I am wondering if I am able to graph separate lines for 2 variables without using the grid function. I would prefer the 4 lines on one graph than 2 lines in 2 grids. Its ok if I can't but thought I would ask.
My data is as follows:
nd<-data.frame(Machine = c(2,2,3,3,2,2,3,3),
Source = c("tube", "machine","tube", "machine","tube", "machine","tube", "machine"),
Time=c(0,0,0,0,2,2,2,2),
Count=c(224000, 107000, 850000, 940000, 610000,116000, 1160000, 1100000))
and this code gives me what I want with a facet...
ggplot(data=nd, aes(x=Time, y=Count, group=Machine, color=Machine)) +
geom_line(aes(group=Machine))+ geom_point()+facet_grid(~Source)
Is there an alternative to this?
P.S. even though Machine is a factor variable why is my legend showing it as continuous?
One quick way is to use the interaction function, which paste your two variables with a "."
ggplot(data=nd, aes(x=Time, y=Count, color=interaction(Machine,Source))) +
geom_line() + geom_point() +
scale_color_manual("groups",
values=c("#61d4b3","#fdd365","#fb8d62","#fd2eb3"))
Related
I am trying to plot a bar chart in ggplot but I am continuously getting only the grid. This is apparently a demonstration about the draw nothing here but I would like to understand how to get the values visible in the simplest way.
library(ggplot2)
testData<-data.frame(x=c("a","b","c","d","e","f"), y=c(10,6,9,28,10,17))
bar <- ggplot(data=testData, aes(x=c("a","b","c","d","e","f"), y=c(10,6,9,28,10,17), fill = "#FFCC00"))
One way I can get the plots is the geom_bar
bar <- ggplot(data=testData, aes(x=c("a","b","c","d","e","f"), y=c(10,6,9,28,10,17), fill = "#FFCC00")) + geom_bar(stat="identity")
Why are the values not plotted on the first bar chart and how to fix it the simplest way? What is the idea behind of this way of plotting with + and what is it called?
With the ggplot2 package, calling ggplot() is only meant to call the basic grid; it's like taking out a piece of graph paper before drawing a graph. In either case, having the grid ready has nothing to do with plotting the graph. That's why running the following command will result in the empty grid in your first example:
ggplot(data=testData, aes(x=x, y=y, fill = "#FFCC00"))
It's not the same as using a function like plot() or hist(), which prep the grid and plot the data at the same time:
plot(x=x,y=y,data=testData)
hist(x=x,data=testData)
The "+" in ggplot is just a way to say that there are more arguments related to the ggplot that we want included on top of the first blank grid. That's why each line separated by a "+" is typically called a layer.
So, if we want to make a simple scatterplot, we add points on top of a grid:
testData<-data.frame(x=c(1:6), y=c(10,6,9,28,10,17))
ggplot(data=testData,aes(x=x,y=y)) +
geom_point()
Output:
If we want to add lines to that scatterplot, we can just add one line of code:
ggplot(data=testData,aes(x=x,y=y)) +
geom_point() +
geom_line()
Output:
We can keep adding layers like this if we want. Just note that they will print in the order that you type them (i.e. the first few lines will be below the lines printed after them):
ggplot(data=testData,aes(x=x,y=y)) +
geom_bar(stat="identity",fill="#00BFC4") +
geom_point() +
geom_line()
Output:
Also, note that it's recommended not to call your data multiple times within a ggplot call; that can lead to errors.
Don't use:
ggplot(data=testData, aes(x=c("a","b","c","d","e","f"),
y=c(10,6,9,28,10,17), fill = "#FFCC00")) +
geom_bar(stat="identity")
#or
ggplot(data=testData, aes(x=testData$x, y=testData$x, fill = "#FFCC00")) +
geom_bar(stat="identity")
Instead use:
ggplot(data=testData, aes(x=x, y=y, fill="#FFCC00")) +
geom_bar(stat="identity")
If you want to plot data from a data frame(s) not called within the first ggplot() line, then simply add a data argument to the "layers" that use that different data frame, like this:
ggplot(data=testData,aes(x=x,y=y)) +
geom_bar(stat="identity",fill="#00BFC4") +
geom_point(data=differentDf, aes(x=x,y=y)) +
geom_line(data=differentDf, aes(x=x,y=y))
Using ggplot2 I have made facetted histograms using the following code.
library(ggplot2)
library(plyr)
df1 <- data.frame(monthNo = rep(month.abb[1:5],20),
classifier = c(rep("a",50),rep("b",50)),
values = c(seq(1,10,length.out=50),seq(11,20,length.out=50))
)
means <- ddply (df1,
c(.(monthNo),.(classifier)),
summarize,
Mean=mean(values)
)
ggplot(df1,
aes(x=values, colour=as.factor(classifier))) +
geom_histogram() +
facet_wrap(~monthNo,ncol=1) +
geom_vline(data=means, aes(xintercept=Mean, colour=as.factor(classifier)),
linetype="dashed", size=1)
The vertical line showing means per month is to stay.
But I want to also add text over these vertical lines displaying the mean values for each month. These means are from the 'means' data frame.
I have looked at geom_text and I can add text to plots. But it appears my circumstance is a little different and not so easy. It's a lot simpler to add text in some cases where you just add values of the plotted data points. But cases like this when you want to add the mean and not the value of the histograms I just can't find the solution.
Please help. Thanks.
Having noted the possible duplicate (another answer of mine), the solution here might not be as (initially/intuitively) obvious. You can do what you need if you split the geom_text call into two (for each classifier):
ggplot(df1, aes(x=values, fill=as.factor(classifier))) +
geom_histogram() +
facet_wrap(~monthNo, ncol=1) +
geom_vline(data=means, aes(xintercept=Mean, colour=as.factor(classifier)),
linetype="dashed", size=1) +
geom_text(y=0.5, aes(x=Mean, label=Mean),
data=means[means$classifier=="a",]) +
geom_text(y=0.5, aes(x=Mean, label=Mean),
data=means[means$classifier=="b",])
I'm assuming you can format the numbers to the appropriate precision and place them on the y-axis where you need to with this code.
I want to group the bars in a stacked barplot according to the values in another factor-variable. However, I want to do this without using facets.
my data in long format
I want to group the stacked bars according the afk variable. The normal stacked bar plot can be made with:
ggplot(nl.melt, aes(x=naam, y=perc, fill=stemmen)) +
geom_bar(stat="identity", width=.7) +
scale_x_discrete(expand=c(0,0)) +
scale_y_continuous(expand=c(0,0)) +
coord_flip() +
theme_bw()
which gives an alfabetically ordered barplot:
I tried to group them by using x=reorder(naam,afk) in the aes. But that didn't work. Also using group=afk does not have the desired effect.
Any ideas how to do this?
reorder should work but the problem is you're trying to re-order by a factor. You need to be explicit on how you want to use that information. You can either use
nl.melt$naam <- reorder(nl.melt$naam, as.numeric(nl.melt$afk))
or
nl.melt$naam <- reorder(nl.melt$naam, as.character(nl.melt$afk), FUN=min)
depending on whether you want to sort by the existing levels of afk or if you want to sort alphabetically by the levels of afk.
After running that and re-running the ggplot code, i get
An alternative to #MrFlick's approach (based on the answer #CarlosCinelli linked to) is:
ggplot(nl.melt, aes(x=interaction(naam,afk), y=perc, fill=stemmen)) +
geom_bar(stat="identity", width=.7) +
scale_x_discrete(expand=c(0,0)) +
scale_y_continuous(expand=c(0,0)) +
coord_flip() +
theme_bw()
which gives:
R tends to see the order of levels as a property of the data rather than a property of the graph. Try reordering the data itself before calling the plotting commands. Try running:
nl.melt$naam <- reorder(nl.melt$naam, nl.melt$afk)
Then run your ggplot code. Or use other ways of reordering your factor levels in naam.
In the data that I am attempting to plot, each sample belongs in one of several groups, that will be plotted on their own grids. I am plotting stacked bar plots for each sample that will be ordered in increasing number of sequences, which is an id attribute of each sample.
Currently, the plot (with some random data) looks like this:
(Since I don't have the required 10 rep for images, I am linking it here)
There are couple things I need to accomplish. And I don't know where to start.
I would like the bars not to be placed at its corresponding nseqs value, rather placed next to each other in ascending nseqs order.
I don't want each grid to have the same scale. Everything needs to fit snugly.
I have tried to set scales and size to for facet_grid to free_x, but this results in an unused argument error. I think this is related to the fact that I have not been able to get the scales library loaded properly (it keeps saying not available).
Code that deals with plotting:
ggfdata <- melt(fdata, id.var=c('group','nseqs','sample'))
p <- ggplot(ggfdata, aes(x=nseqs, y=value, fill = variable)) +
geom_bar(stat='identity') +
facet_grid(~group) +
scale_y_continuous() +
opts(title=paste('Taxonomic Distribution - grouped by',colnames(meta.frame)[i]))
Try this:
update.packages()
## I'm assuming your ggplot2 is out of date because you use opts()
## If the scales library is unavailable, you might need to update R
ggfdata <- melt(fdata, id.var=c('group','nseqs','sample'))
ggfdata$nseqs <- factor(ggfdata$nseqs)
## Making nseqs a factor will stop ggplot from treating it as a numeric,
## which sounds like what you want
p <- ggplot(ggfdata, aes(x=nseqs, y=value, fill = variable)) +
geom_bar(stat='identity') +
facet_wrap(~group, scales="free_x") + ## No need for facet_grid with only one variable
labs(title = paste('Taxonomic Distribution - grouped by',colnames(meta.frame)[i]))
Summary: I want to choose the colors for a ggplot2() density distribution plot without losing the automatically generated legend.
Details: I have a dataframe created with the following code (I realize it is not elegant but I am only learning R):
cands<-scan("human.i.cands.degnums")
non<-scan("human.i.non.degnums")
df<-data.frame(grp=factor(c(rep("1. Candidates", each=length(cands)),
rep("2. NonCands",each=length(non)))), val=c(cands,non))
I then plot their density distribution like so:
library(ggplot2)
ggplot(df, aes(x=val,color=grp)) + geom_density()
This produces the following output:
I would like to choose the colors the lines appear in and cannot for the life of me figure out how. I have read various other posts on the site but to no avail. The most relevant are:
Changing color of density plots in ggplot2
Overlapped density plots in ggplot2
After searching around for a while I have tried:
## This one gives an error
ggplot(df, aes(x=val,colour=c("red","blue"))) + geom_density()
Error: Aesthetics must either be length one, or the same length as the dataProblems:c("red", "blue")
## This one produces a single, black line
ggplot(df, aes(x=val),colour=c("red","green")) + geom_density()
The best I've come up with is this:
ggplot() + geom_density(aes(x=cands),colour="blue") + geom_density(aes(x=non),colour="red")
As you can see in the image above, that last command correctly changes the colors of the lines but it removes the legend. I like ggplot2's legend system. It is nice and simple, I don't want to have to fiddle about with recreating something that ggplot is clearly capable of doing. On top of which, the syntax is very very ugly. My actual data frame consists of 7 different groups of data. I cannot believe that writing + geom_density(aes(x=FOO),colour="BAR") 7 times is the most elegant way of coding this.
So, if all else fails I will accept with an answer that tells me how to get the legend back on to the 2nd plot. However, if someone can tell me how to do it properly I will be very happy.
set.seed(45)
df <- data.frame(x=c(rnorm(100), rnorm(100, mean=2, sd=2)), grp=rep(1:2, each=100))
ggplot(data = df, aes(x=x, color=factor(grp))) + geom_density() +
scale_color_brewer(palette = "Set1")
ggplot(data = df, aes(x=x, color=factor(grp))) + geom_density() +
scale_color_brewer(palette = "Set3")
gives me same plots with different sets of colors.
Provide vector containing colours for the "values" argument to map discrete values to manually chosen visual ones:
ggplot(df, aes(x=val,color=grp)) +
geom_density() +
scale_color_manual(values=c("red", "blue"))
To choose any colour you wish, enter the hex code for it instead:
ggplot(df, aes(x=val,color=grp)) +
geom_density() +
scale_color_manual(values=c("#f5d142", "#2bd63f")) # yellow/green