I want a pie chart instead of a table
method <- dataframe (stringsFactors=FALSE,method=c("violent","nonviolent"),accessiblepeople = (20000,60000)
usage <- dataframe (stringsFactors=FALSE,method=c("violent","nonviolent"),usage = (30%,70%)
ggplot(method, aes(x=method,y=accessiblepeople)+geom_bar(stat="identity")+ggtitle("")+ggpiechart())
Problem add piechart seems not working
You can use plot_grid from the package cowplot to place plots next to each other. I also specified a few features with theme() to remove the gray background so the final plot looks more cohesive.
library(tidyverse)
library(cowplot)
method <- data.frame(method = c("violent", "nonviolent"),
accessiblepeople = c(20000,60000))
bar <- ggplot(method, aes(x = method, y = accessiblepeople, fill = method)) +
geom_bar(stat = "identity") + ggtitle("") +
theme_bw() +
theme(legend.position = "none") +
theme(panel.border = element_blank(),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
axis.line = element_line(color = "black"))
pie <- ggplot(method_df, aes(x="", y=accessiblepeople, fill=method)) +
geom_bar(stat="identity", width=1) +
coord_polar("y", start=0) + theme_void()
plot_grid(bar, pie)
Related
I am trying to plot three variables and want the units in the axes labels but can't find a way to label them properly in facets with the superscripts.
I've tried as_labeller, label_bquote, expression/paste and changing the original data.
p <- ggplot(data = LST, aes(x = Date, y = Measurements)) +
geom_point((aes(color = parameter)))
p + facet_grid(parameter ~ ., scales = "free_y",
switch="y",labeller=as_labeller(DO~(mg~L^{-1}), Temperature~(°C), Light~
(µmol~m^{-2}~s^{-1}))) +
theme_bw()+ theme(strip.background = element_blank(),
legend.title = element_blank(), strip.placement = "outside",
panel.grid.minor = element_blank()) +
scale_x_datetime()+ ylab(NULL) +ggtitle("Spring 2018") +
scale_colour_manual(values=c('royalblue1', 'springgreen4', 'darkblue')) +
theme(legend.position="none")+
theme(strip.text=element_text(size=10))
Everything I try either labels all facets the same or doesn't place the superscripts. I'm pretty new at ggplot2 so am unsure if what I'm trying will help.
You want labeller = label_parsed. Here's a simple example
mt = mtcars
mt$facets = factor(mt$cyl, labels = c(
"DO~(mg~L^{-1})",
"Temperature~('°C')",
"Light~(µmol~m^{-2}~s^{-1})"))
ggplot(mt, aes(mpg,cyl)) +
geom_point() +
facet_grid(~facets, labeller = label_parsed)
I am trying to draw this following graph using ggplot2 package, but somehow the axis won't show up. the ticks are there, just not the axis line. I have used the theme(axis.line=element_line()) function, but it wouldn't work.
Here is my code:
library(ggplot2)
ggplot(data = soepl_randsub, aes(x = year, y =satisf_org, group = id)) +
geom_point() + geom_line() +ylab("Current Life Satisfaction") +theme_bw() +
theme(plot.background = element_blank(),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank() ) +
theme(panel.border= element_blank()) +
theme(axis.line = element_line(color="black", size = "2"))
I am not sure what went wrong. Here is the chart.
The bug was fixed in ggplot2 v2.2.0 There is no longer a need to specify axis lines separately.
I think this is a bug in ggplot2 v2.1.0. (See this bug report and this one.) A workaround is to set the x-axis and y-axis lines separately.
library(ggplot2)
ggplot(data = mpg, aes(x = hwy, y = displ)) +
geom_point() +
theme_bw() +
theme(plot.background = element_blank(),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank() )+
theme(panel.border= element_blank())+
theme(axis.line.x = element_line(color="black", size = 2),
axis.line.y = element_line(color="black", size = 2))
You don't need to specify axis-size for X and Y separately. When you are specifying size="2", R is considering value 2 as non-numeric argument. Hence, axis-line parameter is defaulted to 0 size. Use this line of code:
ggplot(data = mpg, aes(x = hwy, y = displ)) + geom_point() +xlab("Date")+ylab("Value of Home")+theme_bw() +theme(plot.background = element_blank(),panel.grid.major = element_blank(),panel.grid.minor = element_blank()) + theme(panel.border= element_blank()) +
theme(axis.line = element_line(color="black", size = 2))
axis_line inherits from line in R, hence specifying size is mandatory for non-default values.
I am pretty new to R and am trying to create a composite plot using ggplot. I have searched how to do this and have seen I can use the facet function, however, it seems that this is for plotting data which can be split by type e.g. male/female. I have a data frame and I want to plot recovery against concentration, and recovery against equilibrium time on separate plots but as a composite plot. For this I have the following code:
p1 <- ggplot(dat2, aes(x = EqmTime, y = Recovery))
limits <- aes(ymax = Recovery + RecoveryError, ymin=Recovery - RecoveryError)
p1 + geom_point(size = 4) + geom_errorbar(limits, width=4) + geom_smooth(method = "lm", se = FALSE, colour="gray", size=1.5, linetype="dashed") +
labs(x='Equilibrium Time (hrs)', y='Nitrate Recovery (%)') + theme_bw() +
theme(axis.line = element_line(colour = "black"),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.border = element_blank(),
panel.background = element_blank())
p2 <- ggplot(dat2, aes(x = StockConc, y = Recovery))
limits <- aes(ymax = Recovery + RecoveryError, ymin=Recovery - RecoveryError)
p2 + geom_point(size = 4) + geom_errorbar(limits, width=0.1) + geom_smooth(method = "lm", se = FALSE, colour="gray", size=1.5, linetype="dashed") +
labs(x='Concentration (g L-1)', y='Nitrate Recovery (%)') + theme_bw() +
theme(axis.line = element_line(colour = "black"),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.border = element_blank(),
panel.background = element_blank())
Additionally, I also have a problem that I cannot get the '-1' in the x axis label of plot 2 as a superscript, and am having trouble setting axis limits. When I set, for example, xlim=20-180, the axis doesn't start and finish at these, but makes these the major tick marks.
I would greatly appreciate any help with this! I know some of these issues have been addressed in other posts but I cannot seem to use this advise to sort the issue here.
From your question, I understand that you want to plot both the ggplots in single plot window. You can do this using gridextra package as:
library(gridExtra)
grid.arrange(p1, p2, nrow=2)
I'm working with some data that I want to display as a nxn grid of plots. Edit: To be more clear, there's 21 categories in my data. I want to facet by category, and have those 21 plots in a 5 x 5 square grid (where the orphan is by itself on the fifth row). Thus facet_wrap instead of facet_grid.
I've got the following code written up for doing it (using the good old iris data set for my reproducible example):
library(ggplot2)
library(grid)
cust_theme <- theme_bw() + theme(legend.position="none",
axis.title = element_blank(), axis.ticks = element_blank(),
axis.text = element_blank(), strip.text = element_blank(),
strip.background = element_blank(), panel.margin = unit(0, "lines"),
panel.border = element_rect(size = 0.25, color = "black"),
panel.grid = element_blank())
iris.plot <- ggplot(data = iris, aes(x = Sepal.Length, y = Sepal.Width, color = Species)) +
geom_point() + cust_theme + facet_wrap( ~ Species, ncol = 2) +
labs(title = "Irises by species")
This gives me ALMOST what I want, but not quite:
I've still got a tiny strip of space between the top row of plots and the bottom row. I'd like to get rid of that entirely, but panel.margin is obviously not doing it. Is there a way to do this?
This might be a little late, but panel.marginis now deprecated. Inside theme use panel.spacing. To eliminate the spacing between the facets then load the grid package and use panel.spacing = unit(0, "lines")
Change the panel.margin argument to panel.margin = unit(c(-0.5,0-0.5,0), "lines"). For some reason the top and bottom margins need to be negative to line up perfectly. Here is the result:
You can also edit the grobs directly:
library(ggplot2)
library(grid)
g <- ggplot(data = iris, aes(x = Sepal.Length, y = Sepal.Width, color = Species)) +
geom_point() +
facet_wrap( ~ Species, ncol = 2) +
labs(title = "Irises by species") +
theme_bw() +
theme(panel.margin = unit(0, "lines")) +
theme(plot.margin = unit(c(0,0,0,0), "lines")) +
theme(strip.background = element_blank()) +
theme(plot.background = element_blank()) +
theme(strip.text = element_blank()) +
theme(axis.ticks.margin = unit(0, "lines"))
g <- ggplotGrob(p)
g$heights[[7]] = unit(0, "lines")
grid.newpage()
grid.draw(g)
How can scatter plots with alpha transparent, scale-less histograms can be made in R, like this figure?
looks like it's not made in ggplot2.
does anyone know what command is used?
library(ggplot2)
library(gridExtra)
set.seed(42)
DF <- data.frame(x=rnorm(100,mean=c(1,5)),y=rlnorm(100,meanlog=c(8,6)),group=1:2)
p1 <- ggplot(DF,aes(x=x,y=y,colour=factor(group))) + geom_point() +
scale_x_continuous(expand=c(0.02,0)) +
scale_y_continuous(expand=c(0.02,0)) +
theme_bw() +
theme(legend.position="none",plot.margin=unit(c(0,0,0,0),"points"))
theme0 <- function(...) theme( legend.position = "none",
panel.background = element_blank(),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.margin = unit(0,"null"),
axis.ticks = element_blank(),
axis.text.x = element_blank(),
axis.text.y = element_blank(),
axis.title.x = element_blank(),
axis.title.y = element_blank(),
axis.ticks.length = unit(0,"null"),
axis.ticks.margin = unit(0,"null"),
panel.border=element_rect(color=NA),...)
p2 <- ggplot(DF,aes(x=x,colour=factor(group),fill=factor(group))) +
geom_density(alpha=0.5) +
scale_x_continuous(breaks=NULL,expand=c(0.02,0)) +
scale_y_continuous(breaks=NULL,expand=c(0.02,0)) +
theme_bw() +
theme0(plot.margin = unit(c(1,0,0,2.2),"lines"))
p3 <- ggplot(DF,aes(x=y,colour=factor(group),fill=factor(group))) +
geom_density(alpha=0.5) +
coord_flip() +
scale_x_continuous(labels = NULL,breaks=NULL,expand=c(0.02,0)) +
scale_y_continuous(labels = NULL,breaks=NULL,expand=c(0.02,0)) +
theme_bw() +
theme0(plot.margin = unit(c(0,1,1.2,0),"lines"))
grid.arrange(arrangeGrob(p2,ncol=2,widths=c(3,1)),
arrangeGrob(p1,p3,ncol=2,widths=c(3,1)),
heights=c(1,3))
Edit:
I couldn't find out what causes the space below the densities geoms. You can fiddle with the plot margins to avoid it, but I don't really like that.
p2 <- ggplot(DF,aes(x=x,colour=factor(group),fill=factor(group))) +
geom_density(alpha=0.5) +
scale_x_continuous(breaks=NULL,expand=c(0.02,0)) +
scale_y_continuous(breaks=NULL,expand=c(0.00,0)) +
theme_bw() +
theme0(plot.margin = unit(c(1,0,-0.48,2.2),"lines"))
p3 <- ggplot(DF,aes(x=y,colour=factor(group),fill=factor(group))) +
geom_density(alpha=0.5) +
coord_flip() +
scale_x_continuous(labels = NULL,breaks=NULL,expand=c(0.02,0)) +
scale_y_continuous(labels = NULL,breaks=NULL,expand=c(0.00,0)) +
theme_bw() +
theme0(plot.margin = unit(c(0,1,1.2,-0.48),"lines"))
I have no idea whether there is a package that does that directly, but I'm sure this can be done in R. Transparency is easy: you add another two digits to the RGB specification of a color for a given transparency:
#FF0000 # red
#FF0000FF # full opacity
#FF000000 # full transparency
Combining different plots is also easy using the layout function. As for the vertical density plot, it is just the same as the horizontal plot with x and y switched. The example given here can easily be expanded to include colors, smaller margins etc. I can try to come up with a more elaborate example if this description is not sufficient.