I have a dataset, named “data”:
df=ddply(data,c("Treatment","Concentration"),summarise,mean=mean(Inhibition),sd=sd(Inhibition),n=length(Inhibition),se=sd/sqrt(n))
p <- ggplot(df, aes(x=Treatment, y=Inhibition))
p1 <- p + geom_bar(stat="identity", position="dodge") +
geom_errorbar(aes(ymin=Inhibition-se,ymax=Inhibition+se), position="dodge",width=0.2)
and I got the following graph:
I want x-axis to be like the picture below:
How woud I do this??
This is best achieved using a facet within ggplot. As you haven’t included a reusable dataset, I have made one here:
df <- data.frame(Group = c("A", "A", "A", "A", "B"),
SubGroup = c(letters[1:5]),
value = 1:5
)
See below the facet_grid line which has a few additional options specified. You can read more about the added arguments here
library(ggplot2)
ggplot(df, aes(x = SubGroup, value)) +
geom_bar(stat="identity", position="dodge") +
facet_grid(.~Group, scales = "free_x", space = "free", switch = "x") +
theme(strip.placement = "outside")
For your data, you will need to split the drug and dose into two separate columns first, like my example.
Related
I'm new to R and I'm trying to create a single plot with data from 2 melted dataframes.
Ideally I would have a legend for each of the dataframes with their respective titles; however, I get a only a single legend with the title of the first aesthetic.
My starting point is:
aerobic_melt <- melt(aerobic, id.vars = 'Distance', variable.name = 'Aerobic')
anaerobic_melt <- melt(anaerobic, id.vars = 'Distance', variable.name = 'Anaerobic')
plot <- ggplot() +
geom_line(data = aerobic_melt, aes(Distance, value, col=Aerobic)) +
geom_line(data = anaerobic_melt, aes(Distance, value, col= Anaerobic)) +
xlim(0, 125) +
ylab('Energy (J/kg )') +
xlab('Distance (m)')
Which results in
I've searched, but with my limited ability I haven't been able to find a way to do it.
My question is:
How do I create separate legends with titles 'Aerobic' and 'Anaerobic' which should respectively refer to A,B,C,F,G,L and E,H,I,J,K?
Any help is appreciated.
Obviously we don't have your data, but I have created some sample data that should have the same names and structure as your own data frames, since it works with your own plot code. See the end of the answer for the data used here.
You can use the package ggnewscale if you want two color scales on the same plot. Just add in a new_scale_color() call between your geom_line calls. I have left the rest of your code as-is.
library(ggplot2)
library(ggnewscale)
plot <- ggplot() +
geom_line(data = aerobic_melt, aes(Distance, value, col=Aerobic)) +
new_scale_color() +
geom_line(data = anaerobic_melt, aes(Distance, value, col= Anaerobic)) +
xlim(0, 125) +
ylab('Energy (J/kg )') +
xlab('Distance (m)')
plot
Data
set.seed(1)
aerobic_melt <- data.frame(
Aerobic = rep(c("A", "B", "C", "F", "G", "L"), each = 120),
value = as.numeric(replicate(6, cumsum(rnorm(120)))),
Distance = rep(1:120, 6))
anaerobic_melt <- data.frame(
Anaerobic = rep(c("E", "H", "I", "J", "K"), each = 120),
value = as.numeric(replicate(5, cumsum(rnorm(120)))),
Distance = rep(1:120, 5))
Let's say, I have data like following example,
dat1 <- data.frame(group = c("a", "a","a", "a", "a", "b", "b", "b","b","b","b","b","c","c","c"),
subgroup = c(paste0("R", rep(1:5)),paste0("R", rep(1:7)),paste0("R", rep(1:3))),
value = c(5,6,0,8,2,3,4,5,2,4,7,0,3,4,0),
pp = c("AT","BT","CT","AA","AT","TT","RT","CC","SE","DN","AA","MM","XT","QQ","HH"))
And, I want to add some cut off as dat1 = dat1[dat1$value > 2, ]. My code
pl <- ggplot(dat1, aes(y = as.character(pp), x = as.factor(subgroup))) +
geom_point( aes(size=as.numeric(value)))+ facet_grid(cols = vars(group), scales="free", space="free")+
ylab("names") +xlab(" ")
pl
enter image description here
But I want to see all scale in each panel. For example in the first panel, there are five values or five scales even if below of cut off or zero I just want to see all five scale. The second panel has 7 scales but after cut off, there should be 6 columns, but I want to see all 7 scales even if it has zero.
How can I modify my code or make as this kind of plot?
We can use the scales and space arguments in facet_grid.
ggplot(dat1, aes(subgroup, pp)) +
geom_point(aes(size = value)) +
facet_grid(cols = vars(group), scales = "free", space = "free")
I have a data-frame 'x'
I want barplot like this
I tried
barplot(x$Value, names.arg = x$'Categorical variable')
ggplot(as.data.frame(x$Value), aes(x$'Categorical variable')
Nothing seems to work properly. In barplot, all axis labels (freq values) are different. ggplot is filling all bars to 100%.
You can try plotting using geom_bar(). Following code generates what you are looking for.
df = data.frame(X = c("A","B C","D"),Y = c(23,12,43))
ggplot(df,aes(x=X,y=Y)) + geom_bar(stat='identity') + coord_flip()
It helps to read the ggplot documentation. ggplot requires a few things, including data and aes(). You've got both of those statements there but you're not using them correctly.
library(ggplot2)
set.seed(256)
dat <-
data.frame(variable = c("a", "b", "c"),
value = rnorm(3, 10))
dat %>%
ggplot(aes(x = variable, y = value)) +
geom_bar(stat = "identity", fill = "blue") +
coord_flip()
Here, I'm piping my dat to ggplot as the data argument and using the names of the x and y variables rather than passing a data$... value. Next, I add the geom_bar() statement and I have to use stat = "identity" to tell ggplot to use the actual values in my value rather than trying to plot the count of the number.
You have to use stat = "identity" in geom_bar().
dat <- data.frame("cat" = c("A", "BC", "D"),
"val" = c(23, 12, 43))
ggplot(dat, aes(as.factor(cat), val)) +
geom_bar(stat = "identity") +
coord_flip()
I want to know if it's feasible to create a bar chart with groupings by type in ggplot the same way I would in excel. I have the following data:
df <- data.frame(label = c("A", "A", "B", "C"), variable = c("alpha", "beta", "tim", "tom"), values = c(1,2,4,1))
In excel, I can easily create a graph that looks like this:
Is there a way to do something similar in ggplot, where the column 'label' groups the variables?
You can use facet_grid and set the scales = "free_x" and space = "free".
ggplot(df, aes(variable, values)) + geom_bar(stat = "identity") + facet_grid(~ label, scales = "free_x", space = "free")
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))