I have a dataset where I would compare some new and old changes within some groups (Species). I have a plot which creates the desired output, but the labels are not as desired. I would like them to be between the old and new bars. This is a bit tricky when the labels are of different length.
Example
library(ggplot2)
iris$change <- sample(c('new', 'old'), 150, replace = TRUE)
iris$mean1 <- ifelse(iris$Sepal.Length < mean(iris$Sepal.Length), 'Below', 'Above')
breaks
breaks <- unique(paste(iris$Species[iris$change == 'new'], iris$change[iris$change == 'new']))
ggplot(iris, aes(x = paste(Species, change), y = Petal.Width, fill = mean1)) +
geom_bar(stat = 'identity', position = 'fill') +
scale_x_discrete(breaks = breaks, labels = c('Setosa', 'vers', 'Virginica')) +
theme(axis.text.x = element_text(hjust = -1.2)) +
geom_text(aes(label = ifelse(change == "new", 'new', '')), size = 3, y = 0.05) +
geom_text(aes(label = ifelse(change == "old", 'old', '')), size = 3, y = 0.05)
I believe you can get what you want using faceting:
library(ggplot2)
iris$change <- sample(c('new', 'old'), 150, replace = TRUE)
iris$mean1 <- ifelse(iris$Sepal.Length < mean(iris$Sepal.Length), 'Below', 'Above')
ggplot(iris, aes(x = change, y = Petal.Width, fill = mean1)) +
geom_bar(stat = 'identity', position = 'fill') +
facet_wrap(~Species, strip.position = "bottom")+
theme(strip.placement = "outside",
strip.background = element_rect(colour = "white", fill = "white"))+
xlab(NULL)
Related
So my legend here is village which has (Chirodzo, God, Ruaca). How to remove the legend and display it inside the bars; for instance inside the bar for chirodzo, I want chirodzo written inside?
ggplot(data = interviews_plotting, aes(x = respondent_wall_type, fill = village)) +
geom_bar(position = "fill")
Source is here https://mq-software-carpentry.github.io/r-ggplot-extension/02-categorical-data/index.html
ggplot(data = interviews_plotting, aes(x = respondent_wall_type, fill = village)) +
geom_bar(position = "fill")
To label your bars with the fill category and getting rid of the legend you could use geom_text like so:
Using mtcars as example data:
library(ggplot2)
ggplot(data = mtcars, aes(x = am, fill = factor(cyl))) +
geom_bar(position = "fill") +
geom_text(aes(label = cyl), stat = "count", position = position_fill(vjust = 0.5)) +
guides(fill = "none")
From your comments, it sounds like you are looking for something like this:
library(ggplot2)
ggplot(interviews_plotting, aes(x = respondent_wall_type, fill = village)) +
geom_bar(position = position_dodge()) +
geom_text(stat = 'count',
aes(y = stat(count)/2, label = village, group = village),
position = position_dodge(width = 1), angle = 90) +
guides(fill = guide_none())
Or, if you want to get a bit more sophisticated with your label placement and theme choices:
library(ggplot2)
ggplot(interviews_plotting, aes(x = respondent_wall_type, fill = village)) +
geom_bar(position = position_dodge(width = 0.9), width = 0.8) +
geom_text(stat = 'count', size = 6,
aes(y = ifelse(stat(count) > 2, stat(count)/2, stat(count)),
label = village, group = village,
hjust = ifelse(stat(count) > 2, 0.5, -0.2)),
position = position_dodge(width = 0.9), angle = 90) +
labs(x = 'Wall type', y = 'Count') +
theme_minimal(base_size = 16) +
scale_fill_brewer(palette = 'Set2', guide = 'none')
Data used
interviews_plotting <- read.csv(paste0("https://raw.githubusercontent.com/",
"humburg/r-ggplot-project/master/",
"data_output/interviews_plotting.csv"))
I have this code:
as_tibble(earlyCiliated[[]]) %>%
ggplot(aes(x="", y=Phase, fill=Phase)) + geom_col() +
coord_polar("y", start=0) +
geom_text(aes(label = paste0(Phase, "%")))
and my output looks like this:
What am I doing wrong that's causing the labels to all be on top of each other?
I can't completely recreate your plot because I do not have your data. That being said, you can try this:
install.packages("ggrepel")
library(ggrepel)
as_tibble(earlyCiliated[[]]) %>%
ggplot(aes(x="", y=Phase, fill=Phase)) + geom_col() +
coord_polar("y", start=0) +
geom_label_repel(data = earlyCiliated[[]],
aes(y = Phase, label = paste0(Phase, "%")),
size = 4.5, nudge_x = 1, show.legend = FALSE)
This is what it will look like (using other data because none was provided)
library(ggplot2)
library(ggrepel)
library(tidyverse)
df <- data.frame(value = c(15, 25, 32, 28),
group = paste0("G", 1:4))
# Get the positions
df2 <- df %>%
mutate(csum = rev(cumsum(rev(value))),
pos = value/2 + lead(csum, 1),
pos = if_else(is.na(pos), value/2, pos))
ggplot(df, aes(x = "" , y = value, fill = fct_inorder(group))) +
geom_col(width = 1, color = 1) +
coord_polar(theta = "y") +
scale_fill_brewer(palette = "Pastel1") +
geom_label_repel(data = df2,
aes(y = pos, label = paste0(value, "%")),
size = 4.5, nudge_x = 1, show.legend = FALSE) +
guides(fill = guide_legend(title = "Group")) +
theme_void()
I am creating a plot with 3 variables as below. Is there a way to arrange the plot in a descending order such that the bar with the highest proportion of variable "c" comes first in the plot. Using this example last bar should come in first then middle one and then the first bar in the last.
long<- data.frame(
Name = c("abc","abc","abc","gif","gif","gif","xyz","xyz","xyz"),
variable = c("a","b","c","a","b","c","c","b","a"),
value = c(4,6,NA,2,8,1,6,NA,NA))
long_totals <- long %>%
group_by(Name) %>%
summarise(Total = sum(value, na.rm = T))
p <- ggplot()+
geom_bar(data = long,
aes(x = Name,
y = value,
fill=variable),
stat="summary",
position = "fill") +
geom_text(data = long_totals,
aes(y = 100,
x = Name,
label = Total),
size = 7,
position = position_fill(vjust = 1.02)) +
scale_y_continuous(labels = scales::percent_format()) +
ylab("Total_num") +
ggtitle("Totalnum") +
theme(plot.title = element_text(size = 20, hjust = 0.5)) +
theme(axis.text.x = element_text(angle = 75, vjust = 0.95, hjust=1))
The following code does arrange the bars by count of "c" but not by proportion. How can I arrange by proportion?
p<-long %>%
mutate(variable = fct_relevel(variable,
c("c", "b", "a"))) %>%
arrange(variable) %>%
mutate(Name = fct_inorder(Name))
p %>%
ggplot() +
aes(x = Name,
y = value,
fill = variable) +
geom_bar(position = "fill",
stat = "summary") +
We could use fct_rev from forcats package, it is in tidyverse:
p <- ggplot()+
geom_bar(data = long,
aes(x = fct_rev(Name),
y = value,
fill=variable),
stat="summary",
position = "fill") +
geom_text(data = long_totals,
aes(y = 100,
x = Name,
label = Total),
size = 7,
position = position_fill(vjust = 1.02)) +
scale_y_continuous(labels = scales::percent_format()) +
ylab("Total_num") +
ggtitle("Totalnum") +
theme(plot.title = element_text(size = 20, hjust = 0.5)) +
theme(axis.text.x = element_text(angle = 75, vjust = 0.95, hjust=1))
I would like to change the colour of one of my ggrepel labels to black. I have tried to override the inheritance by specifying ...geom_text_repel(...colour='black') but that doesn't seem to work.
My attempt at a fix to the problem is in the second geom_text_repel function (below).
N.B. If there is a way to control the colour of individual geom_text_repel elements, rather than having to call the function twice, I would prefer that.
library("tidyverse")
library("ggthemes")
library("ggrepel")
df1 <- gather(economics, variable_name, observation, -date) %>%
rename(period = date) %>%
filter(variable_name == 'psavert')
df2 <- gather(economics, variable_name, observation, -date) %>%
rename(period = date) %>%
filter(variable_name == 'uempmed')
ggplot(df1, aes(x = period, y = observation, colour = variable_name)) +
geom_line() +
geom_line(data = df2, colour = 'black', size = .8) +
geom_text_repel(
data = subset(df1, period == max(as.Date(period, "%Y-%m-%d"))),
aes(label = variable_name),
size = 3,
nudge_x = 45,
segment.color = 'grey80'
) +
geom_text_repel(
data = subset(df2, period == max(as.Date(period, "%Y-%m-%d"))),
aes(label = variable_name, colour = 'black'), #How do I set the colour of the label text to black?
size = 3,
nudge_x = 45,
segment.color = 'grey80'
) +
scale_y_continuous(labels = scales::comma) +
theme_minimal(base_size = 16) +
scale_color_tableau() +
scale_fill_tableau() +
theme(legend.position = 'none') +
labs(x="", y="", title = "Economic Data") +
scale_x_date(limits = c(min(df1$period), max(df1$period) + 1200))
Do the same thing you did in your geom_line() layer. You want to set a color, not a mapping. Make colour = 'black' an argument to geom_text_repel(), not aes().
ggplot(df1, aes(x = period, y = observation, colour = variable_name)) +
geom_line() +
geom_line(data = df2, colour = 'black', size = .8) + # just like this layer
geom_text_repel(
data = subset(df1, period == max(as.Date(period, "%Y-%m-%d"))),
aes(label = variable_name),
size = 3,
nudge_x = 45,
segment.color = 'grey80'
) +
geom_text_repel(
data = subset(df2, period == max(as.Date(period, "%Y-%m-%d"))),
aes(label = variable_name) # don't assign it here,
size = 3,
nudge_x = 45,
segment.color = 'grey80',
colour = "black" # assign it here
) +
scale_y_continuous(labels = scales::comma) +
theme_minimal(base_size = 16) +
scale_color_tableau() +
scale_fill_tableau() +
theme(legend.position = 'none') +
labs(x="", y="", title = "Economic Data") +
scale_x_date(limits = c(min(df1$period), max(df1$period) + 1200))
Note that now the first line AND text are now both set manually to "black", so the automatic variable assignment will start over with next line (and text). If you want to set that manually to a different color, you can use the same strategy (set it as an argument to the geom, not as an argument to aes
I'm plotting a stacked bar graph and use geom_text to insert the value and name of each stack. The problem is some stacks are very small/narrow, so that the text of two stacks overlap each other and hence is not very readable. How can I modify the code to solve this issue.
Type<-c("ddddddddddd","ddddddddddd","bbbbbbbbbbbbb","ddddddddddd","eeeeeeeeeeeeee","bbbbbbbbbbbbb","ddddddddddd","bbbbbbbbbbbbb","ddddddddddd",
"eeeeeeeeeeeeee","mmmmmmmmmmmmmmmmmmm","bbbbbbbbbbbbb","ddddddddddd","bbbbbbbbbbbbb","eeeeeeeeeeeeee")
Category<-c("mmmmm","mmmmm","gggggggggggggggggg","ffffffffffff","ffffffffffff","ffffffffffff","sanddddddddd","sanddddddddd","yyyyyyyyyyy",
"yyyyyyyyyyy","yyyyyyyyyyy","sssssssssssssss","sssssssssssssss","sssssssssssssss","ttttttttttttt")
Frequency<-c(4,1,30,7,127,11,1,1,6,9,1,200,3,4,5)
Data <- data.frame(Type, Category, Frequency)
p <- ggplot(Data, aes(x = Type, y = Frequency)) +
geom_bar(aes(fill = Category), stat="identity", show.legend = FALSE) +
geom_text(aes(label = Frequency), size = 3) +
geom_text(aes(label = Category), size = 3)
Considering your data, a facetted plot might be a better approach:
# summarise your data
library(dplyr)
d1 <- Data %>%
mutate_each(funs(substr(.,1,2)),Type,Category) %>%
group_by(Type,Category) %>%
summarise(Freq = sum(Frequency)) %>%
mutate(lbl = paste(Category,Freq)) # create a label by pasting the 'Category' and the 'Freq' variables together
# plot
ggplot(d1, aes(x = Category, y = Freq, fill = Category)) +
geom_bar(stat="identity", width = 0.7, position = position_dodge(0.8)) +
geom_text(aes(label = lbl), angle = 90, size = 5, hjust = -0.1, position = position_dodge(0.8)) +
scale_y_continuous(limits = c(0,240)) +
guides(fill = FALSE) +
facet_grid(.~Type, scales = "free", space = "free") +
theme_bw(base_size = 14)
which gives:
In the above plot I shortened the labels on purpose. If you don't want to do that, you could consider this:
d2 <- Data %>%
group_by(Type,Category) %>%
summarise(Freq = sum(Frequency)) %>%
mutate(lbl = paste(Category,Freq))
ggplot(d2, aes(x = Category, y = Freq, fill = Category)) +
geom_bar(stat="identity", width = 0.7, position = position_dodge(0.8)) +
geom_text(aes(y = 5, label = lbl), alpha = 0.6, angle = 90, size = 5, hjust = 0, position = position_dodge(0.8)) +
scale_y_continuous(limits = c(0,240)) +
guides(fill = FALSE) +
facet_grid(.~Type, scales = "free", space = "free") +
theme_bw(base_size = 14) +
theme(axis.text.x = element_blank(),
axis.ticks.x = element_blank())
which gives: