I've been trying to plot two histograms by using the fill aesthetic and a specific column with two levels. However, instead of displaying both desired histograms, my code displays one histogram with the whole data and another only for the second classification. I don't know if there is a problem in my syntax neither if this is some kind of tricky issue.
library(tidyverse)
db1 <- data.frame(type=rep("A",100),val=rnorm(n=100,mean=50,sd=10))
db2 <- data.frame(type=rep("B",150),val=rnorm(n=150,mean=50,sd=10))
dbf <- bind_rows(db1,db2)
P1 <- ggplot(db1, aes(x=val)) + geom_histogram()
P2 <- ggplot(db2, aes(x=val)) + geom_histogram()
PF <- ggplot(dbf, aes(x=val)) + geom_histogram()
I want to get this, P1 and P2
ggplot(db1, aes(x=val)) + geom_histogram(fill="red", alpha=0.5) + geom_histogram(data=db2, aes(x=val),fill="green", alpha=0.5)
What I want
But the code I think should work, P1 and P2 with the fill aesthetic for column val
ggplot(dbf, aes(x=val)) + geom_histogram(aes(fill=type), alpha=0.5)
My code
Produces the combination of PF and P2
ggplot(dbf, aes(x=val)) + geom_histogram(fill="red", alpha=0.5) + geom_histogram(data=db2, aes(x=val),fill="green", alpha=0.5)
What I get
Any help or idea will be highly appreciated!
All you need is to pass position = "identity" to your geom_histogram function.
library(tidyverse)
library(ggplot2)
db1 <- data.frame(type=rep("A",100),val=rnorm(n=100,mean=50,sd=10))
db2 <- data.frame(type=rep("B",150),val=rnorm(n=150,mean=50,sd=10))
dbf <- bind_rows(db1,db2)
ggplot(dbf, aes(x=val, fill = type)) + geom_histogram(alpha=0.5, position = "identity")
Is your goal to show the overlap via the color combination? I'm not sure how to force geom_histogram to show the overlap, but geom_density does do what you want. You can play with the bandwidth (bw) to show more or less detail.
dbf %>% ggplot() +
aes(x = val, fill = type) +
geom_density(alpha = .5, bw = .5) +
scale_fill_manual(values = c("red","green"))
Related
I am trying to make an extremely single heatmap of percentages using ggplot2 which ideally will just be two single thin columns. I tried the following code, believing that the width option in aes would solve the problem.
p_prev_tg <- ggplot(tg_melt, aes(x = variable , y = OTU, fill = value,
width=.3)) + geom_tile() +
scale_fill_gradientn(colours = hm.palette2(10)) +
xlab(NULL) + ylab(NULL) +
theme(axis.text=element_text(size=7))
p_prev_tg
Unfortunately, this returns a plot with lots of empty space as shown. The plot I would like is those two bars side by side, how can I do this in ggplot?
thanks
What about this solution ?
set.seed(1234)
tg_melt <- data.frame(variable=rep(c("Prevalence_T","Prevalence_NT"), each=10),
OTU=rep(paste0("OTU_",1:10),2),
value=rnorm(20))
library(RColorBrewer)
library(ggplot2)
hm.palette2 <- colorRampPalette(rev(brewer.pal(11, 'Spectral')))
p_prev_tg <- ggplot(tg_melt, aes(x = as.numeric(variable), y = OTU, fill = value)) +
geom_tile() +
scale_fill_gradientn(colours = hm.palette2(10)) +
xlab(NULL) + ylab(NULL) +
theme(axis.text=element_text(size=7)) +
scale_x_continuous(breaks=c(1,2),
limits=c(0,3),
labels=levels(tg_melt$variable))+
theme_bw()
p_prev_tg
I have the following code in R which is modified from here, which plots a crosstab table:
#load ggplot2
library(ggplot2)
# Set up the vectors
xaxis <- c("A", "B")
yaxis <- c("A","B")
# Create the data frame
df <- expand.grid(xaxis, yaxis)
df$value <- c(120,5,30,200)
#Plot the Data
g <- <- ggplot(df, aes(Var1, Var2)) + geom_point(aes(size = value), colour = "lightblue") + theme_bw() + xlab("") + ylab("")
g + scale_size_continuous(range=c(10,30)) + geom_text(aes(label = value))
It produces the right figure, which is great, but I was hoping to custom colour the four dots, ideally so that the top left and bottom right are both one colour and the top right and bottom left are another.
I have tried to use:
+ scale_color_manual(values=c("blue","red","blue","red"))
but that doesn't seem to work. Any ideas?
I would suggest that you colour by a vector in your data frame, as you don't have a column that gives you this, you can either create one, or make a rule based on existing columns (which I have done below):
g <- ggplot(df, aes(Var1, Var2)) + geom_point(aes(size = value, colour = (Var2!=Var1))) + theme_bw() + xlab("") + ylab("")
g + scale_size_continuous(range=c(10,30)) + geom_text(aes(label = value))
The important part is: colour = (Var2!=Var1), note that i put this inside the aesthetic (aes) for the geom_point
Edit: if you wish to remove the legend (you annotate the chart with totals, so I guess you don't really need it), you can add: g + theme(legend.position="none") to remove it
I have been struggling in creating a decent looking scatterplot in R. I wouldn't think it was so difficult.
After some research, it seemed to me that ggplot would have been a choice allowing plenty of formatting. However, I'm struggling in understanding how it works.
I'd like to create a scatterplot of two data series, displaying the points with two different colours, and perhaps different shapes, and a legend with series names.
Here is my attempt, based on this:
year1 <- mpg[which(mpg$year==1999),]
year2 <- mpg[which(mpg$year==2008),]
ggplot() +
geom_point(data = year1, aes(x=cty,y=hwy,color="yellow")) +
geom_point(data = year2, aes(x=cty,y=hwy,color="green")) +
xlab('cty') +
ylab('hwy')
Now, this looks almost OK, but with non-matching colors (unless I suddenly became color-blind). Why is that?
Also, how can I add series names and change symbol shapes?
Don't build 2 different dataframes:
df <- mpg[which(mpg$year%in%c(1999,2008)),]
df$year<-as.factor(df$year)
ggplot() +
geom_point(data = df, aes(x=cty,y=hwy,color=year,shape=year)) +
xlab('cty') +
ylab('hwy')+
scale_color_manual(values=c("green","yellow"))+
scale_shape_manual(values=c(2,8))+
guides(colour = guide_legend("Year"),
shape = guide_legend("Year"))
This will work with the way you currently have it set-up:
ggplot() +
geom_point(data = year1, aes(x=cty,y=hwy), col = "yellow", shape=1) +
geom_point(data = year2, aes(x=cty,y=hwy), col="green", shape=2) +
xlab('cty') +
ylab('hwy')
You want:
library(ggplot2)
ggplot(mpg, aes(cty, hwy, color=as.factor(year)))+geom_point()
I have two dataframes: dataf1, dataf2. They have the same structure and columns.
3 columns names are A,B,C. And they both have 50 rows.
I would like to plot the histogram of column B on dataf1 and dataf2. I can plot two histograms separately but they are not of the same scale. I would like to know how to either put them on the same histogram using different colors or plot two histograms of the same scale?
ggplot() + aes(dataf1$B)+ geom_histogram(binwidth=1, colour="black",fill="white")
ggplot() + aes(dataf2$B)+ geom_histogram(binwidth=1, colour="black", fill="white")
Combine your data into a single data frame with a new column marking which data frame the data originally came from. Then use that new column for the fill aesthetic for your plot.
data1$source="Data 1"
data2$source="Data 2"
dat_combined = rbind(data1, data2)
You haven't provided sample data, so here are a few examples of possible plots, using the built-in iris data frame. In the plots below, dat is analogous to dat_combined, Petal.Width is analogous to B, and Species is analogous to source.
dat = subset(iris, Species != "setosa") # We want just two species
ggplot(dat, aes(Petal.Width, fill=Species)) +
geom_histogram(position="identity", colour="grey40", alpha=0.5, binwidth=0.1)
ggplot(dat, aes(Petal.Width, fill=Species)) +
geom_histogram(position="dodge", binwidth=0.1)
ggplot(dat, aes(Petal.Width, fill=Species)) +
geom_histogram(position="identity", colour="grey40", binwidth=0.1) +
facet_grid(Species ~ .)
As Zheyuan says, you just need to set the y limits for each plot to get them on the same scale. With ggplot2, one way to do this is with the lims command (though scale_y_continuous and coord_cartesian also work, albeit slightly differently). You also should never use data$column indside aes(). Instead, use the data argument for the data frame and unquoted column names inside aes(). Here's an example with some built-in data.
p1 = ggplot(mtcars, aes(x = mpg)) + geom_histogram() + lims(y = c(0, 13))
p2 = ggplot(iris, aes(x = Sepal.Length)) + geom_histogram() + lims(y = c(0, 13))
gridExtra::grid.arrange(p1, p2, nrow = 1)
Two get two histograms on the same plot, the best way is to combine your data frames. A guess, without seeing what your data looks like:
dataf = rbind(dataf1["B"], dataf2["B"])
dafaf$source = c(rep("f1", nrow(dataf1)), rep("f2", nrow(dataf2))
ggplot(dataf, aes(x = B, fill = source)) +
geom_histogram(position = "identity", alpha = 0.7)
status = sample(c(0, 1), 500, replace = TRUE)
value = rnorm(500)
plot(value)
smoothScatter(value)
I'm trying to make a scatterplot of value, but if I were to just plot it, the data is all clumped together and it's not very presentable. I've tried smoothScatter(), which makes the plot look a bit nicer, but I am wondering if there's a way to color code the values based on the corresponding status?
I am trying to see if there's a relationship between status and value. What's another way to present the data nicely? I've tried boxplot, but I'm wondering how I can make the smoothScatter() plot better or if there are other ways to visualize it.
I'm assuming you meant to write plot(status, value) in your example? Regardless, there's not going to be much difference using this data, but you should get the idea of things to maybe look at with the following examples...
Have you looked into jitter?
Some basics:
plot(jitter(status), value)
or perhaps plot(jitter(status, 0.5), value)
Fancier with package ggplot2 you could do:
library(ggplot2)
df <- data.frame(value, status)
ggplot(data=df, aes(jitter(status, 0.10), value)) +
geom_point(alpha = 0.5)
or this...
ggplot(data=df, aes(factor(status), value)) +
geom_violin()
or...
ggplot(data=df, aes(x=status, y=value)) +
geom_density2d() +
scale_x_continuous(limits=c(-1,2))
or...
ggplot(data=df, aes(x=status, y=value)) +
geom_density2d() +
stat_density2d(geom="tile", aes(fill = ..density..), contour=FALSE) +
scale_x_continuous(limits=c(-1,2))
or even this..
ggplot(data=df, aes(fill=factor(status), value)) +
geom_density(alpha=0.2)