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))
Related
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()
Hey I have the following code:
df = data.frame(Type = c("A", "B", "A", "A", "B"), FLAG = c(1, 1, 0, 1, 0))
df
ggplot(df, aes(x = Type)) + geom_bar(stat = "count", aes(fill = factor(FLAG)), position = "dodge") + coord_flip() + stat_count(geom = "text", colour = "white", size = 3.5,
aes(label = ..count..),position=position_stack(vjust=0.5)) + theme_bw()
but it doesnt work as I want. The graph is OK but instead displaying the total number of observations of each type I want to display the number of each flag (so instead 2 for "B" type I want to display 1 and 1 because for "B" we have 1 observation with FLAG 1 and 1 observations with FLAG 0). What should I change?
With the interaction between Type and FLAG the bars display the counts per groups of both.
ggplot(df, aes(x = interaction(Type, FLAG))) +
geom_bar(stat = "count",
aes(fill = factor(FLAG)), position = "dodge") +
coord_flip() +
stat_count(geom = "text",
aes(label = ..count..),
position=position_stack(vjust=0.5),
colour = "white", size = 3.5) +
theme_bw()
You could replace the stat_count() and geom_bar() with a little pre-processing with count() and geom_col(). Here is an example:
df %>%
janitor::clean_names() %>%
count(type, flag) %>%
ggplot(aes(type, n, fill = as.factor(flag))) +
geom_col(position = "dodge") +
geom_text(aes(label = n, y = n - 0.05), color = "white",
position = position_dodge(width = 1)) +
scale_y_continuous(breaks = 0:3, limits = c(0,3)) +
labs(fill = "flag") +
coord_flip() +
theme_bw()
The only thing janitor::clean_names() does is transform variable names, from uppercase and spaces to lowercase and underscores, respectively.
In a plot like this
library(ggplot2)
df <- data.frame(class = c("a","b","a","b"), date = c(2009,2009,2010,2010), volume=c(1,1,2,0))
df <- df %>% group_by(date) %>% mutate(volumep = 100 * volume/sum(volume))
ggplot(df, aes(x = date, y = volumep, fill = class, label = volumep)) +
geom_bar(stat = "identity") +
geom_text(size = 3, position = position_stack(vjust = 0.5)) + coord_flip()
How is it possible to increase the text in the boxes in the right (class) and how to make the x axis have 0, 25, 50 and 100 values?
To answer the question, just adjust the involved aesthetics, y and size.
ggplot(df, aes(x = date, y = 100*volume, fill = class, label = volume)) +
geom_bar(stat = "identity") +
geom_text(size = c(3, 3, 5, 5), position = position_stack(vjust = 0.5)) +
coord_flip() +
ylab("volume")
Another option is to mutate the values of volume first. In this case, there would be no need to manually set the y axis label.
After the question's edit, the code is now as follows.
library(ggplot2)
library(dplyr)
df %>%
group_by(date) %>%
mutate(volume = 100*volume/sum(volume)) %>%
ggplot(aes(x = date, y = volume, fill = class, label = volume)) +
geom_bar(stat = "identity") +
geom_text(size = c(3, 3, 5, 5), position = position_stack(vjust = 0.5)) +
coord_flip()
ggplot(df, aes(x = date, y = volumnep, fill = class, label = volumnep)) +
geom_bar(stat = "identity") +
geom_text(size = 3, position = position_stack(vjust = 0.5)) +
coord_flip() +
theme(legend.title=element_text(size=22),
legend.text=element_text(size=22)) +
scale_y_continuous(breaks=c(0,25, 50, 100))
Edit:
I'd suggest recasting date as a factor:
ggplot(df, aes(x = factor(date), y = volumnep, fill = class, label = volumnep)) +
geom_bar(stat = "identity") +
geom_text(size = 3, position = position_stack(vjust = 0.5)) +
coord_flip() +
theme(legend.title=element_text(size=22),
legend.text=element_text(size=22)) +
scale_y_continuous(breaks=c(0,25, 50, 100)) +
labs(y="date")
I have a dataframe which I would like to create a bargraph with primary and secondary axes.
geom_bar(data=top_ten_S, aes(x=Combination, y=AvgTopline), stat="identity",fill="red") +
coord_flip() +
geom_text(
data=top_ten_S,
aes(
x=Combination, y=AvgTopline,
label=paste0("R",round(AvgTopline,0)),
hjust=ifelse(AvgTopline < max(top_ten_S$AvgTopline) / 1.5, -0.1, 1.1), # <- Here lies the magic
),
)
my df looks like
top_ten_S <- data.frame(Combination = c("a", "b", "c"),
Nrcustomers = c(20, 200, 1900),
AvgTopline = c(1000,3000,1500))
I am only able to plot one column with the above code - I would like to a secondary axes so that I could plot Combination against NrCustomers and AvgTopline in
Method 1
top_ten_S %>%
gather(key, value, -Combination) %>%
ggplot(aes(x = Combination, y = value, fill = key)) +
geom_bar(stat = "identity", position = "dodge") +
labs(fill = "")
Method 2
top_ten_S %>%
gather(key, value, -Combination) %>%
ggplot(aes(x = Combination, y = value, fill = key)) +
geom_bar(stat = "identity", position = "dodge", show.legend = FALSE) +
facet_grid(. ~ key)
Edit: Method 2
top_ten_S %>%
gather(key, value, -Combination) %>%
ggplot(aes(x = Combination, y = value, fill = key)) +
geom_bar(stat = "identity", position = "dodge", show.legend = FALSE) +
facet_grid(. ~ key, space = "free_y", scales = "free_y") +
theme(axis.text.x = element_text(angle = 60))
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: