I am trying to add labels in line graph but am unable to do so.
I want to add lable such that blue line mentiones 'model_1'; red line mentioned 'model_2' and darkgreen line mentioned 'model_3'
Attaching the code below
p1 <- ggplot(data = Auto, aes(x = horsepower, y = mpg)) +
geom_point() +
geom_line(aes(y = fitted(lm_mpg_1)), color = "blue", size = 1) +
geom_line(aes(y = fitted(lm_mpg_2)), color = "red", size = 1) +
geom_line(aes(y = fitted(lm_mpg_3)), color = "darkgreen", size = 1)
I have tried to use geom_text, geom_label and annotate function however they give me error.
The code I tried was:
p1 + geom_text(label = c('model_1','model_2','model_3'))
You don't have any data. You can use dput to share your data. In the meanwhile I have used mtcars as an example below:
# library
library(ggplot2)
# Keep 30 first rows in the mtcars natively available dataset
data=head(mtcars, 30)
# 1/ add text with geom_text, use nudge to nudge the text
ggplot(data, aes(x=wt, y=mpg)) +
geom_point() + # Show dots
geom_text(
label=rownames(data),
nudge_x = 0.25, nudge_y = 0.25,
check_overlap = T
)
ggplot(data, aes(x=wt, y=mpg)) +
geom_point() + # Show dots
geom_label(
label=rownames(data),
nudge_x = 0.25, nudge_y = 0.25,
check_overlap = T
)
p <- ggplot(mtcars, aes(x = wt, y = mpg)) + geom_point()
p + annotate("text", x = 4, y = 25, label = "Some text")
p <- ggplot(mtcars, aes(x = wt, y = mpg)) + geom_point()
p + annotate("text", x = 5, y = 25, label = "Some looooooooooooooooooooooooooong text")
Also, I must assume that the range of the x and y axis are unknown. Hence, I can't even hardcode the x and y values like example above.
You might be able to get what you want as described here by disabling clipping and changing the margins:
p <- ggplot(mtcars, aes(x = wt, y = mpg)) + geom_point()
p + annotate("text", x = 5, y = 25,
label = "Some looooooooooooooooooooooooooong text") +
coord_cartesian(clip = 'off') +
theme(plot.margin = unit(c(1,5,1,1), "lines"))
With that approach you still have to compute the size of margin needed depending on the text length and position, for example:
lbl_txt <- "Some looooooooooooooooooooooooooong text"
p <- ggplot(mtcars, aes(x = wt, y = mpg)) + geom_point()
p + annotate("text", x = 5, y = 25,
label = lbl_txt) +
coord_cartesian(clip = 'off') +
theme(plot.margin = unit(c(1,(nchar(lbl_txt)-5)*2,1,1), "points"))
p <- ggplot(mtcars, aes(x = wt, y = mpg)) + geom_point()
p + annotate("text", x = 5, hjust = 1, y = 25, label = "Some looooooooooooooooooooooooooong text")
I have found a solution. There is an hjust parameter that you can set to. 1 to Right align it, that will ensure it will not go out of the plot on the right.
Adding to your solution provided above, since the words in your label are separated by spaces, you can also consider using the str_wrap function from the stringr package. This could give you some extra room as the label pushes further to the left side.
library(ggplot2)
library(stringr)
label_example <- c("Some looooooooooooooooooooooooooong text")
p <- ggplot(mtcars, aes(x = wt, y = mpg)) + geom_point()
p + annotate("text", x = 5, hjust = 1, y = 25, label = str_wrap(label_example, 1))
Created on 2020-11-16 by the reprex package (v0.3.0)
question7 %>% ggplot(aes(x = year, y = n , group = state)) +
geom_point(aes(color = state)) + geom_smooth(method = "loess", formula
= y ~ x, level = 1, aes(color=state))+ labs(x = "Year", y = "No Visitors",#lab means labels title = "Number of Visitors by year by
state", # title of title making interpretation subtitle = "Yearly
comparison trend between NY and CA")
For the Y axis , i would like to label it as 1,2,3,4,5,6... all the way to 45.
Use scale_y_continuous() with the breaks = argument.
An example:
library(ggplot2)
p1 <- ggplot(mtcars) +
geom_point(aes(x = wt, y = mpg))
p2 <- ggplot(mtcars) +
geom_point(aes(x = wt, y = mpg)) +
scale_y_continuous(breaks = seq(10, 35, 1))
cowplot::plot_grid(p1, p2, ncol = 2)
Created on 2020-01-07 by the reprex package (v0.3.0)
I want to highlight 4 single points in a scatter plot with a box surrounding the name associated with the plot. I am using ggrepel to create the boxes surrounding the plots and to repel them.
This is the code I have:
library(ggplot2)
gg <- ggplot(X, aes(x = XX, y = XY)) +
geom_point(col = "steelblue", size = 3) +
geom_smooth(method = "lm", col = "firebrick", se = FALSE) +
labs(title = "XX vs XY", subtitle = "X", y = "XX", x = "XY") +
scale_x_continuous(breaks = seq(76, 82, 1)) +
scale_y_continuous(breaks = seq(15, 19, 1))
library(ggrepel)
gg + geom_text_repel(aes(label = Female), size = 3, data = X)
gg + geom_label_repel(aes(label = Female), size = 2, data = X)
With that code, I obtain boxes surrounding all the plots. However, I only want to have the boxes in 4 specific plots and no boxes in the other plots. How can I do that?
Thanks in advance! Regards,
TD
I know that when you use par( fig=c( ... ), new=T ), you can create inset graphs. However, I was wondering if it is possible to use ggplot2 library to create 'inset' graphs.
UPDATE 1: I tried using the par() with ggplot2, but it does not work.
UPDATE 2: I found a working solution at ggplot2 GoogleGroups using grid::viewport().
Section 8.4 of the book explains how to do this. The trick is to use the grid package's viewports.
#Any old plot
a_plot <- ggplot(cars, aes(speed, dist)) + geom_line()
#A viewport taking up a fraction of the plot area
vp <- viewport(width = 0.4, height = 0.4, x = 0.8, y = 0.2)
#Just draw the plot twice
png("test.png")
print(a_plot)
print(a_plot, vp = vp)
dev.off()
Much simpler solution utilizing ggplot2 and egg. Most importantly this solution works with ggsave.
library(ggplot2)
library(egg)
plotx <- ggplot(mpg, aes(displ, hwy)) + geom_point()
plotx +
annotation_custom(
ggplotGrob(plotx),
xmin = 5, xmax = 7, ymin = 30, ymax = 44
)
ggsave(filename = "inset-plot.png")
Alternatively, can use the cowplot R package by Claus O. Wilke (cowplot is a powerful extension of ggplot2). The author has an example about plotting an inset inside a larger graph in this intro vignette. Here is some adapted code:
library(cowplot)
main.plot <-
ggplot(data = mpg, aes(x = cty, y = hwy, colour = factor(cyl))) +
geom_point(size = 2.5)
inset.plot <- main.plot + theme(legend.position = "none")
plot.with.inset <-
ggdraw() +
draw_plot(main.plot) +
draw_plot(inset.plot, x = 0.07, y = .7, width = .3, height = .3)
# Can save the plot with ggsave()
ggsave(filename = "plot.with.inset.png",
plot = plot.with.inset,
width = 17,
height = 12,
units = "cm",
dpi = 300)
I prefer solutions that work with ggsave. After a lot of googling around I ended up with this (which is a general formula for positioning and sizing the plot that you insert.
library(tidyverse)
plot1 = qplot(1.00*mpg, 1.00*wt, data=mtcars) # Make sure x and y values are floating values in plot 1
plot2 = qplot(hp, cyl, data=mtcars)
plot(plot1)
# Specify position of plot2 (in percentages of plot1)
# This is in the top left and 25% width and 25% height
xleft = 0.05
xright = 0.30
ybottom = 0.70
ytop = 0.95
# Calculate position in plot1 coordinates
# Extract x and y values from plot1
l1 = ggplot_build(plot1)
x1 = l1$layout$panel_ranges[[1]]$x.range[1]
x2 = l1$layout$panel_ranges[[1]]$x.range[2]
y1 = l1$layout$panel_ranges[[1]]$y.range[1]
y2 = l1$layout$panel_ranges[[1]]$y.range[2]
xdif = x2-x1
ydif = y2-y1
xmin = x1 + (xleft*xdif)
xmax = x1 + (xright*xdif)
ymin = y1 + (ybottom*ydif)
ymax = y1 + (ytop*ydif)
# Get plot2 and make grob
g2 = ggplotGrob(plot2)
plot3 = plot1 + annotation_custom(grob = g2, xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax)
plot(plot3)
ggsave(filename = "test.png", plot = plot3)
# Try and make a weird combination of plots
g1 <- ggplotGrob(plot1)
g2 <- ggplotGrob(plot2)
g3 <- ggplotGrob(plot3)
library(gridExtra)
library(grid)
t1 = arrangeGrob(g1,ncol=1, left = textGrob("A", y = 1, vjust=1, gp=gpar(fontsize=20)))
t2 = arrangeGrob(g2,ncol=1, left = textGrob("B", y = 1, vjust=1, gp=gpar(fontsize=20)))
t3 = arrangeGrob(g3,ncol=1, left = textGrob("C", y = 1, vjust=1, gp=gpar(fontsize=20)))
final = arrangeGrob(t1,t2,t3, layout_matrix = cbind(c(1,2), c(3,3)))
grid.arrange(final)
ggsave(filename = "test2.png", plot = final)
'ggplot2' >= 3.0.0 makes possible new approaches for adding insets, as now tibble objects containing lists as member columns can be passed as data. The objects in the list column can be even whole ggplots... The latest version of my package 'ggpmisc' provides geom_plot(), geom_table() and geom_grob(), and also versions that use npc units instead of native data units for locating the insets. These geoms can add multiple insets per call and obey faceting, which annotation_custom() does not. I copy the example from the help page, which adds an inset with a zoom-in detail of the main plot as an inset.
library(tibble)
library(ggpmisc)
p <-
ggplot(data = mtcars, mapping = aes(wt, mpg)) +
geom_point()
df <- tibble(x = 0.01, y = 0.01,
plot = list(p +
coord_cartesian(xlim = c(3, 4),
ylim = c(13, 16)) +
labs(x = NULL, y = NULL) +
theme_bw(10)))
p +
expand_limits(x = 0, y = 0) +
geom_plot_npc(data = df, aes(npcx = x, npcy = y, label = plot))
Or a barplot as inset, taken from the package vignette.
library(tibble)
library(ggpmisc)
p <- ggplot(mpg, aes(factor(cyl), hwy, fill = factor(cyl))) +
stat_summary(geom = "col", fun.y = mean, width = 2/3) +
labs(x = "Number of cylinders", y = NULL, title = "Means") +
scale_fill_discrete(guide = FALSE)
data.tb <- tibble(x = 7, y = 44,
plot = list(p +
theme_bw(8)))
ggplot(mpg, aes(displ, hwy, colour = factor(cyl))) +
geom_plot(data = data.tb, aes(x, y, label = plot)) +
geom_point() +
labs(x = "Engine displacement (l)", y = "Fuel use efficiency (MPG)",
colour = "Engine cylinders\n(number)") +
theme_bw()
The next example shows how to add different inset plots to different panels in a faceted plot. The next example uses the same example data after splitting it according to the century. This particular data set once split adds the problem of one missing level in one of the inset plots. As these plots are built on their own we need to use manual scales to make sure the colors and fill are consistent across the plots. With other data sets this may not be needed.
library(tibble)
library(ggpmisc)
my.mpg <- mpg
my.mpg$century <- factor(ifelse(my.mpg$year < 2000, "XX", "XXI"))
my.mpg$cyl.f <- factor(my.mpg$cyl)
my_scale_fill <- scale_fill_manual(guide = FALSE,
values = c("red", "orange", "darkgreen", "blue"),
breaks = levels(my.mpg$cyl.f))
p1 <- ggplot(subset(my.mpg, century == "XX"),
aes(factor(cyl), hwy, fill = cyl.f)) +
stat_summary(geom = "col", fun = mean, width = 2/3) +
labs(x = "Number of cylinders", y = NULL, title = "Means") +
my_scale_fill
p2 <- ggplot(subset(my.mpg, century == "XXI"),
aes(factor(cyl), hwy, fill = cyl.f)) +
stat_summary(geom = "col", fun = mean, width = 2/3) +
labs(x = "Number of cylinders", y = NULL, title = "Means") +
my_scale_fill
data.tb <- tibble(x = c(7, 7),
y = c(44, 44),
century = factor(c("XX", "XXI")),
plot = list(p1, p2))
ggplot() +
geom_plot(data = data.tb, aes(x, y, label = plot)) +
geom_point(data = my.mpg, aes(displ, hwy, colour = cyl.f)) +
labs(x = "Engine displacement (l)", y = "Fuel use efficiency (MPG)",
colour = "Engine cylinders\n(number)") +
scale_colour_manual(guide = FALSE,
values = c("red", "orange", "darkgreen", "blue"),
breaks = levels(my.mpg$cyl.f)) +
facet_wrap(~century, ncol = 1)
In 2019, the patchwork package entered the stage, with which you can create
insets
easily by using the inset_element() function:
require(ggplot2)
require(patchwork)
gg1 = ggplot(iris, aes(Sepal.Length, Sepal.Width)) +
geom_point()
gg2 = ggplot(iris, aes(Sepal.Length)) +
geom_density()
gg1 +
inset_element(gg2, left = 0.65, bottom = 0.75, right = 1, top = 1)