Who can tell me why ggplot can't give me grouped bars?
ggplot(df, aes(x = factor(labels), y = srednia, dodge=factor(group))) +
labs(title = gen, size=3)+ ylab("Fold change")+ xlab("Linnia komórkowa") +
geom_bar(aes(fill=factor(group)),stat="identity",position ="dodge") +
geom_errorbar(aes(ymin=minus, ymax=plus))
Grouped bars I means something like this (paint art):
Thank you in advance!
I guess you can achieve this by changing the scale for the x axis. Here's a reproducible example and a possible solution.
# packages
require(plyr)
require(ggplot2)
# generate data
set.seed(123)
df <- data.frame(labels=LETTERS[1:6],
group=rep(1:3, each=2),
srednia=runif(6))
# limits for x axis
mylims <- head(unlist(dlply(df, .(group), function(x) c(levels(factor(x$labels)), "space"))), -1)
# additional space between groups
ggplot(df, aes(x = factor(labels), y = srednia, dodge=factor(group))) +
geom_bar(aes(fill=factor(group)),stat="identity") +
scale_x_discrete(limits=mylims, breaks=levels(factor(df$labels)))
# removing space within group
ggplot(df, aes(x = factor(labels), y = srednia, dodge=factor(group))) +
geom_bar(aes(fill=factor(group)),stat="identity", width=1) +
scale_x_discrete(limits=mylims, breaks=levels(factor(df$labels)))
Related
I have a plot like this:
p<-ggplot() +
geom_line(data= myData, aes(x = myData$x , y = myData$y)) +
scale_x_log10()+
scale_y_log10()
My x value is seq(9880000, 12220000, 10000)
There is only one break on the x-axis of the plot, what should I do if to get at least 3 breaks on the plot x-axis?
Here is fully reproducible example of the original poster's problem where a log-scaled plot only displays one break value on the x-axis. I demonstrate three possible solutions below.
library(ggplot2)
# Create a reproducible example data.frame using R functions.
x = seq(9880000, 12220000, 10000)
# Use set.seed() so that anyone who runs this code
# will get the same sequence of 'random' values.
set.seed(31415)
y = cumsum(runif(n=length(x), min=-1e5, max=1e5)) + 1e6
dat = data.frame(x=x, y=y)
# Original poster's plot.
p1 = ggplot(data=dat, aes(x=x, y=y)) +
geom_line() +
scale_x_log10() +
scale_y_log10() +
labs(title="1. Plot has only one x-axis break.")
# Add extra x-axis breaks manually.
x_breaks = c(10^7.0, 10^7.04, 10^7.08)
p2 = ggplot(data=dat, aes(x=x, y=y)) +
geom_line() +
scale_x_log10(breaks=x_breaks) +
scale_y_log10() +
labs(title="2. Add some x-axis breaks manually.")
# Add extra x-axis breaks in semi-automated manner.
x_breaks = 10^pretty(log10(x))
x_labels = formatC(x_breaks, format = "e", digits = 2)
p3 = ggplot(data=dat, aes(x=x, y=y)) +
geom_line() +
scale_x_log10(breaks=x_breaks, labels=x_labels) +
scale_y_log10() +
labs(title="3. Create x-axis breaks with R functions.")
# Skip the log10 scale because the x-values don't span multiple orders of magnitude.
p4 = ggplot(data=dat, aes(x=x, y=y)) +
geom_line() +
scale_y_log10() +
labs(title="4. Check appearance without log10 scale for x-axis.")
library(gridExtra)
ggsave("example.png", plot=arrangeGrob(p1, p2, p3, p4, nrow=2),
width=10, height=5, dpi=150)
I add: scale_x_log10(breaks=seq(9880000, 12220000, 1000000)).
This is my reproducible example:
library(random)
library(ggplot2)
z <- randomStrings(n=235, len=5, digits=TRUE, upperalpha=TRUE, loweralpha=TRUE, unique=TRUE, check=TRUE)
x <- seq(9880000, 12220000, 10000)
y <- randomNumbers(n=235, min=9880000, max=12220000, col=1)
df <- data.frame(z, x, y)
head(df)
V1 x V1.1
1 378VO 9880000 11501626
2 AStRK 9890000 10929705
3 sotp4 9900000 11305700
4 AS4DR 9910000 11302110
5 7iFdk 9920000 11611918
6 HIS7z 9930000 11175074
p<-ggplot() + geom_line(data= df, aes(x = df$x , y = df$V1.1)) + scale_y_log10()
p + scale_x_log10(breaks=seq(9880000, 12220000, 1000000))
Hope it is useful...
Add this between your parenthesis: breaks=seq(specify, breaks, here)
For example, if you wanted a break at 0, 10, 100:
scale_x_log10((breaks=seq(0,10,100))
I have a data frame with five columns and five rows. the data frame looks like this:
df <- data.frame(
day=c("m","t","w","t","f"),
V1=c(5,10,20,15,20),
V2=c(0.1,0.2,0.6,0.5,0.8),
V3=c(120,100,110,120,100),
V4=c(1,10,6,8,8)
)
I want to do some plots so I used the ggplot and in particular the geom_bar:
ggplot(df, aes(x = day, y = V1, group = 1)) + ylim(0,20)+ geom_bar(stat = "identity")
ggplot(df, aes(x = day, y = V2, group = 1)) + ylim(0,1)+ geom_bar(stat = "identity")
ggplot(df, aes(x = day, y = V3, group = 1)) + ylim(50,200)+ geom_bar(stat = "identity")
ggplot(df, aes(x = day, y = V4, group = 1)) + ylim(0,15)+ geom_bar(stat = "identity")
My question is, How can I do a grouped ggplot with geom_bar with multiple y axis? I want at the x axis the day and for each day I want to plot four bins V1,V2,V3,V4 but with different range and color. Is that possible?
EDIT
I want the y axis to look like this:
require(reshape)
data.m <- melt(df, id.vars='day')
ggplot(data.m, aes(day, value)) +
geom_bar(aes(fill = variable), position = "dodge", stat="identity") +
facet_grid(variable ~ .)
You can also change the y-axis limits if you like (here's an example).
Alternately you may have meant grouped like this:
require(reshape)
data.m <- melt(df, id.vars='day')
ggplot(data.m, aes(day, value)) +
geom_bar(aes(fill = variable), position = "dodge", stat="identity")
For the latter examples if you want 2 Y axes then you just create the plot twice (once with a left y axis and once with a right y axis) then use this function:
double_axis_graph <- function(graf1,graf2){
graf1 <- graf1
graf2 <- graf2
gtable1 <- ggplot_gtable(ggplot_build(graf1))
gtable2 <- ggplot_gtable(ggplot_build(graf2))
par <- c(subset(gtable1[['layout']], name=='panel', select=t:r))
graf <- gtable_add_grob(gtable1, gtable2[['grobs']][[which(gtable2[['layout']][['name']]=='panel')]],
par['t'],par['l'],par['b'],par['r'])
ia <- which(gtable2[['layout']][['name']]=='axis-l')
ga <- gtable2[['grobs']][[ia]]
ax <- ga[['children']][[2]]
ax[['widths']] <- rev(ax[['widths']])
ax[['grobs']] <- rev(ax[['grobs']])
ax[['grobs']][[1]][['x']] <- ax[['grobs']][[1]][['x']] - unit(1,'npc') + unit(0.15,'cm')
graf <- gtable_add_cols(graf, gtable2[['widths']][gtable2[['layout']][ia, ][['l']]], length(graf[['widths']])-1)
graf <- gtable_add_grob(graf, ax, par['t'], length(graf[['widths']])-1, par['b'])
return(graf)
}
I believe there's also a package or convenience function that does the same thing.
First I reshaped as described in the documentation in the link below the question.
In general ggplot does not support multiple y-axis. I think it is a philosophical thing. But maybe faceting will work for you.
df <- read.table(text = "day V1 V2 V3 V4
m 5 0.1 120 1
t 10 0.2 100 10
w 2 0.6 110 6
t 15 0.5 120 8
f 20 0.8 100 8", header = TRUE)
library(reshape2)
df <- melt(df, id.vars = 'day')
ggplot(df, aes(x = variable, y = value, fill = variable)) + geom_bar(stat = "identity") + facet_grid(.~day)
If I understand correctly you want to include facets in your plot. You have to use reshape2 to get the data in the right format. Here's an example with your data:
df <- data.frame(
day=c("m","t","w","t","f"),
V1=c(5,10,20,15,20),
V2=c(0.1,0.2,0.6,0.5,0.8),
V3=c(120,100,110,120,100),
V4=c(1,10,6,8,8)
)
library(reshape2)
df <- melt(df, "day")
Then plot with and include facet_grid argument:
ggplot(df, aes(x=day, y=value)) + geom_bar(stat="identity", aes(fill=variable)) +
facet_grid(variable ~ .)
In the code below I build a 40x1000 data frame where in each column I have the cumulative means for successive random draws from an exponential distribution with parameter lambda = 0.2.
I add an additional column to host the specific number of the "draw".
I also calculate the rowmeans as df_means.
How do I add df_means (as a black line) on top of all my simulated RVs? I don't understand ggplot well enough to do this.
df <- data.frame(replicate(1000,cumsum(rexp(40,lambda))/(1:40)))
df$draw <- seq(1,40)
df_means <- rowMeans(df)
Molten <- melt(df, id.vars="draw")
ggplot(Molten, aes(x = draw, y = value, colour = variable)) + geom_line() + theme(legend.position = "none") + geom_line(df_means)
How would I add plot(df_means, type="l") to my ggplot, below?
Thank you,
You can make another data.frame with the means and ids and use that to draw the line,
df_means <- rowMeans(df)
means <- data.frame(id=1:40, mu=df_means)
ggplot(Molten, aes(x=draw, y=value, colour=variable)) +
geom_line() +
theme(legend.position = "none") +
geom_line(data=means, aes(x=id, y=mu), color="black")
As described here
stat_sum_df <- function(fun, geom="crossbar", ...) {
stat_summary(fun.data=fun, colour="red", geom=geom, width=0.2, ...)
}
k<-ggplot(Molten, aes(x = draw, y = value, colour = variable)) + geom_line() + theme(legend.position = "none")
k+stat_sum_single(mean) #gives you the required plot
Im trying to align the x-axes of a bar plot and line plot in one window frame using ggplot. Here is the fake data I'm trying to do it with.
library(ggplot2)
library(gridExtra)
m <- as.data.frame(matrix(0, ncol = 2, nrow = 27))
colnames(m) <- c("x", "y")
for( i in 1:nrow(m))
{
m$x[i] <- i
m$y[i] <- ((i*2) + 3)
}
My_plot <- (ggplot(data = m, aes(x = x, y = y)) + theme_bw())
Line_plot <- My_plot + geom_line()
Bar_plot <- My_plot + geom_bar(stat = "identity")
grid.arrange(Line_plot, Bar_plot)
Thank you for your help.
#eipi10 answers this particular case, but in general you also need to equalize the plot widths. If, for example, the y labels on one of the plots take up more space than on the other, even if you use the same axis on each plot, they will not line up when passed to grid.arrange:
axis <- scale_x_continuous(limits=range(m$x))
Line_plot <- ggplot(data = m, aes(x = x, y = y)) + theme_bw() + axis + geom_line()
m2 <- within(m, y <- y * 1e7)
Bar_plot <- ggplot(data = m2, aes(x = x, y = y)) + theme_bw() + axis + geom_bar(stat = "identity")
grid.arrange(Line_plot, Bar_plot)
In this case, you have to equalize the plot widths:
Line_plot <- ggplot_gtable(ggplot_build(Line_plot))
Bar_plot <- ggplot_gtable(ggplot_build(Bar_plot))
Bar_plot$widths <-Line_plot$widths
grid.arrange(Line_plot, Bar_plot)
The gridlines on the x axes will be aligned if you use scale_x_continuous to force ggplot to use limits you specify.
My_plot <- ggplot(data = m, aes(x = x, y = y)) + theme_bw() +
scale_x_continuous(limits=range(m$x))
Now, when you add the layers, the axes will share the common scaling.
I have data where I look at the difference in growth between a monoculture and a mixed culture for two different species. Additionally, I made a graph to make my data clear.
I want a barplot with error bars, the whole dataset is of course bigger, but for this graph this is the data.frame with the means for the barplot.
plant species means
Mixed culture Elytrigia 0.886625
Monoculture Elytrigia 1.022667
Monoculture Festuca 0.314375
Mixed culture Festuca 0.078125
With this data I made a graph in ggplot2, where plant is on the x-axis and means on the y-axis, and I used a facet to divide the species.
This is my code:
limits <- aes(ymax = meansS$means + eS$se, ymin=meansS$means - eS$se)
dodge <- position_dodge(width=0.9)
myplot <- ggplot(data=meansS, aes(x=plant, y=means, fill=plant)) + facet_grid(. ~ species)
myplot <- myplot + geom_bar(position=dodge) + geom_errorbar(limits, position=dodge, width=0.25)
myplot <- myplot + scale_fill_manual(values=c("#6495ED","#FF7F50"))
myplot <- myplot + labs(x = "Plant treatment", y = "Shoot biomass (gr)")
myplot <- myplot + opts(title="Plant competition")
myplot <- myplot + opts(legend.position = "none")
myplot <- myplot + opts(panel.grid.minor=theme_blank(), panel.grid.major=theme_blank())
So far it is fine. However, I want to add two different horizontal lines in the two facets. For that, I used this code:
hline.data <- data.frame(z = c(0.511,0.157), species = c("Elytrigia","Festuca"))
myplot <- myplot + geom_hline(aes(yintercept = z), hline.data)
However if I do that, I get a plot were there are two extra facets, where the two horizontal lines are plotted. Instead, I want the horizontal lines to be plotted in the facets with the bars, not to make two new facets. Anyone a idea how to solve this.
I think it makes it clearer if I put the graph I create now:
Make sure that the variable species is identical in both datasets. If it a factor in one on them, then it must be a factor in the other too
library(ggplot2)
dummy1 <- expand.grid(X = factor(c("A", "B")), Y = rnorm(10))
dummy1$D <- rnorm(nrow(dummy1))
dummy2 <- data.frame(X = c("A", "B"), Z = c(1, 0))
ggplot(dummy1, aes(x = D, y = Y)) + geom_point() + facet_grid(~X) +
geom_hline(data = dummy2, aes(yintercept = Z))
dummy2$X <- factor(dummy2$X)
ggplot(dummy1, aes(x = D, y = Y)) + geom_point() + facet_grid(~X) +
geom_hline(data = dummy2, aes(yintercept = Z))