Mixing
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Showing data values on stacked bar chart in ggplot2
I'd like to show data values on stacked bar chart in ggplot2. Here is my attempted code
Year <- c(rep(c("2006-07", "2007-08", "2008-09", "2009-10"), each = 4))
Category <- c(rep(c("A", "B", "C", "D"), times = 4))
Frequency <- c(168, 259, 226, 340, 216, 431, 319, 368, 423, 645, 234, 685, 166, 467, 274, 251)
Data <- data.frame(Year, Category, Frequency)
library(ggplot2)
p <- qplot(Year, Frequency, data = Data, geom = "bar", fill = Category, theme_set(theme_bw()))
p + geom_text(aes(label = Frequency), size = 3, hjust = 0.5, vjust = 3, position = "stack")
I'd like to show these data values in the middle of each portion. Any help in this regard will be highly appreciated. Thanks
r graphics ggplot2
asked Jul 11 '11 at 1:42
MYaseen208MYaseen208
7,94327100204
add a comment |
I'd like to show data values on stacked bar chart in ggplot2. Here is my attempted code
Year <- c(rep(c("2006-07", "2007-08", "2008-09", "2009-10"), each = 4))
Category <- c(rep(c("A", "B", "C", "D"), times = 4))
Frequency <- c(168, 259, 226, 340, 216, 431, 319, 368, 423, 645, 234, 685, 166, 467, 274, 251)
Data <- data.frame(Year, Category, Frequency)
library(ggplot2)
p <- qplot(Year, Frequency, data = Data, geom = "bar", fill = Category, theme_set(theme_bw()))
p + geom_text(aes(label = Frequency), size = 3, hjust = 0.5, vjust = 3, position = "stack")
I'd like to show these data values in the middle of each portion. Any help in this regard will be highly appreciated. Thanks
r graphics ggplot2
asked Jul 11 '11 at 1:42
MYaseen208MYaseen208
7,94327100204
Related question: stackoverflow.com/questions/18994631/…
– Tyler Rinker
Sep 25 '13 at 1:48
Not really the place for a debate, but I wonder if it's possible to be overly prescriptive about this, particularly for the more general audience. This is a nice example - numbers denote percentages that can be remembered, which removes the need for a scale that less numerically-literate readers might find less accessible?
– geotheory
Jan 20 '15 at 12:04
add a comment |
I'd like to show data values on stacked bar chart in ggplot2. Here is my attempted code
Year <- c(rep(c("2006-07", "2007-08", "2008-09", "2009-10"), each = 4))
Category <- c(rep(c("A", "B", "C", "D"), times = 4))
Frequency <- c(168, 259, 226, 340, 216, 431, 319, 368, 423, 645, 234, 685, 166, 467, 274, 251)
Data <- data.frame(Year, Category, Frequency)
library(ggplot2)
p <- qplot(Year, Frequency, data = Data, geom = "bar", fill = Category, theme_set(theme_bw()))
p + geom_text(aes(label = Frequency), size = 3, hjust = 0.5, vjust = 3, position = "stack")
I'd like to show these data values in the middle of each portion. Any help in this regard will be highly appreciated. Thanks
r graphics ggplot2
asked Jul 11 '11 at 1:42
MYaseen208MYaseen208
7,94327100204
I'd like to show data values on stacked bar chart in ggplot2. Here is my attempted code
Year <- c(rep(c("2006-07", "2007-08", "2008-09", "2009-10"), each = 4))
Category <- c(rep(c("A", "B", "C", "D"), times = 4))
Frequency <- c(168, 259, 226, 340, 216, 431, 319, 368, 423, 645, 234, 685, 166, 467, 274, 251)
Data <- data.frame(Year, Category, Frequency)
library(ggplot2)
p <- qplot(Year, Frequency, data = Data, geom = "bar", fill = Category, theme_set(theme_bw()))
p + geom_text(aes(label = Frequency), size = 3, hjust = 0.5, vjust = 3, position = "stack")
I'd like to show these data values in the middle of each portion. Any help in this regard will be highly appreciated. Thanks
r graphics ggplot2
r graphics ggplot2
asked Jul 11 '11 at 1:42
MYaseen208MYaseen208
7,94327100204
asked Jul 11 '11 at 1:42
MYaseen208MYaseen208
7,94327100204
asked Jul 11 '11 at 1:42
MYaseen208MYaseen208
7,94327100204
asked Jul 11 '11 at 1:42
MYaseen208MYaseen208
7,94327100204
asked Jul 11 '11 at 1:42
MYaseen208MYaseen208
7,94327100204
7,94327100204
Related question: stackoverflow.com/questions/18994631/…
– Tyler Rinker
Sep 25 '13 at 1:48
Not really the place for a debate, but I wonder if it's possible to be overly prescriptive about this, particularly for the more general audience. This is a nice example - numbers denote percentages that can be remembered, which removes the need for a scale that less numerically-literate readers might find less accessible?
– geotheory
Jan 20 '15 at 12:04
add a comment |
Related question: stackoverflow.com/questions/18994631/…
– Tyler Rinker
Sep 25 '13 at 1:48
Not really the place for a debate, but I wonder if it's possible to be overly prescriptive about this, particularly for the more general audience. This is a nice example - numbers denote percentages that can be remembered, which removes the need for a scale that less numerically-literate readers might find less accessible?
– geotheory
Jan 20 '15 at 12:04
Related question: stackoverflow.com/questions/18994631/…
– Tyler Rinker
Sep 25 '13 at 1:48
Related question: stackoverflow.com/questions/18994631/…
– Tyler Rinker
Sep 25 '13 at 1:48
Not really the place for a debate, but I wonder if it's possible to be overly prescriptive about this, particularly for the more general audience. This is a nice example - numbers denote percentages that can be remembered, which removes the need for a scale that less numerically-literate readers might find less accessible?
– geotheory
Jan 20 '15 at 12:04
Not really the place for a debate, but I wonder if it's possible to be overly prescriptive about this, particularly for the more general audience. This is a nice example - numbers denote percentages that can be remembered, which removes the need for a scale that less numerically-literate readers might find less accessible?
– geotheory
Jan 20 '15 at 12:04
add a comment |
2 Answers
2
active
oldest
votes
From ggplot 2.2.0 labels can easily be stacked by using position = position_stack(vjust = 0.5) in geom_text.
ggplot(Data, aes(x = Year, y = Frequency, fill = Category, label = Frequency)) +
geom_bar(stat = "identity") +
geom_text(size = 3, position = position_stack(vjust = 0.5))
Also note that "position_stack() and position_fill() now stack values in the reverse order of the grouping, which makes the default stack order match the legend."
Answer valid for older versions of ggplot:
Here is one approach, which calculates the midpoints of the bars.
library(ggplot2)
library(plyr)
# calculate midpoints of bars (simplified using comment by @DWin)
Data <- ddply(Data, .(Year),
transform, pos = cumsum(Frequency) - (0.5 * Frequency)
)
# library(dplyr) ## If using dplyr...
# Data <- group_by(Data,Year) %>%
# mutate(pos = cumsum(Frequency) - (0.5 * Frequency))
# plot bars and add text
p <- ggplot(Data, aes(x = Year, y = Frequency)) +
geom_bar(aes(fill = Category), stat="identity") +
geom_text(aes(label = Frequency, y = pos), size = 3)
edited Nov 21 '16 at 16:33
Henrik
42.2k994110
answered Jul 11 '11 at 3:34
RamnathRamnath
44.3k10103135
Thanks for this answer. I used it to do similar usingdata.tableinstead ofplyr, so something like this:Data.dt[,list(Category, Frequency, pos=cumsum(Frequency)-0.5*Frequency), by=Year]
– atomicules
May 17 '12 at 15:49
add a comment |
As hadley mentioned there are more effective ways of communicating your message than labels in stacked bar charts. In fact, stacked charts aren't very effective as the bars (each Category) doesn't share an axis so comparison is hard.
It's almost always better to use two graphs in these instances, sharing a common axis. In your example I'm assuming that you want to show overall total and then the proportions each Category contributed in a given year.
library(grid)
library(gridExtra)
library(plyr)
# create a new column with proportions
prop <- function(x) x/sum(x)
Data <- ddply(Data,"Year",transform,Share=prop(Frequency))
# create the component graphics
totals <- ggplot(Data,aes(Year,Frequency)) + geom_bar(fill="darkseagreen",stat="identity") +
xlab("") + labs(title = "Frequency totals in given Year")
proportion <- ggplot(Data, aes(x=Year,y=Share, group=Category, colour=Category))
+ geom_line() + scale_y_continuous(label=percent_format())+ theme(legend.position = "bottom") +
labs(title = "Proportion of total Frequency accounted by each Category in given Year")
# bring them together
grid.arrange(totals,proportion)
This will give you a 2 panel display like this:
If you want to add Frequency values a table is the best format.
edited Jan 14 '17 at 5:48
DYZ
27.8k62150
answered Aug 9 '13 at 11:28
AndrewMinCHAndrewMinCH
52738
add a comment |
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2 Answers
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2 Answers
2
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oldest
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From ggplot 2.2.0 labels can easily be stacked by using position = position_stack(vjust = 0.5) in geom_text.
ggplot(Data, aes(x = Year, y = Frequency, fill = Category, label = Frequency)) +
geom_bar(stat = "identity") +
geom_text(size = 3, position = position_stack(vjust = 0.5))
Also note that "position_stack() and position_fill() now stack values in the reverse order of the grouping, which makes the default stack order match the legend."
Answer valid for older versions of ggplot:
Here is one approach, which calculates the midpoints of the bars.
library(ggplot2)
library(plyr)
# calculate midpoints of bars (simplified using comment by @DWin)
Data <- ddply(Data, .(Year),
transform, pos = cumsum(Frequency) - (0.5 * Frequency)
)
# library(dplyr) ## If using dplyr...
# Data <- group_by(Data,Year) %>%
# mutate(pos = cumsum(Frequency) - (0.5 * Frequency))
# plot bars and add text
p <- ggplot(Data, aes(x = Year, y = Frequency)) +
geom_bar(aes(fill = Category), stat="identity") +
geom_text(aes(label = Frequency, y = pos), size = 3)
edited Nov 21 '16 at 16:33
Henrik
42.2k994110
answered Jul 11 '11 at 3:34
RamnathRamnath
44.3k10103135
Thanks for this answer. I used it to do similar usingdata.tableinstead ofplyr, so something like this:Data.dt[,list(Category, Frequency, pos=cumsum(Frequency)-0.5*Frequency), by=Year]
– atomicules
May 17 '12 at 15:49
add a comment |
From ggplot 2.2.0 labels can easily be stacked by using position = position_stack(vjust = 0.5) in geom_text.
ggplot(Data, aes(x = Year, y = Frequency, fill = Category, label = Frequency)) +
geom_bar(stat = "identity") +
geom_text(size = 3, position = position_stack(vjust = 0.5))
Also note that "position_stack() and position_fill() now stack values in the reverse order of the grouping, which makes the default stack order match the legend."
Answer valid for older versions of ggplot:
Here is one approach, which calculates the midpoints of the bars.
library(ggplot2)
library(plyr)
# calculate midpoints of bars (simplified using comment by @DWin)
Data <- ddply(Data, .(Year),
transform, pos = cumsum(Frequency) - (0.5 * Frequency)
)
# library(dplyr) ## If using dplyr...
# Data <- group_by(Data,Year) %>%
# mutate(pos = cumsum(Frequency) - (0.5 * Frequency))
# plot bars and add text
p <- ggplot(Data, aes(x = Year, y = Frequency)) +
geom_bar(aes(fill = Category), stat="identity") +
geom_text(aes(label = Frequency, y = pos), size = 3)
edited Nov 21 '16 at 16:33
Henrik
42.2k994110
answered Jul 11 '11 at 3:34
RamnathRamnath
44.3k10103135
Thanks for this answer. I used it to do similar usingdata.tableinstead ofplyr, so something like this:Data.dt[,list(Category, Frequency, pos=cumsum(Frequency)-0.5*Frequency), by=Year]
– atomicules
May 17 '12 at 15:49
add a comment |
From ggplot 2.2.0 labels can easily be stacked by using position = position_stack(vjust = 0.5) in geom_text.
ggplot(Data, aes(x = Year, y = Frequency, fill = Category, label = Frequency)) +
geom_bar(stat = "identity") +
geom_text(size = 3, position = position_stack(vjust = 0.5))
Also note that "position_stack() and position_fill() now stack values in the reverse order of the grouping, which makes the default stack order match the legend."
Answer valid for older versions of ggplot:
Here is one approach, which calculates the midpoints of the bars.
library(ggplot2)
library(plyr)
# calculate midpoints of bars (simplified using comment by @DWin)
Data <- ddply(Data, .(Year),
transform, pos = cumsum(Frequency) - (0.5 * Frequency)
)
# library(dplyr) ## If using dplyr...
# Data <- group_by(Data,Year) %>%
# mutate(pos = cumsum(Frequency) - (0.5 * Frequency))
# plot bars and add text
p <- ggplot(Data, aes(x = Year, y = Frequency)) +
geom_bar(aes(fill = Category), stat="identity") +
geom_text(aes(label = Frequency, y = pos), size = 3)
edited Nov 21 '16 at 16:33
Henrik
42.2k994110
answered Jul 11 '11 at 3:34
RamnathRamnath
44.3k10103135
From ggplot 2.2.0 labels can easily be stacked by using position = position_stack(vjust = 0.5) in geom_text.
ggplot(Data, aes(x = Year, y = Frequency, fill = Category, label = Frequency)) +
geom_bar(stat = "identity") +
geom_text(size = 3, position = position_stack(vjust = 0.5))
Also note that "position_stack() and position_fill() now stack values in the reverse order of the grouping, which makes the default stack order match the legend."
Answer valid for older versions of ggplot:
Here is one approach, which calculates the midpoints of the bars.
library(ggplot2)
library(plyr)
# calculate midpoints of bars (simplified using comment by @DWin)
Data <- ddply(Data, .(Year),
transform, pos = cumsum(Frequency) - (0.5 * Frequency)
)
# library(dplyr) ## If using dplyr...
# Data <- group_by(Data,Year) %>%
# mutate(pos = cumsum(Frequency) - (0.5 * Frequency))
# plot bars and add text
p <- ggplot(Data, aes(x = Year, y = Frequency)) +
geom_bar(aes(fill = Category), stat="identity") +
geom_text(aes(label = Frequency, y = pos), size = 3)
edited Nov 21 '16 at 16:33
Henrik
42.2k994110
answered Jul 11 '11 at 3:34
RamnathRamnath
44.3k10103135
edited Nov 21 '16 at 16:33
Henrik
42.2k994110
edited Nov 21 '16 at 16:33
Henrik
42.2k994110
edited Nov 21 '16 at 16:33
Henrik
42.2k994110
42.2k994110
answered Jul 11 '11 at 3:34
RamnathRamnath
44.3k10103135
answered Jul 11 '11 at 3:34
RamnathRamnath
44.3k10103135
answered Jul 11 '11 at 3:34
RamnathRamnath
44.3k10103135
44.3k10103135
Thanks for this answer. I used it to do similar usingdata.tableinstead ofplyr, so something like this:Data.dt[,list(Category, Frequency, pos=cumsum(Frequency)-0.5*Frequency), by=Year]
– atomicules
May 17 '12 at 15:49
add a comment |
Thanks for this answer. I used it to do similar usingdata.tableinstead ofplyr, so something like this:Data.dt[,list(Category, Frequency, pos=cumsum(Frequency)-0.5*Frequency), by=Year]
– atomicules
May 17 '12 at 15:49
Thanks for this answer. I used it to do similar using
data.table instead of plyr, so something like this: Data.dt[,list(Category, Frequency, pos=cumsum(Frequency)-0.5*Frequency), by=Year]– atomicules
May 17 '12 at 15:49
Thanks for this answer. I used it to do similar using
data.table instead of plyr, so something like this: Data.dt[,list(Category, Frequency, pos=cumsum(Frequency)-0.5*Frequency), by=Year]– atomicules
May 17 '12 at 15:49
add a comment |
As hadley mentioned there are more effective ways of communicating your message than labels in stacked bar charts. In fact, stacked charts aren't very effective as the bars (each Category) doesn't share an axis so comparison is hard.
It's almost always better to use two graphs in these instances, sharing a common axis. In your example I'm assuming that you want to show overall total and then the proportions each Category contributed in a given year.
library(grid)
library(gridExtra)
library(plyr)
# create a new column with proportions
prop <- function(x) x/sum(x)
Data <- ddply(Data,"Year",transform,Share=prop(Frequency))
# create the component graphics
totals <- ggplot(Data,aes(Year,Frequency)) + geom_bar(fill="darkseagreen",stat="identity") +
xlab("") + labs(title = "Frequency totals in given Year")
proportion <- ggplot(Data, aes(x=Year,y=Share, group=Category, colour=Category))
+ geom_line() + scale_y_continuous(label=percent_format())+ theme(legend.position = "bottom") +
labs(title = "Proportion of total Frequency accounted by each Category in given Year")
# bring them together
grid.arrange(totals,proportion)
This will give you a 2 panel display like this:
If you want to add Frequency values a table is the best format.
edited Jan 14 '17 at 5:48
DYZ
27.8k62150
answered Aug 9 '13 at 11:28
AndrewMinCHAndrewMinCH
52738
add a comment |
As hadley mentioned there are more effective ways of communicating your message than labels in stacked bar charts. In fact, stacked charts aren't very effective as the bars (each Category) doesn't share an axis so comparison is hard.
It's almost always better to use two graphs in these instances, sharing a common axis. In your example I'm assuming that you want to show overall total and then the proportions each Category contributed in a given year.
library(grid)
library(gridExtra)
library(plyr)
# create a new column with proportions
prop <- function(x) x/sum(x)
Data <- ddply(Data,"Year",transform,Share=prop(Frequency))
# create the component graphics
totals <- ggplot(Data,aes(Year,Frequency)) + geom_bar(fill="darkseagreen",stat="identity") +
xlab("") + labs(title = "Frequency totals in given Year")
proportion <- ggplot(Data, aes(x=Year,y=Share, group=Category, colour=Category))
+ geom_line() + scale_y_continuous(label=percent_format())+ theme(legend.position = "bottom") +
labs(title = "Proportion of total Frequency accounted by each Category in given Year")
# bring them together
grid.arrange(totals,proportion)
This will give you a 2 panel display like this:
If you want to add Frequency values a table is the best format.
edited Jan 14 '17 at 5:48
DYZ
27.8k62150
answered Aug 9 '13 at 11:28
AndrewMinCHAndrewMinCH
52738
add a comment |
As hadley mentioned there are more effective ways of communicating your message than labels in stacked bar charts. In fact, stacked charts aren't very effective as the bars (each Category) doesn't share an axis so comparison is hard.
It's almost always better to use two graphs in these instances, sharing a common axis. In your example I'm assuming that you want to show overall total and then the proportions each Category contributed in a given year.
library(grid)
library(gridExtra)
library(plyr)
# create a new column with proportions
prop <- function(x) x/sum(x)
Data <- ddply(Data,"Year",transform,Share=prop(Frequency))
# create the component graphics
totals <- ggplot(Data,aes(Year,Frequency)) + geom_bar(fill="darkseagreen",stat="identity") +
xlab("") + labs(title = "Frequency totals in given Year")
proportion <- ggplot(Data, aes(x=Year,y=Share, group=Category, colour=Category))
+ geom_line() + scale_y_continuous(label=percent_format())+ theme(legend.position = "bottom") +
labs(title = "Proportion of total Frequency accounted by each Category in given Year")
# bring them together
grid.arrange(totals,proportion)
This will give you a 2 panel display like this:
If you want to add Frequency values a table is the best format.
edited Jan 14 '17 at 5:48
DYZ
27.8k62150
answered Aug 9 '13 at 11:28
AndrewMinCHAndrewMinCH
52738
As hadley mentioned there are more effective ways of communicating your message than labels in stacked bar charts. In fact, stacked charts aren't very effective as the bars (each Category) doesn't share an axis so comparison is hard.
It's almost always better to use two graphs in these instances, sharing a common axis. In your example I'm assuming that you want to show overall total and then the proportions each Category contributed in a given year.
library(grid)
library(gridExtra)
library(plyr)
# create a new column with proportions
prop <- function(x) x/sum(x)
Data <- ddply(Data,"Year",transform,Share=prop(Frequency))
# create the component graphics
totals <- ggplot(Data,aes(Year,Frequency)) + geom_bar(fill="darkseagreen",stat="identity") +
xlab("") + labs(title = "Frequency totals in given Year")
proportion <- ggplot(Data, aes(x=Year,y=Share, group=Category, colour=Category))
+ geom_line() + scale_y_continuous(label=percent_format())+ theme(legend.position = "bottom") +
labs(title = "Proportion of total Frequency accounted by each Category in given Year")
# bring them together
grid.arrange(totals,proportion)
This will give you a 2 panel display like this:
If you want to add Frequency values a table is the best format.
edited Jan 14 '17 at 5:48
DYZ
27.8k62150
answered Aug 9 '13 at 11:28
AndrewMinCHAndrewMinCH
52738
edited Jan 14 '17 at 5:48
DYZ
27.8k62150
edited Jan 14 '17 at 5:48
DYZ
27.8k62150
edited Jan 14 '17 at 5:48
DYZ
27.8k62150
27.8k62150
answered Aug 9 '13 at 11:28
AndrewMinCHAndrewMinCH
52738
answered Aug 9 '13 at 11:28
AndrewMinCHAndrewMinCH
52738
answered Aug 9 '13 at 11:28
AndrewMinCHAndrewMinCH
52738
52738
add a comment |
add a comment |
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Related question: stackoverflow.com/questions/18994631/…
– Tyler Rinker
Sep 25 '13 at 1:48
Not really the place for a debate, but I wonder if it's possible to be overly prescriptive about this, particularly for the more general audience. This is a nice example - numbers denote percentages that can be remembered, which removes the need for a scale that less numerically-literate readers might find less accessible?
– geotheory
Jan 20 '15 at 12:04