I would like to be able to extend my boxplots with additional information. Here is a working example for ggplot2:
library(ggplot2)
ToothGrowth$dose <- as.factor(ToothGrowth$dose)
# Basic box plot
p <- ggplot(ToothGrowth, aes(x=dose, y=len)) +
geom_boxplot()
# Rotate the box plot
p + coord_flip()
I would like to add additional information from a separate data frame. For example:
extra <- data.frame(dose=factor(c(0.5,1,2)), label=c("Label1", "Label2", "Label3"), n=c("n=42","n=52","n=35"))
> extra
dose label n
1 0.5 Label1 n=42
2 1 Label2 n=52
3 2 Label3 n=35
I would like to create the following figure where the information to each dose (factor) is outside the plot and aligns with each of the dose levels (I made this in powerpoint as an example):
EDIT:
I would like to ask advice for an extension of the initial question.
What about this extension where I use fill to split up dose by the two groups?
ToothGrowth$dose <- as.factor(ToothGrowth$dose)
ToothGrowth$group <- head(rep(1:2, 100), dim(ToothGrowth)[1])
ToothGrowth$group <- factor(ToothGrowth$group)
p <- ggplot(ToothGrowth, aes(x=dose, y=len, fill=group)) +
geom_boxplot()
# Rotate the box plot
p + coord_flip()
extra <- data.frame(
dose=factor(rep(c(0.5,1,2), each=2)),
group=factor(rep(c(1:2), 3)),
label=c("Label1A", "Label1B", "Label2A", "Label2B", "Label3A", "Label3B"),
n=c("n=12","n=30","n=20", "n=32","n=15","n=20")
)
Is it possible to align data from the new data frame (extra, 6 rows) with each of the dose/group combinations?
We can use geom_text with clip = "off" inside coord_flip:
ggplot(ToothGrowth, aes(x=dose, y=len)) +
geom_boxplot() +
geom_text(
y = max(ToothGrowth$len) * 1.1,
data = extra,
aes(x = dose, label = sprintf("%s\n%s", label, n)),
hjust = 0) +
coord_flip(clip = "off") +
theme(plot.margin = unit(c(1, 5, 0.5, 0.5), "lines"))
Explanation: We place text outside of the plot area with geom_text and disable clipping with clip = "off" inside coord_flip. Lastly, we increase the plot margin to accommodate the additional labels. You can adjust the vertical y position in the margin (so the horizontal position in the plot because of the coordinate flip) by changing the factor in y = max(ToothGrowth$len) * 1.1.
In response to your edit, here is a possibility
extra <- data.frame(
dose=factor(rep(c(0.5,1,2), each=2)),
group=factor(rep(c(1:2), 3)),
label=c("Label1A", "Label1B", "Label2A", "Label2B", "Label3A", "Label3B"),
n=c("n=12","n=30","n=20", "n=32","n=15","n=20")
)
library(tidyverse)
ToothGrowth %>%
mutate(
dose = as.factor(dose),
group = as.factor(rep(1:2, nrow(ToothGrowth) / 2))) %>%
ggplot(aes(x = dose, y = len, fill = group)) +
geom_boxplot(position = position_dodge(width = 1)) +
geom_text(
data = extra %>%
mutate(
dose = as.factor(dose),
group = as.factor(group),
ymax = max(ToothGrowth$len) * 1.1),
aes(x = dose, y = ymax, label = sprintf("%s\n%s", label, n)),
position = position_dodge(width = 1),
size = 3,
hjust = 0) +
coord_flip(clip = "off", ylim = c(0, max(ToothGrowth$len))) +
theme(
plot.margin = unit(c(1, 5, 0.5, 0.5), "lines"),
legend.position = "bottom")
A few comments:
We ensure that labels match the dodged bars by using position_dodge(with = 1) inside geom_text and geom_boxplot.
It seems that position_dodge does not like a global y (outside of aes). So we include the y position for the labels in extra and use it inside aes. As a result, we need to explicitly limit the range of the y axis. We can do that inside coord_flip with ylim = c(0, max(ToothGrowth$len)).
Related
I'd like to draw bar plot like this but in dual Y axis
(https://i.stack.imgur.com/ldMx0.jpg)
the first three indexs range from 0 to 1,
so I want the left y-axis (corresponding to NSE, KGE, VE) to range from 0 to 1,
and the right y-axis (corresponding to PBIAS) to range from -15 to 5.
the following is my data and code:
library("ggplot2")
## data
data <- data.frame(
value=c(0.82,0.87,0.65,-3.39,0.75,0.82,0.63,1.14,0.85,0.87,0.67,-7.03),
sd=c(0.003,0.047,0.006,4.8,0.003,0.028,0.006,4.77,0.004,0.057,0.014,4.85),
index=c("NSE","KGE","VE","PBIAS","NSE","KGE","VE","PBIAS","NSE","KGE","VE","PBIAS"),
period=c("all","all","all","all","calibration","calibration","calibration","calibration","validation","validation","validation","validation")
)
## fix index sequence
data$index <- factor(data$index, levels = c('NSE','KGE','VE',"PBIAS"))
data$period <- factor(data$period, levels = c('all','calibration', 'validation'))
## bar plot
ggplot(data, aes(x=index, y=value, fill=period))+
geom_bar(position="dodge", stat="identity")+
geom_errorbar(aes(ymin=value-sd, ymax=value+sd),
position = position_dodge(0.9), width=0.2 ,alpha=0.5, size=1)+
theme_bw()
I try to scale and shift the second y-axis,
but PBIAS bar plot was removed because of out of scale limit as follow:
(https://i.stack.imgur.com/n6Jfm.jpg)
the following is my code with dual y axis:
## bar plot (scale and shift the second y-axis with slope/intercept in 20/-15)
ggplot(data, aes(x=index, y=value, fill=period))+
geom_bar(position="dodge", stat="identity")+
geom_errorbar(aes(ymin=value-sd, ymax=value+sd),
position = position_dodge(0.9), width=0.2 ,alpha=0.5, size=1)+
theme_bw()+
scale_y_continuous(limits = c(0,1), name = "value", sec.axis = sec_axis(~ 20*.- 15, name="value"))
Any advice for move bar_plot or other solution？
Taking a different approach, instead of using a dual axis one option would be to make two separate plots and glue them together using patchwork. IMHO that is much easier than fiddling around with the rescaling the data (that's the step you missed, i.e. if you want to have a secondary axis you also have to rescale the data) and makes it clearer that the indices are measured on a different scale:
library(ggplot2)
library(patchwork)
data$facet <- data$index %in% "PBIAS"
plot_fun <- function(.data) {
ggplot(.data, aes(x = index, y = value, fill = period)) +
geom_bar(position = "dodge", stat = "identity") +
geom_errorbar(aes(ymin = value - sd, ymax = value + sd),
position = position_dodge(0.9), width = 0.2, alpha = 0.5, size = 1
) +
theme_bw()
}
p1 <- subset(data, !facet) |> plot_fun() + scale_y_continuous(limits = c(0, 1))
p2 <- subset(data, facet) |> plot_fun() + scale_y_continuous(limits = c(-15, 15), position = "right")
p1 + p2 +
plot_layout(guides = "collect", width = c(3, 1))
A second but similar option would be to use ggh4x which via ggh4x::facetted_pos_scales allows to set the limits for facet panels individually. One drawback, the panels have the same width. (I failed in making this approach work with facet_grid and space="free")
library(ggplot2)
library(ggh4x)
data$facet <- data$index %in% "PBIAS"
ggplot(data, aes(x = index, y = value, fill = period)) +
geom_bar(position = "dodge", stat = "identity") +
geom_errorbar(aes(ymin = value - sd, ymax = value + sd),
position = position_dodge(0.9), width = 0.2, alpha = 0.5, size = 1
) +
facet_wrap(~facet, scales = "free") +
facetted_pos_scales(
y = list(
facet ~ scale_y_continuous(limits = c(-15, 15), position = "right"),
!facet ~ scale_y_continuous(limits = c(0, 1), position = "left")
)
) +
theme_bw() +
theme(strip.text.x = element_blank())
Title pretty well covers it.
I have two legends, relating to size and colour, and wish to have one,say, on the top and one within the graph.
Is this possible and, if so, how
TIA
It can be done by extracting separate legends from plots, then arranging the legends in the relevant plot. The code here uses functions from the gtable package to do the extraction, then functions from the gridExtra package to do the arranging. The aim is to have a plot that contains a color legend and a size legend. First, extract the colour legend from a plot that contains the colour legend only. Second, extract the size legend from a plot that contains the size legend only. Third, draw a plot that contains no legend. Fourth, arrange the plot and the two legends into one new plot.
# Some data
df <- data.frame(
x = 1:10,
y = 1:10,
colour = factor(sample(1:3, 10, replace = TRUE)),
size = factor(sample(1:3, 10, replace = TRUE)))
library(ggplot2)
library(gridExtra)
library(gtable)
library(grid)
### Step 1
# Draw a plot with the colour legend
(p1 <- ggplot(data = df, aes(x=x, y=y)) +
geom_point(aes(colour = colour)) +
theme_bw() +
theme(legend.position = "top"))
# Extract the colour legend - leg1
leg1 <- gtable_filter(ggplot_gtable(ggplot_build(p1)), "guide-box")
### Step 2
# Draw a plot with the size legend
(p2 <- ggplot(data = df, aes(x=x, y=y)) +
geom_point(aes(size = size)) +
theme_bw())
# Extract the size legend - leg2
leg2 <- gtable_filter(ggplot_gtable(ggplot_build(p2)), "guide-box")
# Step 3
# Draw a plot with no legends - plot
(plot <- ggplot(data = df, aes(x=x, y=y)) +
geom_point(aes(size = size, colour = colour)) +
theme_bw() +
theme(legend.position = "none"))
### Step 4
# Arrange the three components (plot, leg1, leg2)
# The two legends are positioned outside the plot:
# one at the top and the other to the side.
plotNew <- arrangeGrob(leg1, plot,
heights = unit.c(leg1$height, unit(1, "npc") - leg1$height), ncol = 1)
plotNew <- arrangeGrob(plotNew, leg2,
widths = unit.c(unit(1, "npc") - leg2$width, leg2$width), nrow = 1)
grid.newpage()
grid.draw(plotNew)
# OR, arrange one legend at the top and the other inside the plot.
plotNew <- plot +
annotation_custom(grob = leg2, xmin = 7, xmax = 10, ymin = 0, ymax = 4)
plotNew <- arrangeGrob(leg1, plotNew,
heights = unit.c(leg1$height, unit(1, "npc") - leg1$height), ncol = 1)
grid.newpage()
grid.draw(plotNew)
Using ggplot2and cowplot (= ggplot2 extension).
The approach is similar to Sandy's one as it takes out the legend as seperate objects and lets you do the placement independently. It was primarly designed for multiple legends which belong to two or more plots in a grid of plots.
The idea is as follows:
Create Plot1, Plot2,...,PlotX without legends
Create Plot1, Plot2,...,PlotX with legends
Extract legends from step 1 & 2 into separate objects
Set up legend grid and arrange legends they way you want to
Create grid combining plots and legends
It seems kinda complicated and time/code consuming but set up once, you can adapt and use it for every kind of plot/legend customization.
library(ggplot2)
library(cowplot)
# Some data
df <- data.frame(
Name = factor(rep(c("A", "B", "C"), 12)),
Month = factor(rep(1:12, each = 3)),
Temp = sample(0:40, 12),
Precip = sample(50:400, 12)
)
# 1. create plot1
plot1 <- ggplot(df, aes(Month, Temp, fill = Name)) +
geom_point(
show.legend = F, aes(group = Name, colour = Name),
size = 3, shape = 17
) +
geom_smooth(
method = "loess", se = F,
aes(group = Name, colour = Name),
show.legend = F, size = 0.5, linetype = "dashed"
)
# 2. create plot2
plot2 <- ggplot(df, aes(Month, Precip, fill = Name)) +
geom_bar(stat = "identity", position = "dodge", show.legend = F) +
geom_smooth(
method = "loess", se = F,
aes(group = Name, colour = Name),
show.legend = F, size = 1, linetype = "dashed"
) +
scale_fill_grey()
# 3.1 create legend1
legend1 <- ggplot(df, aes(Month, Temp)) +
geom_point(
show.legend = T, aes(group = Name, colour = Name),
size = 3, shape = 17
) +
geom_smooth(
method = "loess", se = F, aes(group = Name, colour = Name),
show.legend = T, size = 0.5, linetype = "dashed"
) +
labs(colour = "Station") +
theme(
legend.text = element_text(size = 8),
legend.title = element_text(
face = "italic",
angle = -0, size = 10
)
)
# 3.2 create legend2
legend2 <- ggplot(df, aes(Month, Precip, fill = Name)) +
geom_bar(stat = "identity", position = "dodge", show.legend = T) +
scale_fill_grey() +
guides(
fill =
guide_legend(
title = "",
title.theme = element_text(
face = "italic",
angle = -0, size = 10
)
)
) +
theme(legend.text = element_text(size = 8))
# 3.3 extract "legends only" from ggplot object
legend1 <- get_legend(legend1)
legend2 <- get_legend(legend2)
# 4.1 setup legends grid
legend1_grid <- cowplot::plot_grid(legend1, align = "v", nrow = 2)
# 4.2 add second legend to grid, specifying its location
legends <- legend1_grid +
ggplot2::annotation_custom(
grob = legend2,
xmin = 0.5, xmax = 0.5, ymin = 0.55, ymax = 0.55
)
# 5. plot "plots" + "legends" (with legends in between plots)
cowplot::plot_grid(plot1, legends, plot2,
ncol = 3,
rel_widths = c(0.45, 0.1, 0.45)
)
Created on 2019-10-05 by the reprex package (v0.3.0)
Changing the order of the final plot_grid() call moves the legends to the right:
cowplot::plot_grid(plot1, plot2, legends, ncol = 3,
rel_widths = c(0.45, 0.45, 0.1))
From my understanding, basically there is very limited control over legends in ggplot2. Here is a paragraph from the Hadley's book (page 111):
ggplot2 tries to use the smallest possible number of legends that accurately conveys the aesthetics used in the plot. It does this by combining legends if a variable is used with more than one aesthetic. Figure 6.14 shows an example of this for the points geom: if both colour and shape are mapped to the same variable, then only a single legend is necessary. In order for legends to be merged, they must have the same name (the same legend title). For this reason, if you change the name of one of the merged legends, you’ll need to change it for all of them.
I prepared a MWE and hope for help on how to set ticks and labels at different position on the x-axis for a grouped bar plot.
library(ggplot2)
library(reshape2)
data <- data.frame(name = c("X","Y","Z"), A = c(2,4,6), B = c(1,3,4), C = c(3,4,5))
data <- melt(data, id = 1)
ggplot(data, aes(name,value)) +
geom_bar(aes(fill = variable), position = "dodge", stat = "identity")
The ticks should appear BETWEEN the groups, but the labels centered below the grouped bars (as they are in the figure). I tried to set user-defined breaks (as factors) for scale_x_discrete but it only made my ticks and labels disappear completely.
Any help is much appreciated!
One options would be to convert the discrete x scale to continuous, to facilitate calculation of break positions:
# numeric version of x values
data$x <- as.integer(as.factor(data$name))
1. x ticks between groups of bars
x_tick <- head(unique(data$x), -1) + 0.5
len <- length(x_tick)
ggplot(data, aes(x = x, y = value, fill = variable)) +
geom_col(position = "dodge") +
scale_x_continuous(breaks = c(sort(unique(data$x)), x_tick),
labels = c(sort(unique(data$name)), rep(c(""), len))) +
theme(axis.ticks.x = element_line(color = c(rep(NA, len + 1), rep("black", len))))
2: x ticks before, between, and after groups of bars
x_tick <- c(0, unique(data$x)) + 0.5
len <- length(x_tick)
ggplot(data, aes(x = x, y = value, fill = variable)) +
geom_col(position = "dodge") +
scale_x_continuous(breaks = c(sort(unique(data$x)), x_tick),
labels = c(sort(unique(data$name)), rep(c(""), len))) +
theme(axis.ticks.x = element_line(color = c(rep(NA, len - 1), rep("black", len))))
Don't ask me about the additional grid lines which appeared at 2.25 and 1.75 respectively...
Here is another solution which uses grid package.
library(grid)
nTicks <- 2
tickersPosition <- unit(rep(1:nTicks /(nTicks+1), each=2), "native")
Part 1:nTicks /(nTicks+1) identifies positions where ticks will be placed.
p1 <- ggplot(data, aes(name,value)) +
geom_bar(aes(fill = variable), position = "dodge", stat = "identity")
To change position of ticks we need to create gtable
p2 <- ggplot_gtable(ggplot_build(p1))
and find the right grob (using str):
p2$grobs[[7]]$children$axis$grobs[[1]]$x <- tickersPosition
After the position is rewritten, we can run
grid::grid.draw(p2)
which will show warnings. This is because of a different number of splits.
I want to explore the directlabels package with ggplot. I am trying to plot labels at the endpoint of a simple line chart; however, the labels are clipped by the plot panel. (I intend to plot about 10 financial time series in one plot and I thought directlabels would be the best solution.)
I would imagine there may be another solution using annotate or some other geoms. But I would like to solve the problem using directlabels. Please see code and image below. Thanks.
library(ggplot2)
library(directlabels)
library(tidyr)
#generate data frame with random data, for illustration and plot:
x <- seq(1:100)
y <- cumsum(rnorm(n = 100, mean = 6, sd = 15))
y2 <- cumsum(rnorm(n = 100, mean = 2, sd = 4))
data <- as.data.frame(cbind(x, y, y2))
names(data) <- c("month", "stocks", "bonds")
tidy_data <- gather(data, month)
names(tidy_data) <- c("month", "asset", "value")
p <- ggplot(tidy_data, aes(x = month, y = value, colour = asset)) +
geom_line() +
geom_dl(aes(colour = asset, label = asset), method = "last.points") +
theme_bw()
On data visualization principles, I would like to avoid extending the x-axis to make the labels fit--this would mean having data space with no data. Rather, I would like the labels to extend toward the white space beyond the chart box/panel (if that makes sense).
In my opinion, direct labels is the way to go. Indeed, I would position labels at the beginning and at the end of the lines, creating space for the labels using expand(). Also note that with the labels, there is no need for the legend.
This is similar to answers here and here.
library(ggplot2)
library(directlabels)
library(grid)
library(tidyr)
x <- seq(1:100)
y <- cumsum(rnorm(n = 100, mean = 6, sd = 15))
y2 <- cumsum(rnorm(n = 100, mean = 2, sd = 4))
data <- as.data.frame(cbind(x, y, y2))
names(data) <- c("month", "stocks", "bonds")
tidy_data <- gather(data, month)
names(tidy_data) <- c("month", "asset", "value")
ggplot(tidy_data, aes(x = month, y = value, colour = asset, group = asset)) +
geom_line() +
scale_colour_discrete(guide = 'none') +
scale_x_continuous(expand = c(0.15, 0)) +
geom_dl(aes(label = asset), method = list(dl.trans(x = x + .3), "last.bumpup")) +
geom_dl(aes(label = asset), method = list(dl.trans(x = x - .3), "first.bumpup")) +
theme_bw()
If you prefer to push the labels into the plot margin, direct labels will do that. But because the labels are positioned outside the plot panel, clipping needs to be turned off.
p1 <- ggplot(tidy_data, aes(x = month, y = value, colour = asset, group = asset)) +
geom_line() +
scale_colour_discrete(guide = 'none') +
scale_x_continuous(expand = c(0, 0)) +
geom_dl(aes(label = asset), method = list(dl.trans(x = x + .3), "last.bumpup")) +
theme_bw() +
theme(plot.margin = unit(c(1,4,1,1), "lines"))
# Code to turn off clipping
gt1 <- ggplotGrob(p1)
gt1$layout$clip[gt1$layout$name == "panel"] <- "off"
grid.draw(gt1)
This effect can also be achieved using geom_text (and probably also annotate), that is, without the need for direct labels.
p2 = ggplot(tidy_data, aes(x = month, y = value, group = asset, colour = asset)) +
geom_line() +
geom_text(data = subset(tidy_data, month == 100),
aes(label = asset, colour = asset, x = Inf, y = value), hjust = -.2) +
scale_x_continuous(expand = c(0, 0)) +
scale_colour_discrete(guide = 'none') +
theme_bw() +
theme(plot.margin = unit(c(1,3,1,1), "lines"))
# Code to turn off clipping
gt2 <- ggplotGrob(p2)
gt2$layout$clip[gt2$layout$name == "panel"] <- "off"
grid.draw(gt2)
Since you didn't provide a reproducible example, it's hard to say what the best solution is. However, I would suggest trying to manually adjust the x-scale. Use a "buffer" increase the plot area.
#generate data frame with random data, for illustration and plot:
p <- ggplot(tidy_data, aes(x = month, y = value, colour = asset)) +
geom_line() +
geom_dl(aes(colour = asset, label = asset), method = "last.points") +
theme_bw() +
xlim(minimum_value, maximum_value + buffer)
Using scale_x_discrete() or scale_x_continuous() would likely also work well here if you want to use the direct labels package. Alternatively, annotate or a simple geom_text would also work well.
Title pretty well covers it.
I have two legends, relating to size and colour, and wish to have one,say, on the top and one within the graph.
Is this possible and, if so, how
TIA
It can be done by extracting separate legends from plots, then arranging the legends in the relevant plot. The code here uses functions from the gtable package to do the extraction, then functions from the gridExtra package to do the arranging. The aim is to have a plot that contains a color legend and a size legend. First, extract the colour legend from a plot that contains the colour legend only. Second, extract the size legend from a plot that contains the size legend only. Third, draw a plot that contains no legend. Fourth, arrange the plot and the two legends into one new plot.
# Some data
df <- data.frame(
x = 1:10,
y = 1:10,
colour = factor(sample(1:3, 10, replace = TRUE)),
size = factor(sample(1:3, 10, replace = TRUE)))
library(ggplot2)
library(gridExtra)
library(gtable)
library(grid)
### Step 1
# Draw a plot with the colour legend
(p1 <- ggplot(data = df, aes(x=x, y=y)) +
geom_point(aes(colour = colour)) +
theme_bw() +
theme(legend.position = "top"))
# Extract the colour legend - leg1
leg1 <- gtable_filter(ggplot_gtable(ggplot_build(p1)), "guide-box")
### Step 2
# Draw a plot with the size legend
(p2 <- ggplot(data = df, aes(x=x, y=y)) +
geom_point(aes(size = size)) +
theme_bw())
# Extract the size legend - leg2
leg2 <- gtable_filter(ggplot_gtable(ggplot_build(p2)), "guide-box")
# Step 3
# Draw a plot with no legends - plot
(plot <- ggplot(data = df, aes(x=x, y=y)) +
geom_point(aes(size = size, colour = colour)) +
theme_bw() +
theme(legend.position = "none"))
### Step 4
# Arrange the three components (plot, leg1, leg2)
# The two legends are positioned outside the plot:
# one at the top and the other to the side.
plotNew <- arrangeGrob(leg1, plot,
heights = unit.c(leg1$height, unit(1, "npc") - leg1$height), ncol = 1)
plotNew <- arrangeGrob(plotNew, leg2,
widths = unit.c(unit(1, "npc") - leg2$width, leg2$width), nrow = 1)
grid.newpage()
grid.draw(plotNew)
# OR, arrange one legend at the top and the other inside the plot.
plotNew <- plot +
annotation_custom(grob = leg2, xmin = 7, xmax = 10, ymin = 0, ymax = 4)
plotNew <- arrangeGrob(leg1, plotNew,
heights = unit.c(leg1$height, unit(1, "npc") - leg1$height), ncol = 1)
grid.newpage()
grid.draw(plotNew)
Using ggplot2and cowplot (= ggplot2 extension).
The approach is similar to Sandy's one as it takes out the legend as seperate objects and lets you do the placement independently. It was primarly designed for multiple legends which belong to two or more plots in a grid of plots.
The idea is as follows:
Create Plot1, Plot2,...,PlotX without legends
Create Plot1, Plot2,...,PlotX with legends
Extract legends from step 1 & 2 into separate objects
Set up legend grid and arrange legends they way you want to
Create grid combining plots and legends
It seems kinda complicated and time/code consuming but set up once, you can adapt and use it for every kind of plot/legend customization.
library(ggplot2)
library(cowplot)
# Some data
df <- data.frame(
Name = factor(rep(c("A", "B", "C"), 12)),
Month = factor(rep(1:12, each = 3)),
Temp = sample(0:40, 12),
Precip = sample(50:400, 12)
)
# 1. create plot1
plot1 <- ggplot(df, aes(Month, Temp, fill = Name)) +
geom_point(
show.legend = F, aes(group = Name, colour = Name),
size = 3, shape = 17
) +
geom_smooth(
method = "loess", se = F,
aes(group = Name, colour = Name),
show.legend = F, size = 0.5, linetype = "dashed"
)
# 2. create plot2
plot2 <- ggplot(df, aes(Month, Precip, fill = Name)) +
geom_bar(stat = "identity", position = "dodge", show.legend = F) +
geom_smooth(
method = "loess", se = F,
aes(group = Name, colour = Name),
show.legend = F, size = 1, linetype = "dashed"
) +
scale_fill_grey()
# 3.1 create legend1
legend1 <- ggplot(df, aes(Month, Temp)) +
geom_point(
show.legend = T, aes(group = Name, colour = Name),
size = 3, shape = 17
) +
geom_smooth(
method = "loess", se = F, aes(group = Name, colour = Name),
show.legend = T, size = 0.5, linetype = "dashed"
) +
labs(colour = "Station") +
theme(
legend.text = element_text(size = 8),
legend.title = element_text(
face = "italic",
angle = -0, size = 10
)
)
# 3.2 create legend2
legend2 <- ggplot(df, aes(Month, Precip, fill = Name)) +
geom_bar(stat = "identity", position = "dodge", show.legend = T) +
scale_fill_grey() +
guides(
fill =
guide_legend(
title = "",
title.theme = element_text(
face = "italic",
angle = -0, size = 10
)
)
) +
theme(legend.text = element_text(size = 8))
# 3.3 extract "legends only" from ggplot object
legend1 <- get_legend(legend1)
legend2 <- get_legend(legend2)
# 4.1 setup legends grid
legend1_grid <- cowplot::plot_grid(legend1, align = "v", nrow = 2)
# 4.2 add second legend to grid, specifying its location
legends <- legend1_grid +
ggplot2::annotation_custom(
grob = legend2,
xmin = 0.5, xmax = 0.5, ymin = 0.55, ymax = 0.55
)
# 5. plot "plots" + "legends" (with legends in between plots)
cowplot::plot_grid(plot1, legends, plot2,
ncol = 3,
rel_widths = c(0.45, 0.1, 0.45)
)
Created on 2019-10-05 by the reprex package (v0.3.0)
Changing the order of the final plot_grid() call moves the legends to the right:
cowplot::plot_grid(plot1, plot2, legends, ncol = 3,
rel_widths = c(0.45, 0.45, 0.1))
From my understanding, basically there is very limited control over legends in ggplot2. Here is a paragraph from the Hadley's book (page 111):
ggplot2 tries to use the smallest possible number of legends that accurately conveys the aesthetics used in the plot. It does this by combining legends if a variable is used with more than one aesthetic. Figure 6.14 shows an example of this for the points geom: if both colour and shape are mapped to the same variable, then only a single legend is necessary. In order for legends to be merged, they must have the same name (the same legend title). For this reason, if you change the name of one of the merged legends, you’ll need to change it for all of them.