x = 0.90, y = 0.5,
width = 0.4, height = 0.4)
# clear current device
grid.newpage()
# add objects to the viewports
# plot without legend
print(g1 + theme(legend.position = "none"), vp = vp_plot)
upViewport(0)
pushViewport(vp_legend_g1)
grid.draw(legend_g1)
upViewport(0)
pushViewport(vp_legend_g2)
grid.draw(legend_g2)
# legends on top
vp_plot <- viewport(x = 0.5, y = 0.4,
width = 1, height = 0.85)
vp_legend_g1 <- viewport(x = 0.5, y = 0.9,
width = 0.4, height = 0.4)
vp_legend_g2 <- viewport(x = 0.55, y = 0.9,
width = 0.4, height = 0.4)
grid.newpage()
print(g1 + theme(legend.position = "none"), vp = vp_plot)
upViewport(0)
pushViewport(vp_legend_g1)
grid.draw(legend_g1)
upViewport(0)
pushViewport(vp_legend_g2)
grid.draw(legend_g2)
#Henrik
This might be a little easier,
g1 <- ggplotGrob(p1)
g2 <- ggplotGrob(p2)
leg1 <- gtable_filter(g1, "guide-box")
leg2 <- gtable_filter(g2, "guide-box")
leg <- gtable:::cbind_gtable(leg1[["grobs"]][[1]], leg2[["grobs"]][[1]], "first")
g1$grobs[g1$layout$name == "guide-box"][[1]] <- leg
g1$widths[max(subset(g1$layout, name == "guide-box")[["r"]])] <- list(leg1$width + leg2$width)
grid.newpage()
grid.draw(g1)