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I want to create a box plot + line plot in a single plot using ggplot2
This is what my code now:
library(ggplot2)
dat <- data.frame(day = c(0,0,0,0,0,0,10,10,10,10,10,10,14,14,14,14,14,14,21,21,21,21,21,21,28,28,28,28,28,28,35,35,35,35,35,35,42,42,42,42,42,42), group = c('Saline','RP','Saline','Saline','RP','RP','Saline','RP','Saline','Saline','RP','RP','Saline','RP','Saline','Saline','RP','RP','Saline','RP','Saline','Saline','RP','RP','Saline','RP','Saline','Saline','RP','RP','Saline','RP','Saline','Saline','RP','RP','Saline','RP','Saline','Saline','RP','RP'), score = c(37.5,43,7,63,26,15,17,16,43,26,53,26,26,26,43,10,6,15,18,9,10,4,8,18,60,26,20,12.5,9,43,43,43,11,10,7,60,43,43,32,10.5,8,57.5))
g1 = ggplot(data = dat, aes(x = factor(day), y = score)) +
geom_boxplot(aes(fill = group))
g1
When doing box plot, I want scores of different treatments(groups) to be represented separately, so I let x = factor(day).
But for line plot, I want each day's score to be the average of the two treatments(group) of the day.
This is how my plot look like now
This is how I want my plot to look
How can I do this? Thank you so much!
#Libraries
library(tidyverse)
#Data
dat <- data.frame(day = c(0,0,0,0,0,0,10,10,10,10,10,10,14,14,14,14,14,14,21,21,21,21,21,21,28,28,28,28,28,28,35,35,35,35,35,35,42,42,42,42,42,42), group = c('Saline','RP','Saline','Saline','RP','RP','Saline','RP','Saline','Saline','RP','RP','Saline','RP','Saline','Saline','RP','RP','Saline','RP','Saline','Saline','RP','RP','Saline','RP','Saline','Saline','RP','RP','Saline','RP','Saline','Saline','RP','RP','Saline','RP','Saline','Saline','RP','RP'), score = c(37.5,43,7,63,26,15,17,16,43,26,53,26,26,26,43,10,6,15,18,9,10,4,8,18,60,26,20,12.5,9,43,43,43,11,10,7,60,43,43,32,10.5,8,57.5))
#How to
dat %>%
ggplot(aes(x = factor(day), y = score)) +
geom_boxplot(aes(fill = group))+
geom_line(
data = dat %>%
group_by(day) %>%
summarise(score = median(score,na.rm = TRUE)),
aes(group = 1),
size = 1,
col = "red"
)
I want to create in R a plot which contains side by side bars and line charts as follows:
I tried:
Total <- c(584,605,664,711,759,795,863,954,1008,1061,1117,1150)
Infected <- c(366,359,388,402,427,422,462,524,570,560,578,577)
Recovered <- c(212,240,269,301,320,359,385,413,421,483,516,548)
Death <- c(6,6,7,8,12,14,16,17,17,18,23,25)
day <- itemizeDates(startDate="01.04.20", endDate="12.04.20")
df <- data.frame(Day=day, Infected=Infected, Recovered=Recovered, Death=Death, Total=Total)
value_matrix = matrix(, nrow = 2, ncol = 12)
value_matrix[1,] = df$Recovered
value_matrix[2,] = df$Death
plot(c(1:12), df$Total, ylim=c(0,1200), xlim=c(1,12), type = "b", col="peachpuff", xaxt="n", xlab = "", ylab = "")
points(c(1:12), df$Infected, type = "b", col="red")
barplot(value_matrix, beside = TRUE, col = c("green", "black"), width = 0.35, add = TRUE)
But the bar chart does not fit the line chart. I guess it would be easier to use ggplot2, but don't know how. Could anyone help me? Thanks a lot in advance!
With ggplot2, the margins are handled nicely for you, but you'll need the data in two separate long forms. Reshape from wide to long with tidyr::gather, tidyr::pivot_longer, reshape2::melt, reshape, or whatever you prefer.
library(tidyr)
library(ggplot2)
df <- data.frame(
Total = c(584,605,664,711,759,795,863,954,1008,1061,1117,1150),
Infected = c(366,359,388,402,427,422,462,524,570,560,578,577),
Recovered = c(212,240,269,301,320,359,385,413,421,483,516,548),
Death = c(6,6,7,8,12,14,16,17,17,18,23,25),
day = seq(as.Date("2020-04-01"), as.Date("2020-04-12"), by = 'day')
)
ggplot(
tidyr::gather(df, Population, count, Total:Infected),
aes(day, count, color = Population, fill = Population)
) +
geom_line() +
geom_point() +
geom_col(
data = tidyr::gather(df, Population, count, Recovered:Death),
position = 'dodge', show.legend = FALSE
)
Another way to do it is to gather twice before plotting. Not sure if this is easier or harder to understand, but you get the same thing.
df %>%
tidyr::gather(Population, count, Total:Infected) %>%
tidyr::gather(Resolution, count2, Recovered:Death) %>%
ggplot(aes(x = day, y = count, color = Population)) +
geom_line() +
geom_point() +
geom_col(
aes(y = count2, color = Resolution, fill = Resolution),
position = 'dodge', show.legend = FALSE
)
You can actually plot the lines and points without reshaping by making separate calls for each, but to dodge bars (or get legends), you'll definitely need to reshape.
I have a data frame and I would like to stack the points that have overlaps exactly on top of each other.
here is my example data:
value <- c(1.080251e-04, 1.708859e-01, 1.232473e-05, 4.519876e-03,2.914256e-01, 5.869711e-03, 2.196347e-01,4.124873e-01, 5.914052e-03, 2.305623e-03, 1.439013e-01, 5.407597e-03, 7.530298e-02, 7.746897e-03)
names = letters[1:7]
data <- data.frame(names = rep(names,), group = group, value = value, stringsAsFactors = T)
group <- c(rep("AA", 7) , rep("BB", 7))
I am using the following command:
p <- ggplot(data, aes(x = names, y = "", color = group)) +
geom_point(aes(size = -log(value)), position = "stack")
plot(p)
But the stacked circle outlines out of the grid. I want it close or exactly next to the bottom circle. do you have any idea how I can fix the issue?
Thanks,
The y-axis has no numeric value, so use the group instead. And we don't need the color legend now since the group labels are shown on the y-axis.
ggplot(data, aes(x = names, y = group, color = group)) +
geom_point(aes(size = -log(value))) +
guides(color=FALSE)
I have a boxplot with multiple groups in R.
When i add the dots within the boxplots, they are not in the center.
Since each week has a different number of boxplots, the dots are not centered within the box.
The problem is in the geom_point part.
I uploaded my data of df.m in a text file and a figure of what i get.
I am using ggplot, and here is my code:
setwd("/home/usuario")
dput("df.m")
df.m = read.table("df.m.txt")
df.m$variable <- as.factor(df.m$variable)
give.n = function(elita){
return(c(y = median(elita)*-0.1, label = length(elita)))
}
p = ggplot(data = df.m, aes(x=variable, y=value))
p = p + geom_boxplot(aes(fill = Label))
p = p + geom_point(aes(fill = Label), shape = 21,
position = position_jitterdodge(jitter.width = 0))
p = p + stat_summary(fun.data = give.n, geom = "text", fun.y = median)
p
Here is my data in a text file:
https://drive.google.com/file/d/1kpMx7Ao01bAol5eUC6BZUiulLBKV_rtH/view?usp=sharing
Only in variable 12 is in the center, because there are 3 groups (the maximum of possibilities!
I would also like to show the counting of observations. If I use the code shown, I can only get the number of observations for all the groups. I would like to add the counting for EACH GROUP.
Thank you in advance
enter image description here
Here's a solution using boxplot and dotplot and an example dataset:
library(tidyverse)
# example data
dt <- data.frame(week = c(1,1,1,1,1,1,1,1,1,
2,2,2,2,2,2,2,2,2),
value = c(6.40,6.75,6.11,6.33,5.50,5.40,5.83,4.57,5.80,
6.00,6.11,6.40,7.00,3,5.44,6.00,5,6.00),
donor_type = c("A","A","A","A","CB","CB","CB","CB","CB",
"CB","CB","CB","CB","CB","A","A","A","A"))
# create the plot
ggplot(dt, aes(x = factor(week), y = value, fill = donor_type)) +
geom_boxplot() +
geom_dotplot(binaxis='y', stackdir='center', position = position_dodge(0.75))
You should be able to adjust my code to your real dataset easily.
Edited answer with OP's dataset:
Using some generated data and geom_point():
library(tidyverse)
df.m <- df.m %>%
mutate(variable = as.factor(variable)) %>%
filter(!is.na(value))
ggplot(df.m, aes(x = variable, y = value, fill = Label)) +
geom_boxplot() +
geom_point(shape = 21, position = position_jitterdodge(jitter.width = 0)) +
scale_x_discrete("variable", drop = FALSE)
I want to make a heatmap that creates a group of clarity & color combinations as the X axis and cut as the Y axis. The heatmap would color based upon the counts of clarity+color and its intersection with the cut.
library(ggplot2)
library(dplyr)
## rename diamonds df
# 1. Generate a count for the frequency of cut+clarity
# 2. Make a heatmap of this using the following bins
# 3. Red <= 100 Frequency
Yellow = between (100 and 500)
Green > 500
# place counts inside the cell:
df = diamonds %>%
select( cut, clarity) %>%
group_by(cut,clarity)%>%
mutate(count = n())
myplot = ggplot(df, aes(x = clarity, y=cut)) +
geom_bin2d( bins = c(100,500,50000), col='orange') #
geom_text( aes(label = count),col='red')
myplot
Try this:
df$col <- cut(df$count,breaks = c(-Inf,100,500,Inf),right = TRUE)
df$color<-df$col
levels(df$color) <- c("<=100","100<#<=500",">500")
ggplot(data = df, aes(x = clarity, y = cut)) +
geom_tile(aes(fill = df$color), colour = "white") +
scale_fill_brewer("Count",palette = "Set1")+
geom_text(aes(label = count),col='yellow',cex=3)