This is the current version of my figure:
require(MuMIn)
require(ggplot2)
data(Cement)
d <- data.frame(Cement)
dd <- melt(d,id.var = "y")
ggplot(dd,aes(x = y,y = value, group = variable)) +
geom_point(size = 2) +
theme_classic() +
facet_grid(variable ~ ., scales = "free") +
theme(axis.text.x = element_text(angle = 90, hjust = 1)) +
xlab("") +
ylab("") +
guides(colour = FALSE)
How can I
1) Alter this graph so that the X1, X2, X3, and X4 labels are on the left hand side and they read c("factor x^2","factor x^3","factor x^4","factor x^5"),
2) Is there a method for surrounding each panel with a box, to make them more distinguishable?
Try this,
library(ggplot2)
library(gtable)
p <- ggplot(mtcars, aes(mpg, cyl))+
facet_grid(gear~., labeller=label_both) + geom_point() +
theme(strip.text.y=element_text(angle=90)) + labs(y="")
g <- ggplotGrob(p)
g$layout[g$layout$name == "strip-right",c("l", "r")] <- 2
grid.newpage()
grid.draw(g)
A solution for question 1 (partial) and 2:
names(d) <- c("x^1","x^2","x^3","x^4","y")
dd <- melt(d,id.var = "y", variable.name="factor")
ggplot(dd, aes(x = y, y = value, group = factor)) +
geom_point(size = 2) +
theme_bw() +
facet_grid(factor ~ ., scales = "free", labeller = label_both) +
theme(axis.text.x = element_text(angle = 90, hjust = 1), panel.grid = element_blank()) +
xlab("") +
ylab("") +
guides(colour = FALSE)
which gives:
Using labeller is a good option (problem #1) and facet_grid and facet_wrap have a switch argument for moving facet labels around a bit (problem #2):
library("ggplot2")
x <- runif(100)
exp <- rep(1:4, each = 25)
y <- x^exp
df <- data.frame(x, y, exp)
# facet_grid
ggplot(df, aes(x, y)) +
facet_grid(exp ~ ., labeller = label_bquote(factor~x^.(exp)), switch = "y") +
geom_point() + labs(y="") +
theme(strip.background = element_blank()) # Remove facet border if you want
# facet_wrap
ggplot(df, aes(x, y)) +
facet_wrap(~ exp, ncol = 1, labeller = label_bquote(factor~x^.(exp)), switch = "y") +
geom_point() + labs(y="") +
theme(strip.background = element_blank())
Related
I want to create a plot that looks like this:
x=1:20
y=sample(20)
df <- tibble(x=x,y=y)
ggplot(df,aes(x,y))+
geom_smooth()+
geom_point()
But the codes unabled to show legends.
Could anyone help me, thanks!
I'm perhaps being a bit over-literal in your requirements, but you could do:
tibble(x = 1:20, y = sample(20)) %>%
ggplot(aes(x, y)) +
geom_smooth(aes(linetype = "line")) +
geom_point(aes(shape = "point"), color = "red", size = 3) +
theme_gray(base_size = 20) +
theme(legend.position = c(0.75, 0.9),
legend.background = element_blank()) +
labs(shape = NULL, linetype = NULL)
You could set them inside their aes() as variables:
x <- 1:20
y <- sample(20)
library(ggplot2)
library(dplyr)
df <- tibble(x=x,y=y)
ggplot(df,aes(x,y))+
geom_smooth(aes(color = "line"))+
geom_point(aes(color = "point"))+
scale_color_manual(values = c("blue","red"))
With ggnewscale you could try:
library(tibble)
library(ggplot2)
library(ggnewscale)
x=1:20
y=sample(20)
df1 <- tibble(x=x, y=y)
ggplot(df1, aes(x, y))+
geom_smooth(aes(colour = "line"))+
scale_colour_manual(values = "black") +
labs(colour = NULL)+
new_scale_colour()+
geom_point(aes(colour = "point"))+
scale_colour_manual(values = "red")+
labs(colour = NULL)
#> `geom_smooth()` using method = 'loess' and formula = 'y ~ x'
Created on 2022-11-27 with reprex v2.0.2
I am currently working with a dataset of "world bank islands". In that, I am trying to plot the population Vs country graph for each year. Below is the code that I have done.
library(ggplot2)
options(scipen = 999)
bank <- read.csv("C:/Users/True Gamer/OneDrive/Desktop/world_bank_international_arrivals_islands.csv")
bank[bank == "" | bank == "."] <- NA
bank$country <- as.numeric(bank$country)
bank$year <- as.numeric(bank$year)
bank$areakm2 <- as.numeric(bank$areakm2)
bank$pop <- as.numeric(bank$pop)
bank$gdpnom <- as.numeric(bank$gdpnom)
bank$flights...WB <- as.numeric(bank$flights...WB)
bank$hotels <- as.numeric(bank$hotels)
bank$hotrooms <- as.numeric(bank$hotrooms)
bank$receipt <- as.numeric(bank$receipt)
bank$ovnarriv <- as.numeric(bank$ovnarriv)
bank$dayvisit <- as.numeric(bank$dayvisit)
bank$arram <- as.numeric(bank$arram)
bank$arreur <- as.numeric(bank$arreur)
bank$arraus <- as.numeric(bank$arraus)
str(bank)
plot1 <- ggplot(bank, aes(x=country,y=pop)) + geom_bar(stat = "identity",aes(fill=year)) + ggtitle("Population of each country yearwise") + xlab("Countries") + ylab("Population")
plot1
However, when I do this, the y values shown on the graph are different from the actual y values. This is the link to the dataset
The problem is that you are stacking the bars (this is default behaviour). Also, geom_bar(stat = "identity") is just a long way of writing geom_col. One further point to note is that since all your columns are numeric, the single line:
bank <- as.data.frame(lapply(bank, as.numeric))
replaces all your individual numeric conversions.
The plot you are trying to create would be something like this:
ggplot(bank, aes(x = country, y = pop)) +
geom_col(aes(fill = factor(year)), position = "dodge") +
ggtitle("Population of each country yearwise") +
xlab("Countries") +
ylab("Population") +
labs(fill = "Year") +
scale_y_continuous(labels = scales::comma) +
scale_x_continuous(breaks = 1:27)
However, it would probably be best to present your data in a different way. Perhaps, if you are comparing population growth, something like this would be better:
ggplot(bank, aes(x = year, y = pop)) +
geom_line(aes(color = factor(country)), position = "dodge") +
ggtitle("Population of each country yearwise") +
xlab("Year") +
ylab("Population") +
facet_wrap(.~country, scales = "free_y", nrow = 6) +
scale_y_continuous(labels = scales::comma) +
scale_x_continuous(breaks = c(0, 5, 10)) +
theme_minimal() +
theme(legend.position = "none")
Or with bars:
ggplot(bank, aes(x = year, y = pop)) +
geom_col(aes(fill = factor(country)), position = "dodge") +
ggtitle("Population of each country yearwise") +
xlab("Year") +
ylab("Population") +
facet_wrap(.~country, scales = "free_y", nrow = 6) +
scale_y_continuous(labels = scales::comma) +
scale_x_continuous(breaks = c(0, 5, 10)) +
theme_minimal() +
theme(legend.position = "none")
I want to customize the formula used in geom_smooth like this:
library(MASS)
library(ggplot2)
data("Cars93", package = "MASS")
str(Cars93)
Cars93.log <- transform(Cars93, log.price = log(Price))
log.model <- lm(log.price ~ Horsepower*Origin, data = Cars93.log)
summary(log.model)
plot(log.model)
p <- ggplot(data = Cars93.log, aes(x = Horsepower, y = log.price, colour = Origin)) +
geom_point(aes(shape = Origin, color = Origin)) + # Punkte
facet_grid(~ Origin) +
theme(axis.title.x = element_text(margin=margin(15,0,0,0)),
axis.title.y = element_text(margin=margin(0,15,0,0))) +
scale_y_continuous(n.breaks = 7) +
scale_colour_manual(values = c("USA" = "red","non-USA" = "black")) +
scale_shape_manual(values = c(16,16)) +
ylab("Price(log)")
lm.mod <- function(df) {
y ~ x*Cars93.log$Origin
}
p_smooth <- by(Cars93.log, Cars93.log$Origin,
function(x) geom_smooth(data=x, method = lm, formula = lm.mod(x)))
p + p_smooth
However, I receive the error that the computation failed because of different lengths of my used variables.
length(Cars93.log$log.price)
length(Cars93.log$Origin)
length(Cars93.log$Horsepower)
But when I check the length for each variable they're all the same... Any ideas, what's wrong?
Thanks a lot, Martina
I agree with #Rui Barradas, seems like the issue is the lines for lm.mod and p_smooth and the by function
Once you are making a distinction by Origin (e.g., by doing either facet_wrap or color = Origin) then geom_smooth will automatically run different models for those facets.
p <- ggplot(data = Cars93.log,
aes(x = Horsepower, y = log.price, color = Origin)) +
geom_point(aes(shape = Origin)) +
facet_wrap(~ Origin) +
theme(axis.title.x = element_text(margin=margin(15,0,0,0)),
axis.title.y = element_text(margin=margin(0,15,0,0))) +
scale_y_continuous(n.breaks = 7) +
scale_colour_manual(values = c("USA" = "red","non-USA" = "black")) +
scale_shape_manual(values = c(16,16)) +
ylab("Price(log)")
p + geom_smooth(method = lm, formula = y ~ x)
you can convince yourself that this is the same as the output of log.model by extending the x-axis limits to see where the geom_smooth line would cross the y axis (e.g., + coord_cartesian(xlim = c(0, 300)))
You can also see the difference in the graph if you don't pass color = Origin to the geom_smooth function (essentially what is happening if you comment this out from the first ggplot() initialization):
p <- ggplot(data = Cars93.log,
aes(x = Horsepower, y = log.price)) + # color = Origin)) +
geom_point(aes(shape = Origin)) +
#facet_wrap(~ Origin) +
theme(axis.title.x = element_text(margin=margin(15,0,0,0)),
axis.title.y = element_text(margin=margin(0,15,0,0))) +
scale_y_continuous(n.breaks = 7) +
scale_colour_manual(values = c("USA" = "red","non-USA" = "black")) +
scale_shape_manual(values = c(16,16)) +
ylab("Price(log)")
p + geom_smooth(method = lm, formula = y ~ x)
I am trying to add the labels A, B, and C to the top left hand corner of each of these graphs. I have tried cowplot::draw_plot_label(), but nothing seems to work. Can anyone help?
These A, B and C labels are not the main title of each plot.
# Packages
library(ggplot2)
library(gridExtra)
library(cowplot)
# 1st plot
p1 <- ggplot(data = new_data %>%
filter(Species =="Sharksucker_Remora")) +
scale_colour_manual(values=c(Sharksucker_Remora="black"), labels = c("Sharksucker Remora")) +
geom_line(mapping = aes(x = Date, y = Proportion, group = Species, colour = Species)) +
xlab("") +
ylab("Proportion") +
theme(legend.position="top") +
theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)) + labs(colour = ~italic(M.alfredi)~"Hitchhiker Species:") +
theme(legend.key=element_blank())
# 2nd plot
p2 <- ggplot(data = new_data %>%
filter(Species !="Sharksucker_Remora")) +
geom_line(mapping = aes(x = Date, y = Proportion, group = Species, colour = Species)) +
scale_colour_manual(values=c(Golden_Trevally="goldenrod2", Red_Snapper="firebrick2", Juvenile_Remora="darkolivegreen3"), labels = c("Juvenile Remora", "Golden Trevally", "Red Snapper")) +
xlab("") + ylab("Proportion") + labs(colour = "") + theme(legend.position="top") + theme(legend.key=element_blank()) +
theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1))
# 3rd plot
p3 <- ggplot(data = new_data_counts) +
geom_bar(mapping = aes(x = Date, y = Count), stat =
'identity') +
xlab("Date (2015-2019)") + ylab("Total"~italic
(M.alfredi)~"Sightings") +
draw_plot_label(label =c("C") + theme(axis.text.x =
element_text(angle = 90, vjust = 0.5, hjust = 1))
# The grid
grid.arrange(p1,p2,p3)
I suggest you use labs(..., tag = ...) and theme(plot.tag = element_text()).
The code show how you can format the main title (here centered with hjust = 0.5) and the tag inside the theme() function. See the reproducible example, below:
# Packages
library(ggplot2)
library(gridExtra)
# library(cowplot) # not necessary here
# Plots
p1 <- ggplot() +
labs(title = "plot 1", tag = "A") +
theme(plot.title = element_text(hjust = 0.5),
plot.tag = element_text())
p2 <- ggplot() +
labs(title = "plot 2", tag = "B") +
theme(plot.title = element_text(hjust = 0.5),
plot.tag = element_text())
grid.arrange(p1, p2)
If you want the tag (A, B, C) to be inside the plotting area, this post suggest to use plot.tag.position = c(x, y). See for example:
p3 <- ggplot() +
labs(title = "plot 3", tag = "C") +
theme(plot.title = element_text(hjust = 0.5),
plot.tag = element_text(),
plot.tag.position = c(0.1, 0.8))
p3
Have you tried the package egg?
https://cran.r-project.org/web/packages/egg/vignettes/Overview.html
library(tidyverse)
library(magrittr)
data <- list()
for(i in 1:6) data[[i]] <- rnorm(100,0,1)
data %<>% bind_cols() %>% setNames(paste0("var",1:6))
p1 <- ggplot(data,aes(x = var1, y = var2)) + geom_point()
p2 <- ggplot(data,aes(x = var3, y = var4)) + geom_point()
p3 <- ggplot(data,aes(x = var5, y = var6)) + geom_point()
egg::ggarrange(p1,p2,p3,ncol = 1,
labels = c("A","B","C"))
Another option is using the patchwork package with plot_annotation which has the tag_levels argument which gives the possibility to add tags like letters or numbers. First a reproducible example with letters:
library(patchwork)
library(ggplot2)
p1 <- ggplot(mtcars) +
geom_point(aes(hp, disp)) +
ggtitle('Plot 1')
p2 <- ggplot(mtcars) +
geom_boxplot(aes(gear, mpg, group = gear)) +
ggtitle('Plot 2')
p1 + p2 & plot_annotation(tag_levels = 'A')
Created on 2022-08-21 with reprex v2.0.2
Another option with numbers where you change the tag_levels to "1" like this:
p1 + p2 & plot_annotation(tag_levels = '1')
Created on 2022-08-21 with reprex v2.0.2
As you can see, the tags have letters or numbers. Check the links above for more information and options.
ggplot(all, aes(x=area, y=nq)) +
geom_point(size=0.5) +
geom_abline(data = levelnew, aes(intercept=log10(exp(interceptmax)), slope=fslope)) + #shifted regression line
scale_y_log10(labels = function(y) format(y, scientific = FALSE)) +
scale_x_log10(labels = function(x) format(x, scientific = FALSE)) +
facet_wrap(~levels) +
theme_bw() +
theme(panel.grid.major = element_line(colour = "#808080"))
And I get this figure
Now I want to add one geom_line to one of the facets. Basically, I wanted to have a dotted line (Say x=10,000) in only the major panel. How can I do this?
I don't have your data, so I made some up:
df <- data.frame(x=rnorm(100),y=rnorm(100),z=rep(letters[1:4],each=25))
ggplot(df,aes(x,y)) +
geom_point() +
theme_bw() +
facet_wrap(~z)
To add a vertical line at x = 1 we can use geom_vline() with a dataframe that has the same faceting variable (in my case z='b', but yours will be levels='major'):
ggplot(df,aes(x,y)) +
geom_point() +
theme_bw() +
facet_wrap(~z) +
geom_vline(data = data.frame(xint=1,z="b"), aes(xintercept = xint), linetype = "dotted")
Another way to express this which is possibly easier to generalize (and formatting stuff left out):
ggplot(df, aes(x,y)) +
geom_point() +
facet_wrap(~ z) +
geom_vline(data = subset(df, z == "b"), aes(xintercept = 1))
The key things being: facet first, then decorate facets by subsetting the original data frame, and put the details in a new aes if possible. Other examples of a similar idea:
ggplot(df, aes(x,y)) +
geom_point() +
facet_wrap(~ z) +
geom_vline(data = subset(df, z == "b"), aes(xintercept = 1)) +
geom_smooth(data = subset(df, z == "c"), aes(x, y), method = lm, se = FALSE) +
geom_text(data = subset(df, z == "d"), aes(x = -2, y=0, label = "Foobar"))