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My ggplot includes geom_boxplot and geom_line, but it only shows the legend for the boxplot part but does not show the legend for the geom_line part. How can I add it please?
Note: The boxplot and the line were made from two different data sources, but shown in one graph.
I really need help with this please, thank you!
Here is the code:
library(ggnewscale)
bplot6 <- ggplot(seasonalmerge_neale1989) +
geom_boxplot(aes(x = date, y = values, group = date, fill = `Data Source`), width = 2, outlier.shape = NA,
lwd = 0.1) +
xlab("") +
ylab("") +
ylim(0,1.2) +
theme(
axis.text.x = element_text(family="serif", size = 8),
axis.text.y = element_text(family="serif", size = 8),
legend.title = element_text(family="serif", size = 8),
legend.text = element_text(family="serif", size = 8),
plot.title = element_text(family="serif", face="bold", size = 8, hjust = 0.5)) +
ggtitle("(f)")+
new_scale_color() +
geom_line(data=pointframe, aes(x= pointdate, y=pointvar), colour="gold", size=1, method = "lm", se=FALSE)
# +theme_classic()+scale_linetype_manual(values=bplot6, name="Data Source: ", labels=c("Ceres", "Landsat", "FAO"))+ theme(legend.position = "bottom")
bplot6
image of boxplots and line
A color must be specified inside an aesthetic in order for there to be a legend.
Moving colour inside aes() will build a legend automatically. Then we can adjust the labels and colors with scale_color_manual. Reproducing your code using iris data.
library(ggnewscale)
bplot6 <- ggplot(iris) +
geom_boxplot(aes(x = Petal.Length, y = Petal.Width , group = Species, fill = `Species`), width = 2, outlier.shape = NA,lwd = 0.1) +
xlab("") +
ylab("") +
#ylim(0,1.2) + you can use it as per your requirement
theme(
axis.text.x = element_text(family="serif", size = 8),
axis.text.y = element_text(family="serif", size = 8),
legend.title = element_text(family="serif", size = 8),
legend.text = element_text(family="serif", size = 8),
plot.title = element_text(family="serif", face="bold", size = 8, hjust = 0.5)) +
ggtitle("(f)")+
new_scale_color() +
geom_line(data=iris, aes(x= Sepal.Length, y=Sepal.Width, color="Gold"), size=1)+
scale_color_manual(name = "Colour", values = c("Gold" = "gold"))
# +theme_classic()+scale_linetype_manual(values=bplot6, name="Data Source: ", labels=c("Ceres", "Landsat", "FAO"))+ theme(legend.position = "bottom")
bplot6
I have a dataframe (dat) with two columns 1) Month and 2) Value. I would like to highlight that the x-axis is not continuous in my boxplot by interrupting the x-axis with two angled lines on the x-axis that are empty between the angled lines.
Example Data and Boxplot
library(ggplot2)
set.seed(321)
dat <- data.frame(matrix(ncol = 2, nrow = 18))
x <- c("Month", "Value")
colnames(dat) <- x
dat$Month <- rep(c(1,2,3,10,11,12),3)
dat$Value <- rnorm(18,20,2)
ggplot(data = dat, aes(x = factor(Month), y = Value)) +
geom_boxplot() +
labs(x = "Month") +
theme_bw() +
theme(panel.grid = element_blank(),
text = element_text(size = 16),
axis.text.x = element_text(size = 14, color = "black"),
axis.text.y = element_text(size = 14, color = "black"))
The ideal figure would look something like below. How can I make this discontinuous axis in ggplot?
You could make use of the extended axis guides in the ggh4x package. Alas, you won't easily be able to create the "separators" without a hack similar to the one suggested by user Zhiqiang Wang
guide_axis_truncated accepts vectors to define lower and upper trunks. This also works for units, by the way, then you have to pass the vector inside the unit function (e.g., trunc_lower = unit(c(0,.45), "npc") !
library(ggplot2)
library(ggh4x)
set.seed(321)
dat <- data.frame(matrix(ncol = 2, nrow = 18))
x <- c("Month", "Value")
colnames(dat) <- x
dat$Month <- rep(c(1,2,3,10,11,12),3)
dat$Value <- rnorm(18,20,2)
# this is to make it slightly more programmatic
x1end <- 3.45
x2start <- 3.55
p <-
ggplot(data = dat, aes(x = factor(Month), y = Value)) +
geom_boxplot() +
labs(x = "Month") +
theme_classic() +
theme(axis.line = element_line(colour = "black"))
p +
guides(x = guide_axis_truncated(
trunc_lower = c(-Inf, x2start),
trunc_upper = c(x1end, Inf)
))
Created on 2021-11-01 by the reprex package (v2.0.1)
The below is taking user Zhiqiang Wang's hack a step further. You will see I am using simple trigonometry to calculate the segment coordinates. in order to make the angle actually look as it is defined in the function, you would need to set coord_equal.
# a simple function to help make the segments
add_separators <- function(x, y = 0, angle = 45, length = .1){
add_y <- length * sin(angle * pi/180)
add_x <- length * cos(angle * pi/180)
## making the list for your segments
myseg <- list(x = x - add_x, xend = x + add_x,
y = rep(y - add_y, length(x)), yend = rep(y + add_y, length(x)))
## this function returns an annotate layer with your segment coordinates
annotate("segment",
x = myseg$x, xend = myseg$xend,
y = myseg$y, yend = myseg$yend)
}
# you will need to set limits for correct positioning of your separators
# I chose 0.05 because this is the expand factor by default
y_sep <- min(dat$Value) -0.05*(min(dat$Value))
p +
guides(x = guide_axis_truncated(
trunc_lower = c(-Inf, x2start),
trunc_upper = c(x1end, Inf)
)) +
add_separators(x = c(x1end, x2start), y = y_sep, angle = 70) +
# you need to set expand to 0
scale_y_continuous(expand = c(0,0)) +
## to make the angle look like specified, you would need to use coord_equal()
coord_cartesian(clip = "off", ylim = c(y_sep, NA))
I think it is possible to get what you want. It may take some work.
Here is your graph:
library(ggplot2)
set.seed(321)
dat <- data.frame(matrix(ncol = 2, nrow = 18))
x <- c("Month", "Value")
colnames(dat) <- x
dat$Month <- rep(c(1,2,3,10,11,12),3)
dat$Value <- rnorm(18,20,2)
p <- ggplot(data = dat, aes(x = factor(Month), y = Value)) +
geom_boxplot() +
labs(x = "Month") +
theme_bw() +
theme(panel.grid = element_blank(),
text = element_text(size = 16),
axis.text.x = element_text(size = 14, color = "black"),
axis.text.y = element_text(size = 14, color = "black"))
Here is my effort:
p + annotate("segment", x = c(3.3, 3.5), xend = c(3.6, 3.8), y = c(14, 14), yend = c(15, 15))+
coord_cartesian(clip = "off", ylim = c(15, 25))
Get something like this:
If you want to go further, it may take several tries to get it right:
p + annotate("segment", x = c(3.3, 3.5), xend = c(3.6, 3.8), y = c(14, 14), yend = c(15, 15))+
annotate("segment", x = c(0, 3.65), xend = c(3.45, 7), y = c(14.55, 14.55), yend = c(14.55, 14.55)) +
coord_cartesian(clip = "off", ylim = c(15, 25)) +
theme_classic()+
theme(axis.line.x = element_blank())
Just replace axis with two new lines. This is a rough idea, it may take some time to make it perfect.
You could use facet_wrap. If you assign the first 3 months to one group, and the other months to another, then you can produce two plots that are side by side and use a single y axis.
It's not exactly what you want, but it will show the data effectively, and highlights the fact that the x axis is not continuous.
dat$group[dat$Month %in% c("1", "2", "3")] <- 1
dat$group[dat$Month %in% c("10", "11", "12")] <- 2
ggplot(data = dat, aes(x = factor(Month), y = Value)) +
geom_boxplot() +
labs(x = "Month") +
theme_bw() +
theme(panel.grid = element_blank(),
text = element_text(size = 16),
axis.text.x = element_text(size = 14, color = "black"),
axis.text.y = element_text(size = 14, color = "black")) +
facet_wrap(~group, scales = "free_x")
* Differences in the plot are likely due to using different versions of R where the set.seed gives different result
Following codes generate a grid of plots shown in the figure below:
library(tidyverse)
library(cowplot)
p1 <- cars %>%
ggplot(aes(x = speed, y = dist)) +
geom_point() +
theme_bw()
p2 <- cars %>%
ggplot(aes(x = speed, y = dist)) +
geom_point() +
scale_y_continuous(trans = "log2", breaks = c(2, 4, 8, 16, 32, 64, 128),
limits = c(2, 128)) +
annotation_logticks(sides = "l") +
theme_bw()
p3 <- diamonds %>%
ggplot(aes(x = carat, y = price, colour = clarity)) +
geom_point() +
theme_bw() +
theme(legend.position = c(0.8, 0.4))
p4 <- plot_grid(p1, p1, nrow = 2, labels = c("B", "C"))
p5 <- plot_grid(p3, p4, nrow = 2, align = "hv", axis = "lb", rel_heights = c(0.5, 1),
labels = c("A", ""))
p6 <- plot_grid(p1, p2, nrow = 2, align = "h", rel_heights = c(0.5, 1),
labels = c("D", "E"))
p7 <- plot_grid(p5, p6, ncol = 2, align = "b")
p7
I wish to align the bottom axis of (A) with top axes of (B, C) respectively, and align bottom axis of (C) with the bottom axis of (E). This should stretch the (B,C) grid plot across the height of (E) and width of (A). I have tried several alignment options.
I have found queries similar to this problem which allow to either get the width or the height alignment right but not both!
I will also add that this reproducible example is the closest I can get to my actual plot. Here I have managed to align the width with panel (A) but am unable to align the height of (B,C) with (E).
May I suggest to use patchwork instead? I find that it handles the alignment of panels more elegantly than anything else around.
library(tidyverse)
library(cowplot)
p1 <- cars %>%
ggplot(aes(x = speed, y = dist)) +
geom_point() +
theme_bw()
p2 <- cars %>%
ggplot(aes(x = speed, y = dist)) +
geom_point() +
scale_y_continuous(trans = "log2", breaks = c(2, 4, 8, 16, 32, 64, 128),
limits = c(2, 128)) +
annotation_logticks(sides = "l") +
theme_bw()
p3 <- diamonds %>%
ggplot(aes(x = carat, y = price, colour = clarity)) +
geom_point() +
theme_bw() +
theme(legend.position = c(0.8, 0.4))
library(patchwork)
#>
#> Attaching package: 'patchwork'
#> The following object is masked from 'package:cowplot':
#>
#> align_plots
p3 + p1 + p1 + p1 + p2 +
plot_layout(
design = "
AD
BE
CE
"
) +
plot_annotation(tag_levels = "A")
Created on 2022-01-05 by the reprex package (v2.0.1)
I am wondering if there is a way to add the second description of x-axis in ggplot2 as follows: Here "the second description" refers "Sample A / Sample B / two arrows" colored in red (shown in the figure).
Please click for the figure!
Of course, I can just put the "second description" using PowerPoint as I did, but I just wonder if it is possible to add it using ggplot2.
Here is the code for the background plot.
library(ggplot2)
library(ggridges)
x <- data.frame(v1=rnorm(100, mean = -2, sd = 0.022),
v2=rnorm(100, mean = -1, sd = 0.022),
v3=rnorm(100, mean = 0, sd = 0.022),
v4=rnorm(100, mean = 1, sd = 0.022),
v5=rnorm(100, mean = 2, sd = 0.022),
v6=rnorm(100, mean = 3, sd = 0.022),
v7=rnorm(100, mean = 4, sd = 0.022))
colnames(x) <- c("A",
"B",
"C",
"D",
"E",
"F",
"G")
head(x)
# Manipulate the data
library(reshape2)
data <- melt(x)
head(data)
# Generating plot
colors <- rainbow(7)
ggplot(data, aes(x = value, y = variable)) +
geom_density_ridges(aes(fill = variable), alpha=0.6, bandwidth=0.1) +
scale_fill_manual(values = colors)+
theme(axis.title = element_text(size = 12),
axis.text = element_text(size = 10),
legend.text = element_text(size = 12),
plot.title = element_text(size = 17, face = "bold",
margin = margin(b=10), hjust = 0.5),
panel.spacing = unit(0.1, "lines"),
legend.position="none") +
geom_vline(xintercept = 0, linetype="dotted") +
geom_vline(xintercept = 2, linetype="dotted",
color = "red", size=1.2) +
xlab("") +
ylab("Groups") +
labs(title = 'Density plot of each group')
Thank you in advance!
I'm not 100% sure this is what you mean, but you can add text on the x-axis using the following in labs:
labs(x="← Sample A Sample B →")
I got the arrows from unicode here: http://xahlee.info/comp/unicode_arrows.html
There are bigger arrows in the link if needed.
EDIT:
Here's your code adapted with the new labels in red font:
ggplot(data, aes(x = value, y = variable)) +
geom_density_ridges(aes(fill = variable), alpha=0.6, bandwidth=0.1) +
scale_fill_manual(values = colors)+
theme(axis.title = element_text(size = 12),
axis.text = element_text(size = 10),
legend.text = element_text(size = 12),
plot.title = element_text(size = 17, face = "bold",
margin = margin(b=10), hjust = 0.5),
panel.spacing = unit(0.1, "lines"),
legend.position="none") +
geom_vline(xintercept = 0, linetype="dotted") +
geom_vline(xintercept = 2, linetype="dotted",
color = "red", size=1.2) +
xlab("🢀 Sample A Sample B 🢂") +
theme(axis.title.x = element_text(size=40,colour = "red")) +
ylab("Groups") +
labs(title = 'Density plot of each group')
You can also push the labels further apart by adding extra spaces. Bring them closer together with fewer spaces.
My input data looks like:
COMPANY DOMAIN REVIEW PROGRESS
Company A Service Good +
Company A Response Good +
Company A Delay Very Good
Company A Cost Poor -
Company B Service Poor -
Company B Delay Average
Company B Cost Good +
Company C Service Very Poor +
Company C Cost Average
I produced a heat map in which I add some text (value of the "PROGRESS" variable - i.e. plus or minus sign).
Here is my code:
require("ggplot2")
graph <- read.table("input.tab", header=T, sep="\t")
ggplot(data=graph, aes(x=COMPANY, y=DOMAIN, group=REVIEW, fill=REVIEW)) +
geom_tile() +
geom_text(aes(x=COMPANY, y=DOMAIN, label=PROGRESS)) +
scale_x_discrete(expand = c(0, 0)) +
scale_y_discrete(expand = c(0, 0)) +
geom_vline(xintercept=seq(1.5, length(graph$COMPANY)+0.5)) +
geom_hline(yintercept=seq(1.5, length(graph$DOMAIN)+0.5)) +
theme(
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
axis.line = element_blank(),
axis.ticks = element_blank(),
panel.background = element_blank(),
plot.background = element_blank(),
axis.title=element_blank(),
axis.text.x = element_text(angle=45, size=12, hjust=1)
)
However I am struggling adding (see figure modified manually below):
(1) the following "PROGRESS" legend as part of the color code already listed:
+ Better
- Worse
(2) the count of data available on each row between the right side of the plot and the legend
(3) the count of data available on each column on top of the plot
Any advice?
Here's my proposed solution, I added comments in the code for you to understand what I did. There is probably a better way of generating the grid, though. Hope it helps.
graph <- read_csv(
"COMPANY ,DOMAIN ,REVIEW ,PROGRESS
Company A ,Service ,Good ,+
Company A ,Response ,Good ,+
Company A ,Delay ,Very Good ,
Company A ,Cost ,Poor ,-
Company B ,Service ,Poor ,-
Company B ,Delay ,Average ,
Company B ,Cost ,Good ,+
Company C ,Service ,Very Poor ,+
Company C ,Cost ,Average ,")
ggplot() +
# moved aesthetics and data to each geom,
# if you keep them in the ggplot call,
# you have to specify `inherit.aes = FALSE` in the rest of the geoms
geom_tile(data = graph,
aes(x = COMPANY,
y = DOMAIN,
fill = REVIEW)) +
# changed from `geom_text` to `geom_point` with custom shapes
geom_point(data = graph,
aes(x = COMPANY,
y = DOMAIN,
shape = factor(PROGRESS, labels = c("Worse", "Better"))),
size = 3) +
# custom shape scale
scale_shape_manual(name = "", values = c("-", "+")) +
# calculate marginal totals "on the fly"
# top total
geom_text(data = summarize(group_by(graph, COMPANY),
av_data = length(!is.na(PROGRESS))),
aes(x = COMPANY,
y = length(unique(graph$DOMAIN)) + 0.7,
label = av_data)) +
# right total
geom_text(data = summarize(group_by(graph, DOMAIN),
av_data = length(!is.na(PROGRESS))),
aes(x = length(unique(graph$COMPANY)) + 0.7,
y = DOMAIN, label = av_data)) +
# expand the plotting area to accomodate for the marginal totals
scale_x_discrete(expand = c(0, 0.8)) +
scale_y_discrete(expand = c(0, 0.8)) +
# changed to `geom_segment` to generate the grid, otherwise grid extends
# beyond the heatmap
# horizontal lines
geom_segment(aes(y = rep(0.5, 1 + length(unique(graph$COMPANY))),
yend = rep(length(unique(graph$DOMAIN)) + 0.5,
1 + length(unique(graph$COMPANY))),
x = seq(0.5, 1 + length(unique(graph$COMPANY))),
xend = seq(0.5, 1 + length(unique(graph$COMPANY))))) +
# vertical lines
geom_segment(aes(x = rep(0.5, 1 + length(unique(graph$DOMAIN))),
xend = rep(length(unique(graph$COMPANY)) + 0.5,
1 + length(unique(graph$DOMAIN))),
y = seq(0.5, 1 + length(unique(graph$DOMAIN))),
yend = seq(0.5, 1 + length(unique(graph$DOMAIN))))) +
# custom legend order
guides(fill = guide_legend(order = 1),
shape = guide_legend(order = 2)) +
# theme tweaks
theme(
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
axis.line = element_blank(),
axis.ticks = element_blank(),
panel.background = element_blank(),
plot.background = element_blank(),
axis.title = element_blank(),
axis.text.x = element_text(angle = 45,
size = 12,
hjust = 1,
# move text up 20 pt
margin = margin(-20,0,0,0, "pt")),
# move text right 20 pt
axis.text.y = element_text(margin = margin(0,-20,0,0, "pt"))
)