I'm producing a stacked bar plot with purple and yellow but the two colours won't show up. Here is my code:
ggplot(df_group, aes(x = COLOUR, y =COUNT, fill = GROUP,label=GROUP)) +
geom_bar(position="stack", stat = "identity") +
scale_fill_manual("Flower Colour", values = c("Purple" = "mediumpurple", "Yellow" = "Gold")) +
labs(x='Group', y="Visits")
What do I need to change?
I suspect that your code could not have created that plot. Your aesthetics are swapped around. Try this:
df <- data.frame(
COUNT = runif(n = 20, min = 0, max = 10),
GROUP = sample(c("bee", "beetle", "butterfly"), 20, replace = TRUE),
COLOUR = sample(c("Purple", "Yellow"), 20, replace = TRUE))
ggplot(df, aes(x = GROUP, y = COUNT, fill = COLOUR)) +
geom_bar(position = "stack", stat = "identity") +
scale_fill_manual("Flower Colour", values = c("Purple" = "mediumpurple", "Yellow" = "Gold")) +
labs(x='Group', y="Visits")
Related
Im making a scatterplot which shows a value plotted against the date since symptom onset. These patients are categorised based on disease severity, and i wanted to show how the values change over time in each severity category. I have coloured the dots based on severity score, but i prefer to use shape =21 so i can have a border. I also draw a line to see the trend, and i want that coloured in the same way, however, this has added another legend and it looks complicated. This issue doesnt happen if use a different shape that isnt filled, because scale_colour_manual can be used for both the lines and the dots, but i dont think it looks as nice. Any idea how i can fix this?
IC50SymObySS <- ggplot(data = isaric) +
geom_point(mapping = aes(x = Days_since_onset, y = log2IC50, fill = Severity_score), size = 2, colour = "black", shape = 21)+
geom_smooth(mapping = aes(x = Days_since_onset, y = log2IC50, colour = Severity_score), se = FALSE)+
scale_fill_manual(breaks=c("1","2","3","4","5"),
values=c("1" = "lightblue1","2" = "lightblue3","3" = "lightblue4","4" = "lightcoral","5" = "firebrick2"),
labels=c("1","2","3","4","5"),
name = "Severity Score")+
scale_colour_manual(values=c("1" = "lightblue1","2" = "lightblue3","3" = "lightblue4","4" = "lightcoral","5" = "firebrick2"))+
theme_minimal()+
JTheme+
ylab("Serum Log2 IC50")+
xlab("Days Since Symptom Onset")+
guides(colour = guide_legend(title.position = "top", title.hjust = 0.5))
IC50SymObySS
As per this answer, you need to use identical name and labels values for both fill and colour scale.
library(ggplot2)
library(dplyr)
isaric <- transmute(iris,
Days_since_onset = (Sepal.Length - 4)^3,
log2IC50 = Sepal.Width * 3,
Severity_score = cut(Petal.Length, breaks = quantile(Petal.Length, prob = 0:5 / 5), labels = 1:5))
ggplot(data = isaric) +
geom_smooth(mapping = aes(x = Days_since_onset, y = log2IC50, colour = Severity_score), se = FALSE)+
geom_point(mapping = aes(x = Days_since_onset, y = log2IC50, fill = Severity_score), size = 2, colour = "black", shape = 21)+
scale_colour_manual(
name = "Severity Score",
values=c("1" = "lightblue1","2" = "lightblue3","3" = "lightblue4","4" = "lightcoral","5" = "firebrick2"),
labels=c("1","2","3","4","5"))+
scale_fill_manual(
name = "Severity Score",
breaks=c("1","2","3","4","5"),
values=c("1" = "lightblue1","2" = "lightblue3","3" = "lightblue4","4" = "lightcoral","5" = "firebrick2"),
labels=c("1","2","3","4","5"))+
theme_minimal()+
ylab("Serum Log2 IC50")+
xlab("Days Since Symptom Onset")+
guides(colour = guide_legend(title.position = "top", title.hjust = 0.5))
I am creating a stacked bar chart below using ggplot and I convert it to interactive using ggplotly(). As you can see in the screenshot below the pop up text when I hover over a bar shows as "Name" the correct "Name" of the relative bar-in that case- DCH. I tried to replace that with a name of my choice but then the whole chart breaks down. So basically I would like to know if I can use "Name" in the background in order to display the chart but display another Name instead. The same for all of the 5 bars.
The code chunk which is related with this is:
geom_col(mapping = aes(x = Name, y = count, fill = Class), width = rep(0.9,5),
color = "black", position = position_fill(reverse = T)) +
geom_text(size = 4, position = position_fill(reverse = T, vjust = 0.50), color = "black",
mapping = aes(x = Name, y = count, group = Class, label = round(count))) +
#DATA
Name<-c("DCH","DCH","DCH","DGI","DGI","DGI","LDP","LDP","LDP","RH","RH","RH","TC","TC","TC")
Class<-c("Class1","Class2","Overlap","Class1","Class2","Overlap","Class1","Class2","Overlap","Class1","Class2","Overlap","Class1","Class2","Overlap")
count<-c(2077,1642,460,1971,5708,566,2316,810,221,2124,3601,413,2160,1097,377)
FinalDF<-data.frame(Name, Class,count)
#PLOT
ggplotly(ggplot(data = FinalDF) +
geom_col(mapping = aes(x = Name, y = count, fill = Class), width = rep(0.9,5),
color = "black", position = position_fill(reverse = T)) +
geom_text(size = 4, position = position_fill(reverse = T, vjust = 0.50), color = "black",
mapping = aes(x = Name, y = count, group = Class, label = round(count))) +
annotate('text', size = 5, x = (5+1)/2, y = -0.1, label = c('A'), angle = 90) +
coord_flip() +
scale_fill_manual(values = c('lemonchiffon', 'palegreen3', 'deepskyblue2'),breaks=c("Class1", "Overlap", "Class2"), labels = c(paste("Unique to","DB"), "Overlap", "Unique to Comparison Dataset "),
guide = guide_legend(label.position = 'left', label.hjust = 0, label.vjust = 0.5)) )
The tooltip argument might be in the right direction.
library(sf)
library(plotly)
# Create the stacked bar plot using ggplot()
stackedBarPlot<- ggplot(data = FinalDF) +
geom_col(mapping = aes(x = Name, y = count, fill = Class), width = rep(0.9,5),
color = "black", position = position_fill(reverse = T)) +
geom_text(size = 4, position = position_fill(reverse = T, vjust = 0.50), color = "black",
mapping = aes(x = Name, y = count, group = Class, label = round(count))) +
annotate('text', size = 5, x = (5+1)/2, y = -0.1, label = c('A'), angle = 90) +
coord_flip() +
scale_fill_manual(values = c('lemonchiffon', 'palegreen3', 'deepskyblue2'),breaks=c("Class1", "Overlap", "Class2"), labels = c(paste("Unique to","DB"), "Overlap", "Unique to Comparison Dataset "),
guide = guide_legend(label.position = 'left', label.hjust = 0, label.vjust = 0.5))+
geom_sf(aes(fill=Class,text=paste(Name,"DB")))
stackedBarPlot%>%
ggplotly(tooltip = "text")
In this SO answer, user #Crops shows how to add a legend to a ggalt::geom_dumbbell plot. Very nice.
library(ggalt)
df <- data.frame(trt=LETTERS[1:5], l=c(20, 40, 10, 30, 50), r=c(70, 50, 30, 60, 80))
df2 = tidyr::gather(df, group, value, -trt)
ggplot(df, aes(y = trt)) +
geom_point(data = df2, aes(x = value, color = group), size = 3) +
geom_dumbbell(aes(x = l, xend = r), size=3, color="#e3e2e1",
colour_x = "red", colour_xend = "blue",
dot_guide=TRUE, dot_guide_size=0.25) +
theme_bw() +
scale_color_manual(name = "", values = c("red", "blue") )
I want to sort trt descending on r. I tried replacing y = trt with y = reorder(trt, r), but I get an error that object r is not found.
Here is a way where we reorder the factor levels of trt in df and df2 before we plot.
# reorder factor levels
df$trt <- reorder(df$trt, df$r)
df2$trt <- factor(df2$trt, levels = levels(df$trt))
ggplot(df, aes(y = trt)) +
geom_point(data = df2, aes(x = value, color = group), size = 3) +
geom_dumbbell(aes(x = l, xend = r), size=3, color="#e3e2e1",
colour_x = "red", colour_xend = "blue",
dot_guide=TRUE, dot_guide_size=0.25) +
theme_bw() +
scale_color_manual(name = "", values = c("red", "blue") )
Using the dumbbell package
##Reformat data
df3<-df %>% arrange(r)
df2<-df%>% mutate("key"="trt")
df2$trt<-factor(df2$trt,df3$trt)
##plot
dumbbell::dumbbell(df2, id="trt", column1="l", column2="r",key="key", delt =1, textsize=3, lab1 = "l", lab2="r", pt_val = 1, pointsize = 3,pt_alpha = 0.6, arrow=1, leg = "Add legend title", pval=2) + xlim(8,85) + facet_wrap(key ~.)
Added in some bells and whistles, you can remove them toggling with the options.
I dont have enough points to embed for here is the link. Hope someone finds it useful.
I am using scale_fill_gradient2() and the colourbar that is created is showing decimal places. I tried to reproduce the text that shows decimals but could not but the text below is in scientific notations.
How can you round the numbers that displayed in the colourbar using scale_fill_gradient2()? For example I am seeing "25.00" and I'd like to show just "25"?
Also how can you set the labels manually? Let's say I want to look a the data and set labels like c(15, 25, 40)?
library(ggplot2)
dat <- data.frame(group = c(rep("A", 10), rep("B", 10)),
value = c(rnorm(10, 5,300), rnorm(10, 5000, 80000)))
ggplot(dat, aes(x = group, y = value, fill= value)) +
geom_bar(stat = "identity") +
scale_fill_gradient2(low = "red", mid = "yellow", high = "blue", midpoint = 0, name = "")
You can manually specify breaks and labels as needed.
ggplot(dat, aes(x = group, y = value, fill= value)) +
geom_bar(stat = "identity")+
scale_fill_gradient2(low = "red", mid = "yellow", high = "blue",
midpoint = 0, name = "",
breaks = c(0, 1e5, 2e5),
labels = c("0", "100,000", "200,000"))
I have seen lots of question regarding converting count on y axis into percent but must of them are in bar plot.
I want to do similar thing in histogram but not able to show the labels on the bar clearly. Please tell me where I am doing wrong.
x = runif(100, min = 0, max = 10)
data1 <- data.frame(x = x)
ggplot(aes(x = x), data = data1)+
geom_histogram(aes(y = (..count..)/sum(..count..)), bins = 10, breaks =
seq(0,10,1), fill = "blue", col = "black")+
geom_text(aes(y = ((..count..)/sum(..count..)),
label = scales::percent((..count..)/sum(..count..))),
stat = "count", vjust = -10)+
scale_y_continuous(labels = scales::percent)
Output:
Use scale_y_continous with breaks and labels will solve your problem.
data1 <- data.frame (x = runif(100, min = 0, max = 10))
ggplot(aes(x=x), data1) + stat_bin(aes(y = ..count..))
ggplot(data1, aes(x = x)) + geom_histogram(fill = "blue", col = "black")+ scale_y_continuous(breaks = seq(0,10,1),labels = paste(seq(0, 10, by = 1) / 100, "%", sep = ""))+geom_text(aes(y = (..count..),label = scales::percent((..count..)/sum(..count..))), stat="bin",colour="green",vjust=2)
or, you can specify where you would like to add the percentage like this:
geom_text(aes(y = (..count..)+0.5))
of course you can change the color as well. from,
stat="bin",colour="your prefer color "
Also you can change the width of the bins as follows:
geom_histogram(fill = "blue", col = "black", binwidth = 0.5)