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 a set of angles that I want to plot, compare and visualise in a circular scale and then patch them into a comparative figure panel. I understand the plot function does what I want for an individual dataset. However, I have multiple of them and want to compare and visualise them with better aesthetics (like in ggplots). Primarily I want to overlay 2 circles on each other and compare them. Here is a sample of my data
a<-c(289.25, 279.61, 288.09, 208.22, 295.74, 214.48, 192.51, 269.93, 225.89, 215.65)
a
ap<-circular(a, template = "geographics", modulo = "2pi")
plot(ap)
arrows.circular(ap, col = "blue", length = 0.25, angle = 30)
enter image description here
I tried the as.ggplot function from the ggplotify package as suggested here. However, I cannot add arrows or layers to my base plot by using as.ggplot (i.e) It converts the plot(ap)part in my example into a ggplot object but the next part (arrows.circular(ap, col = "blue", length = 0.25, angle = 30) is not working.
Is there a way I can draw these plots in ggplot or is there a way to convert the layers of base plots into ggplots using as.ggplot??
Any suggestions would be helpful. Thanks in advance!
You can recreate the plot using ggplot like this:
library(ggplot2)
ggplot(data.frame(a = a %% (2 * pi))) +
geom_segment(aes(x = a, xend = a, y = 0, yend = 1), color = 'blue',
arrow = arrow()) +
geom_hline(yintercept = 1) +
annotate('text', x = 0:3 * pi/2, y = 0.9, label = c('N', 'E', 'S', 'W'),
size = 5) +
geom_point(aes(x = a, y = 1)) +
scale_x_continuous(limits = c(0, 2 * pi)) +
coord_polar() +
theme_void()
And it's certainly possible to alter its appearance to make it look a bit 'softer' and more professional, though this is of course a matter of taste:
library(ggplot2)
ggplot(data.frame(a = a %% (2 * pi))) +
annotate('rect', xmin = -Inf, xmax = Inf, ymin = 0, ymax = 1,
fill = 'gray97') +
geom_hline(yintercept = 1, color = 'gray60') +
geom_segment(aes(x = a, xend = a, y = 0, yend = 1),
color = 'deepskyblue4', size = 1, alpha = 0.5,
arrow = arrow(angle = 25, length = unit(4, 'mm'))) +
annotate('text', x = 0:3 * pi/2, y = 0.9, label = c('N', 'E', 'S', 'W'),
size = 7, fontface = 2, color = 'gray30') +
geom_point(aes(x = a, y = 1)) +
scale_x_continuous(limits = c(0, 2 * pi)) +
coord_polar() +
theme_void() +
theme(plot.background = element_rect(color = NA, fill = '#ecf1f4'))
I tried lately to annotate a graph with boxes above a ggplot.
Here is what I want:
I found a way using grid, but I find it too complicated, and I am quite sure there is a better way to do it, more ggplot2 friendly. Here is the example and my solution:
the data:
y2 <- 350
mesure_pol <- data.frame(x1 = c(1,4,7),
x2 = c(4,7,10),
politiquecat = c(1:3),
politique = c("Phase 1\n","Phase 2\n","Phase 3\n"),
y = c(y2,y2,y2)
)
mesure_pol$x_median <- (mesure_pol$x1 + mesure_pol$x2)/2
colorpal <- viridis::inferno(n=3,direction = -1)
plot
the main plot
p <- ggplot(data = mesure_pol) +
geom_rect(aes(xmin = x1,
xmax = x2,
ymin = 0,
ymax = 300,
fill = as.factor(politiquecat)),
fill = colorpal,
color = "black",
size = 0.3,
alpha = 0.2)+
theme(plot.margin=unit(c(60, 5.5, 5.5, 5.5), "points"))+
coord_cartesian(clip = 'off')
the annotation part
Here is the part I am not happy with:
for (i in 1:dim(mesure_pol)[1]) {
text <- textGrob(label = mesure_pol[i,"politique"], gp = gpar(fontsize=7,fontface="bold"),hjust = 0.5)
rg <- rectGrob(x = text$x, y = text$y, width = stringWidth(text$label) - unit(3,"mm") ,
height = stringHeight(text$label) ,gp = gpar(fill=colorpal[i],alpha = 0.3))
p <- p + annotation_custom(
grob = rg,
ymin = mesure_pol[i,"y"], # Vertical position of the textGrob
ymax = mesure_pol[i,"y"],
xmin = mesure_pol[i,"x_median"], # Note: The grobs are positioned outside the plot area
xmax = mesure_pol[i,"x_median"]) +
annotation_custom(
grob = text,
ymin = mesure_pol[i,"y"], # Vertical position of the textGrob
ymax = mesure_pol[i,"y"],
xmin = mesure_pol[i,"x_median"], # Note: The grobs are positioned outside the plot area
xmax = mesure_pol[i,"x_median"])
}
Is there a simplier/nicer way to obtain similar result ? I tried with annotate, label but without any luck.
An alternative approach to achieve the desired result would be to make the annotations via a second ggplot which could be glued to the main plot via e.g. patchwork.
For the annotation plot I basically used your code for the main plot, added a geom_text layer, get rid of the axix, etc. via theme_void and set the limits in line with main plot. Main difference is that I restrict the y-axis to a 0 to 1 scale. Besides that I shifted the xmin, xmax, ymin and ymax values to add some space around the rectangels (therefore it is important to set the limits).
library(ggplot2)
library(patchwork)
y2 <- 350
mesure_pol <- data.frame(x1 = c(1,4,7),
x2 = c(4,7,10),
politiquecat = c(1:3),
politique = c("Phase 1\n","Phase 2\n","Phase 3\n"),
y = c(y2,y2,y2)
)
mesure_pol$x_median <- (mesure_pol$x1 + mesure_pol$x2)/2
colorpal <- viridis::inferno(n=3,direction = -1)
p <- ggplot(data = mesure_pol) +
geom_rect(aes(xmin = x1,
xmax = x2,
ymin = 0,
ymax = 300,
fill = as.factor(politiquecat)),
fill = colorpal,
color = "black",
size = 0.3,
alpha = 0.2)
ann <- ggplot(data = mesure_pol) +
geom_rect(aes(xmin = x1 + 1,
xmax = x2 - 1,
ymin = 0.2,
ymax = 0.8,
fill = as.factor(politiquecat)),
fill = colorpal,
color = "black",
size = 0.3,
alpha = 0.2) +
geom_text(aes(x = x_median, y = .5, label = politique), vjust = .8, fontface = "bold", color = "black") +
coord_cartesian(xlim = c(1, 10), ylim = c(0, 1)) +
theme_void()
ann / p +
plot_layout(heights = c(1, 4))
By setting a second x-axis and filling the background of the new axis labels with element_markdown from the ggtext package. You may achieve this:
Here is the code:
library(ggtext)
y2 <- 350
mesure_pol <- data.frame(x1 = c(1,4,7),
x2 = c(4,7,10),
politiquecat = c(1:3),
politique = c("Phase 1\n","Phase 2\n","Phase 3\n"),
y = c(y2,y2,y2)
)
mesure_pol$x_median <- (mesure_pol$x1 + mesure_pol$x2)/2
p <- ggplot(data = mesure_pol) +
geom_rect(aes(xmin = x1,
xmax = x2,
ymin = 0,
ymax = 300,
fill = as.factor(politiquecat)),
fill = c("yellow", "red", "black"),
color = "black",
size = 0.3,
alpha = 0.2) +
scale_x_continuous(sec.axis = dup_axis(name = "",
breaks = c(2.5, 5.5, 8.5),
labels = c("Phase 1", "Phase 2", "Phase 3"))) +
theme(plot.margin=unit(c(60, 5.5, 5.5, 5.5), "points"),
axis.ticks.x.top = element_blank(),
axis.text.x.top = element_markdown(face = "bold",
size = 12,
fill = adjustcolor(c("yellow", "red", "black"),
alpha.f = .2)))+
coord_cartesian(clip = 'off')
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'd like to create a chart displaying the size of the seats to a parliament, such as the one below, in ggplot2. My main problem is, essentially, how do I turn a donut chart to a half-donut chart (half-circle arc)?
Using the picture above as an example, I don't know where to go from here:
df <- data.frame(Party = c("GUE/NGL", "S&D", "Greens/EFA", "ALDE", "EPP", "ECR", "EFD", "NA"),
Number = c(35, 184, 55, 84, 265, 54, 32, 27))
df$Party <- factor(df$Party)
df$Share <- df$Number / sum(df$Number)
df$ymax <- cumsum(df$Share)
df$ymin <- c(0, head(df$ymax, n= -1))
ggplot(df, aes(fill = Party, ymax = ymax, ymin = ymin, xmax = 2, xmin = 1)) + geom_rect() +
coord_polar(theta = "y") + xlim(c(0, 2))
To get labels etc you can use unit circle properties! I wrote a small function trying to recreate the style of the plot in your question :)
library(ggforce)
parlDiag <- function(Parties, shares, cols = NULL, repr=c("absolute", "proportion")) {
repr = match.arg(repr)
stopifnot(length(Parties) == length(shares))
if (repr == "proportion") {
stopifnot(sum(shares) == 1)
}
if (!is.null(cols)) {
names(cols) <- Parties
}
# arc start/end in rads, last one reset bc rounding errors
cc <- cumsum(c(-pi/2, switch(repr, "absolute" = (shares / sum(shares)) * pi, "proportion" = shares * pi)))
cc[length(cc)] <- pi/2
# get angle of arc midpoints
meanAngles <- colMeans(rbind(cc[2:length(cc)], cc[1:length(cc)-1]))
# unit circle
labelX <- sin(meanAngles)
labelY <- cos(meanAngles)
# prevent bounding box < y=0
labelY <- ifelse(labelY < 0.015, 0.015, labelY)
p <- ggplot() + theme_no_axes() + coord_fixed() +
expand_limits(x = c(-1.3, 1.3), y = c(0, 1.3)) +
theme(panel.border = element_blank()) +
theme(legend.position = "none") +
geom_arc_bar(aes(x0 = 0, y0 = 0, r0 = 0.5, r = 1,
start = cc[1:length(shares)],
end = c(cc[2:length(shares)], pi/2), fill = Parties)) +
switch(is.null(cols)+1, scale_fill_manual(values = cols), NULL) +
# for label and line positions, just scale sin & cos to get in and out of arc
geom_path(aes(x = c(0.9 * labelX, 1.15 * labelX), y = c(0.9 * labelY, 1.15 * labelY),
group = rep(1:length(shares), 2)), colour = "white", size = 2) +
geom_path(aes(x = c(0.9 * labelX, 1.15 * labelX), y = c(0.9 * labelY, 1.15 * labelY),
group = rep(1:length(shares), 2)), size = 1) +
geom_label(aes(x = 1.15 * labelX, y = 1.15 * labelY,
label = switch(repr,
"absolute" = sprintf("%s\n%i", Parties, shares),
"proportion" = sprintf("%s\n%i%%", Parties, round(shares*100)))), fontface = "bold",
label.padding = unit(1, "points")) +
geom_point(aes(x = 0.9 * labelX, y = 0.9 * labelY), colour = "white", size = 2) +
geom_point(aes(x = 0.9 * labelX, y = 0.9 * labelY)) +
geom_text(aes(x = 0, y = 0, label = switch(repr,
"absolute" = (sprintf("Total: %i MPs", sum(shares))),
"proportion" = "")),
fontface = "bold", size = 7)
return(p)
}
bt <- data.frame(parties = c("CDU", "CSU", "SPD", "AfD", "FDP", "Linke", "Grüne", "Fraktionslos"),
seats = c(200, 46, 153, 92, 80, 69, 67, 2),
cols = c("black", "blue", "red", "lightblue", "yellow", "purple", "green", "grey"),
stringsAsFactors = FALSE)
parlDiag(bt$parties, bt$seats, cols = bt$cols)
Would this work for you?
ggplot(df, aes(fill = Party, ymax = ymax, ymin = ymin, xmax = 2, xmin = 1)) + geom_rect() +
coord_polar(theta = "y",start=-pi/2) + xlim(c(0, 2)) + ylim(c(0,2))
Basically you just set the ylim to be 2x your max so it only plots it on half. In this case we set the y limits to be from 0 to 2. Then you can offset the start in coord_polar(start=) to get it in proper place.
FWIW, one might also check out the nice ggforce package:
library(tidyverse)
library(ggforce)
library(scales)
df %>%
mutate_at(vars(starts_with("y")), rescale, to=pi*c(-.5,.5), from=0:1) %>%
ggplot +
geom_arc_bar(aes(x0 = 0, y0 = 0, r0 = .5, r = 1, start = ymin, end = ymax, fill=Party)) +
coord_fixed()