dodged bar plot in ggplot again has me stumped. I asked about annotating text above bars on here a few weeks back (LINK) and got a terrific response to use + stat_bin(geom="text", aes(label=..count.., vjust=-1)). I figured since I already have the counts I'll just supply them with out the .. before and after and I told stat_bin that the position was dodge. It lines them up over the center of the group and adjusts up and down. Probably something minor. Please help me to get the text over the bars.
mtcars2 <- data.frame(type=factor(mtcars$cyl),
group=factor(mtcars$gear))
library(plyr); library(ggplot)
dat <- rbind(ddply(mtcars2,.(type,group), summarise,
count = length(group)),c(8,4,NA))
p2 <- ggplot(dat,aes(x = type,y = count,fill = group)) +
geom_bar(colour = "black",position = "dodge",stat = "identity") +
stat_bin(geom="text", aes(position='dodge', label=count, vjust=-.6))
I was having trouble getting the position dodges to line up, so I ended up creating a position_dodge object (is that the right terminology?), saving it to a variable, and then using that as the position for both geoms. Somewhat infuriatingly, they still seem to be a little off centre.
dodgewidth <- position_dodge(width=0.9)
ggplot(dat,aes(x = type,y = count, fill = group)) +
geom_bar(colour = "black", position = dodgewidth ,stat = "identity") +
stat_bin(geom="text", position= dodgewidth, aes(x=type, label=count), vjust=-1)
Updated geom_bar() needs stat = "identity"
I think this does what you want as well.
mtcars2 <- data.frame(type = factor(mtcars$cyl), group = factor(mtcars$gear))
library(plyr); library(ggplot2)
dat <- rbind(ddply(mtcars2, .(type, group), summarise, count = length(group)), c(8, 4, NA))
p2 <- ggplot(dat, aes(x = type,y = count,fill = group)) +
geom_bar(stat = "identity", colour = "black",position = "dodge", width = 0.8) +
ylim(0, 14) +
geom_text(aes(label = count, x = type, y = count), position = position_dodge(width = 0.8), vjust = -0.6)
p2
Related
I want to plot the data shown below as a grouped bar_plot.
I tried position = "dodge" or position = "dodge2" but it didn't work. Ι also tried position = position_dodge()
It kinda works if i use geom_bar instead of geom_col and remove the y=overlap_percent:
p3 <- ggplot(data = comp_coors, aes(x = species_code, fill = mirna_form)) +
geom_bar(position = "dodge2") + theme_classic()
p3
but i would like the y_axis to have the overlap_percent.
Another attempt which ends in a stacked barplot is:
p2 <- ggplot(data = comp_coors, aes(x = species_code, y = overlap_percent, fill = mirna_form)) +
geom_bar(stat = "identity") + theme_classic()
p2
Finally by using geom_col, it returns this which it doesn't make sense, at least to me:
p4 <- ggplot(data = comp_coors, aes(x = species_code, y = overlap_percent, fill = mirna_form)) +
geom_col(position = "dodge") + theme_classic()
p4
The data that i want to plot :
comp_coors <- data.table( species = c("aae","cel", "dme","hsa", "mdo"),
mirna_form = c("mature", "precursor"),
overlap_percent = c(100.0, 100.0, 88.0, 95.5, 91.7, 100.0, 96.6, 98.4),
overlapping_attribute = c("ID=MIMAT0014285;Alias=MIMAT0014285", "ID=MI0000043;Alias=MI0000043;Name=cel-mir-72", "ID=MIMAT0000401;Alias=MIMAT0000401;Name=dme-miR-", "ID=MI0000791;Alias=MI0000791;Name=hsa-mir-383", "ID=MI0005331;Alias=MI0005331;Name=mdo-let-7g")
)
Try using species as a factor and add stat = "identity" like this:
ggplot(data = comp_coors, aes(x = factor(species), y = overlap_percent, fill = mirna_form)) +
geom_bar(position = "dodge", stat = "identity") + theme_classic() + labs(x = "Species", y = "Overlap percent")
Output:
A grouped barplot with overlap_percent on y-axis right.
I have createg stacked barplot with the corresponding lables inside of the bars are. However, I would like to change the plot, such that position = fill. This does something weird with my plot. Any ideas how to fix this ?
cat <- c (0,0,0,0,0,1,1,1,1,1)
value <- c(100,200,300,100,300,200,200,200,300,300)
N <- c(15,43,7,53,25,33,5,3,2,2)
year <- c(2014,2017,2018,2016,2015,2014,2016,2018,2017,2015)
exdata <- cbind(cat, value, N, year)
exdata <- as.data.frame(exdata)
exdata2 <- group_by(exdata, year) %>% mutate (pct = paste0((round(value/sum(value)*100, 2))," %"))
exdata2 <- as.data.frame(exdata2)
plot.exdata2 <- ggplot(exdata2, aes(year, value, fill = factor(cat))) +
geom_bar(stat = "identity", position = "stack") + # position = stack
geom_text(aes(label = exdata2$pct), position = position_stack(vjust = 0.5), size = 3.2) +
theme_pubclean()
desired format:
You can try geom_col instead as it is recommended to use when stat = "identity". In addition you have to specify "fill" position in the geom_text as well:
ggplot(exdata2, aes(year, value, fill = factor(cat))) +
geom_col(position = "fill") +
geom_text(aes(label = pct), position = position_fill(vjust = 0.5))
I'm having an issue with data labels incorrectly ordering using ggplot2.
Unfortunately, other SE Q&As on this topic are not very insightful(example), so I'm having to reach out with a reprex. I have the following data:
df = as.data.frame(structure(list(geotype = c('urban','urban','urban','urban','suburban','suburban','suburban','suburban'),
limitations = c('all','some','all','some','all','some','all','some'),
metric = c('lte','lte','5g','5g','lte','lte','5g','5g'),
capacity=c(12,11,5,4,14,10,5,3))))
If I then try to plot this data using this code:
ggplot(df, aes(x = geotype, y = capacity, fill=metric)) + geom_bar(stat="identity") +
facet_grid(~limitations) +
geom_text(data = df, aes(geotype, capacity + 2, label=capacity), size = 3)
I get this incorrect labelling order:
I've played with the ordering of the variables for ages (e.g. rev(capacity)) but I can't fix the issue. Can anyone provide a more comprehensive answer for the whole SE community as to how to deal with label ordering?
You need to call the position argument in geom_text to match the filled aesthetics data with geom_bar and to let the function know the data is stacked.
ggplot(df, aes(x = geotype, y = capacity, fill=metric)) +
geom_bar(stat="identity") +
geom_text(data = df, aes(geotype, capacity, label=capacity), size = 3, vjust = 2,
position = position_stack()) +
facet_grid(~limitations)
You can set the labels in the mail ggplot aes
ggplot(df, aes(x = geotype, y = capacity, fill = metric, label = capacity ) ) +
geom_col() +
geom_text( size = 3, position = position_stack( vjust = 0.5 ) ) +
facet_grid( ~limitations )
Something like this? The position stack.
g <- ggplot(df, aes(x = geotype, y = capacity, fill = metric, label =
capacity))
g + geom_col() + facet_grid(~limitations) +
geom_text(size = 3, vjust =3, position = position_stack())
I came across this question the other day and tried to re-create it for myself. ggplot, facet, piechart: placing text in the middle of pie chart slices
. My data is in a very similar format, but sadly the accepted answer did not help, hence why I am re posting.
I essentially want to create the accepted answer but with my own data, yet the issue I run into is that coord_polar does not support free scale. Using the first answer:
I tried it using the second version of the answer, with the ddplyr version, but I also do not get my desired output. Using the second answer:
Clearly none of these has the desired effect. I would prefer to create one as with size pie charts, but only showed four as an example, follows: .
This I did in excel, but with one legend, and no background grid.
Code
title<-c(1,1,2,2,3,3,4,4,5,5,6,6)
type<-c('A','B','A','B','A','B','A','B','A','B','A','B')
value<-c(0.25,0.75,0.3,0.7,0.4,0.6,0.5,0.5,0.1,0.9,0.15,0.85)
piec<-data.frame(title,type,value)
library(tidyverse)
p1<-ggplot(data = piec, aes(x = "", y = value, fill = type)) +
geom_bar(stat = "identity") +
geom_text(aes(label = value), position = position_stack(vjust = 0.5)) +
coord_polar(theta = "y")
#facet_grid(title ~ ., scales = "free")
p1
piec <- piec %>% group_by(title) %>% mutate(pos=cumsum(value)-0.5*value)
p2<-ggplot(data = piec) +
geom_bar(aes(x = "", y = value, fill = type), stat = "identity") +
geom_text(aes(x = "", y = pos, label = value)) +
coord_polar(theta = "y")
#facet_grid(Channel ~ ., scales = "free")
p2
You don't have to supply different y values for geom_text and geom_bar (use y = value for both of them). Next you have to specify position in geom_text. Finally, remove scales from facets.
library(ggplot2)
title<-c(1,1,2,2,3,3,4,4,5,5,6,6)
type<-c('A','B','A','B','A','B','A','B','A','B','A','B')
value<-c(0.25,0.75,0.3,0.7,0.4,0.6,0.5,0.5,0.1,0.9,0.15,0.85)
piec<-data.frame(title,type,value)
ggplot(piec, aes("", value, fill = type)) +
geom_bar(stat = "identity", color = "white", size = 1) +
geom_text(aes(label = paste0(value * 100, "%")),
position = position_stack(vjust = 0.5),
color = "white", size = 3) +
coord_polar(theta = "y") +
facet_wrap(~ title, ncol = 3) +
scale_fill_manual(values = c("#0048cc", "#cc8400")) +
theme_void()
I'm working on some data on party polarization (something like this) and used geom_dumbbell from ggalt and ggplot2. I keep getting the same aes error and other solutions in the forum did not address this as effectively. This is my sample data.
df <- data_frame(policy=c("Not enough restrictions on gun ownership", "Climate change is an immediate threat", "Abortion should be illegal"),
Democrats=c(0.54, 0.82, 0.30),
Republicans=c(0.23, 0.38, 0.40),
diff=sprintf("+%d", as.integer((Democrats-Republicans)*100)))
I wanted to keep order of the plot, so converted policy to factor and wanted % to be shown only on the first line.
df <- arrange(df, desc(diff))
df$policy <- factor(df$policy, levels=rev(df$policy))
percent_first <- function(x) {
x <- sprintf("%d%%", round(x*100))
x[2:length(x)] <- sub("%$", "", x[2:length(x)])
x
}
Then I used ggplot that rendered something close to what I wanted.
gg2 <- ggplot()
gg2 <- gg + geom_segment(data = df, aes(y=country, yend=country, x=0, xend=1), color = "#b2b2b2", size = 0.15)
# making the dumbbell
gg2 <- gg + geom_dumbbell(data=df, aes(y=country, x=Democrats, xend=Republicans),
size=1.5, color = "#B2B2B2", point.size.l=3, point.size.r=3,
point.color.l = "#9FB059", point.color.r = "#EDAE52")
I then wanted the dumbbell to read Democrat and Republican on top to label the two points (like this). This is where I get the error.
gg2 <- gg + geom_text(data=filter(df, country=="Government will not control gun violence"),
aes(x=Democrats, y=country, label="Democrats"),
color="#9fb059", size=3, vjust=-2, fontface="bold", family="Calibri")
gg2 <- gg + geom_text(data=filter(df, country=="Government will not control gun violence"),
aes(x=Republicans, y=country, label="Republicans"),
color="#edae52", size=3, vjust=-2, fontface="bold", family="Calibri")
Any thoughts on what I might be doing wrong?
I think it would be easier to build your own "dumbbells" with geom_segment() and geom_point(). Working with your df and changing the variable refences "country" to "policy":
library(tidyverse)
# gather data into long form to make ggplot happy
df2 <- gather(df,"party", "value", Democrats:Republicans)
ggplot(data = df2, aes(y = policy, x = value, color = party)) +
# our dumbell
geom_path(aes(group = policy), color = "#b2b2b2", size = 2) +
geom_point(size = 7, show.legend = FALSE) +
# the text labels
geom_text(aes(label = party), vjust = -1.5) + # use vjust to shift text up to no overlap
scale_color_manual(values = c("Democrats" = "blue", "Republicans" = "red")) + # named vector to map colors to values in df2
scale_x_continuous(limits = c(0,1), labels = scales::percent) # use library(scales) nice math instead of pasting
Produces this plot:
Which has some overlapping labels. I think you could avoid that if you use just the first letter of party like this:
ggplot(data = df2, aes(y = policy, x = value, color = party)) +
geom_path(aes(group = policy), color = "#b2b2b2", size = 2) +
geom_point(size = 7, show.legend = FALSE) +
geom_text(aes(label = gsub("^(\\D).*", "\\1", party)), vjust = -1.5) + # just the first letter instead
scale_color_manual(values = c("Democrats" = "blue", "Republicans" = "red"),
guide = "none") +
scale_x_continuous(limits = c(0,1), labels = scales::percent)
Only label the top issue with names:
ggplot(data = df2, aes(y = policy, x = value, color = party)) +
geom_path(aes(group = policy), color = "#b2b2b2", size = 2) +
geom_point(size = 7, show.legend = FALSE) +
geom_text(data = filter(df2, policy == "Not enough restrictions on gun ownership"),
aes(label = party), vjust = -1.5) +
scale_color_manual(values = c("Democrats" = "blue", "Republicans" = "red")) +
scale_x_continuous(limits = c(0,1), labels = scales::percent)