facet_wrap Title wrapping & Decimal places on free_y axis (ggplot2) - r

I have a set of code that produces multiple plots using facet_wrap:
ggplot(summ,aes(x=depth,y=expr,colour=bank,group=bank)) +
geom_errorbar(aes(ymin=expr-se,ymax=expr+se),lwd=0.4,width=0.3,position=pd) +
geom_line(aes(group=bank,linetype=bank),position=pd) +
geom_point(aes(group=bank,pch=bank),position=pd,size=2.5) +
scale_colour_manual(values=c("coral","cyan3", "blue")) +
facet_wrap(~gene,scales="free_y") +
theme_bw()
With the reference datasets, this code produces figures like this:
I am trying to accomplish two goals here:
Keep the auto scaling of the y axis, but make sure only 1 decimal place is displayed across all the plots. I have tried creating a new column of the rounded expr values, but it causes the error bars to not line up properly.
I would like to wrap the titles. I have tried changing the font size as in Change plot title sizes in a facet_wrap multiplot, but some of the gene names are too long and will end up being too small to read if I cram them on a single line. Is there a way to wrap the text, using code within the facet_wrap statement?

Probably cannot serve as definite answer, but here are some pointers regarding your questions:
Formatting the y-axis scale labels.
First, let's try the direct solution using format function. Here we format all y-axis scale labels to have 1 decimal value, after rounding it with round.
formatter <- function(...){
function(x) format(round(x, 1), ...)
}
mtcars2 <- mtcars
sp <- ggplot(mtcars2, aes(x = mpg, y = qsec)) + geom_point() + facet_wrap(~cyl, scales = "free_y")
sp <- sp + scale_y_continuous(labels = formatter(nsmall = 1))
The issue is, sometimes this approach is not practical. Take the leftmost plot from your figure, for example. Using the same formatting, all y-axis scale labels would be rounded up to -0.3, which is not preferable.
The other solution is to modify the breaks for each plot into a set of rounded values. But again, taking the leftmost plot of your figure as an example, it'll end up with just one label point, -0.3
Yet another solution is to format the labels into scientific form. For simplicity, you can modify the formatter function as follow:
formatter <- function(...){
function(x) format(x, ..., scientific = T, digit = 2)
}
Now you can have a uniform format for all of plots' y-axis. My suggestion, though, is to set the label with 2 decimal places after rounding.
Wrap facet titles
This can be done using labeller argument in facet_wrap.
# Modify cyl into factors
mtcars2$cyl <- c("Four Cylinder", "Six Cylinder", "Eight Cylinder")[match(mtcars2$cyl, c(4,6,8))]
# Redraw the graph
sp <- ggplot(mtcars2, aes(x = mpg, y = qsec)) + geom_point() +
facet_wrap(~cyl, scales = "free_y", labeller = labeller(cyl = label_wrap_gen(width = 10)))
sp <- sp + scale_y_continuous(labels = formatter(nsmall = 2))
It must be noted that the wrap function detects space to separate labels into lines. So, in your case, you might need to modify your variables.

This only solved the first part of the question. You can create a function to format your axis and use scale_y_continous to adjust it.
df <- data.frame(x=rnorm(11), y1=seq(2, 3, 0.1) + 10, y2=rnorm(11))
library(ggplot2)
library(reshape2)
df <- melt(df, 'x')
# Before
ggplot(df, aes(x=x, y=value)) + geom_point() +
facet_wrap(~ variable, scale="free")
# label function
f <- function(x){
format(round(x, 1), nsmall=1)
}
# After
ggplot(df, aes(x=x, y=value)) + geom_point() +
facet_wrap(~ variable, scale="free") +
scale_y_continuous(labels=f)

scale_*_continuous(..., labels = function(x) sprintf("%0.0f", x)) worked in my case.

Related

Add data label to bar chart in R [duplicate]

I'd like to have some labels stacked on top of a geom_bar graph. Here's an example:
df <- data.frame(x=factor(c(TRUE,TRUE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE)))
ggplot(df) + geom_bar(aes(x,fill=x)) + opts(axis.text.x=theme_blank(),axis.ticks=theme_blank(),axis.title.x=theme_blank(),legend.title=theme_blank(),axis.title.y=theme_blank())
Now
table(df$x)
FALSE TRUE
3 5
I'd like to have the 3 and 5 on top of the two bars. Even better if I could have the percent values as well. E.g. 3 (37.5%) and 5 (62.5%). Like so:
(source: skitch.com)
Is this possible? If so, how?
To plot text on a ggplot you use the geom_text. But I find it helpful to summarise the data first using ddply
dfl <- ddply(df, .(x), summarize, y=length(x))
str(dfl)
Since the data is pre-summarized, you need to remember to change add the stat="identity" parameter to geom_bar:
ggplot(dfl, aes(x, y=y, fill=x)) + geom_bar(stat="identity") +
geom_text(aes(label=y), vjust=0) +
opts(axis.text.x=theme_blank(),
axis.ticks=theme_blank(),
axis.title.x=theme_blank(),
legend.title=theme_blank(),
axis.title.y=theme_blank()
)
As with many tasks in ggplot, the general strategy is to put what you'd like to add to the plot into a data frame in a way such that the variables match up with the variables and aesthetics in your plot. So for example, you'd create a new data frame like this:
dfTab <- as.data.frame(table(df))
colnames(dfTab)[1] <- "x"
dfTab$lab <- as.character(100 * dfTab$Freq / sum(dfTab$Freq))
So that the x variable matches the corresponding variable in df, and so on. Then you simply include it using geom_text:
ggplot(df) + geom_bar(aes(x,fill=x)) +
geom_text(data=dfTab,aes(x=x,y=Freq,label=lab),vjust=0) +
opts(axis.text.x=theme_blank(),axis.ticks=theme_blank(),
axis.title.x=theme_blank(),legend.title=theme_blank(),
axis.title.y=theme_blank())
This example will plot just the percentages, but you can paste together the counts as well via something like this:
dfTab$lab <- paste(dfTab$Freq,paste("(",dfTab$lab,"%)",sep=""),sep=" ")
Note that in the current version of ggplot2, opts is deprecated, so we would use theme and element_blank now.
Another solution is to use stat_count() when dealing with discrete variables (and stat_bin() with continuous ones).
ggplot(data = df, aes(x = x)) +
geom_bar(stat = "count") +
stat_count(geom = "text", colour = "white", size = 3.5,
aes(label = ..count..),position=position_stack(vjust=0.5))
So, this is our initial plot↓
library(ggplot2)
df <- data.frame(x=factor(c(TRUE,TRUE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE)))
p <- ggplot(df, aes(x = x, fill = x)) +
geom_bar()
p
As suggested by yuan-ning, we can use stat_count().
geom_bar() uses stat_count() by default. As mentioned in the ggplot2 reference, stat_count() returns two values: count for number of points in bin and prop for groupwise proportion. Since our groups match the x values, both props are 1 and aren’t useful. But we can use count (referred to as “..count..”) that actually denotes bar heights, in our geom_text(). Note that we must include “stat = 'count'” into our geom_text() call as well.
Since we want both counts and percentages in our labels, we’ll need some calculations and string pasting in our “label” aesthetic instead of just “..count..”. I prefer to add a line of code to create a wrapper percent formatting function from the “scales” package (ships along with “ggplot2”).
pct_format = scales::percent_format(accuracy = .1)
p <- p + geom_text(
aes(
label = sprintf(
'%d (%s)',
..count..,
pct_format(..count.. / sum(..count..))
)
),
stat = 'count',
nudge_y = .2,
colour = 'royalblue',
size = 5
)
p
Of course, you can further edit the labels with colour, size, nudges, adjustments etc.

How do I add label for each of my bar plot? [duplicate]

I'd like to have some labels stacked on top of a geom_bar graph. Here's an example:
df <- data.frame(x=factor(c(TRUE,TRUE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE)))
ggplot(df) + geom_bar(aes(x,fill=x)) + opts(axis.text.x=theme_blank(),axis.ticks=theme_blank(),axis.title.x=theme_blank(),legend.title=theme_blank(),axis.title.y=theme_blank())
Now
table(df$x)
FALSE TRUE
3 5
I'd like to have the 3 and 5 on top of the two bars. Even better if I could have the percent values as well. E.g. 3 (37.5%) and 5 (62.5%). Like so:
(source: skitch.com)
Is this possible? If so, how?
To plot text on a ggplot you use the geom_text. But I find it helpful to summarise the data first using ddply
dfl <- ddply(df, .(x), summarize, y=length(x))
str(dfl)
Since the data is pre-summarized, you need to remember to change add the stat="identity" parameter to geom_bar:
ggplot(dfl, aes(x, y=y, fill=x)) + geom_bar(stat="identity") +
geom_text(aes(label=y), vjust=0) +
opts(axis.text.x=theme_blank(),
axis.ticks=theme_blank(),
axis.title.x=theme_blank(),
legend.title=theme_blank(),
axis.title.y=theme_blank()
)
As with many tasks in ggplot, the general strategy is to put what you'd like to add to the plot into a data frame in a way such that the variables match up with the variables and aesthetics in your plot. So for example, you'd create a new data frame like this:
dfTab <- as.data.frame(table(df))
colnames(dfTab)[1] <- "x"
dfTab$lab <- as.character(100 * dfTab$Freq / sum(dfTab$Freq))
So that the x variable matches the corresponding variable in df, and so on. Then you simply include it using geom_text:
ggplot(df) + geom_bar(aes(x,fill=x)) +
geom_text(data=dfTab,aes(x=x,y=Freq,label=lab),vjust=0) +
opts(axis.text.x=theme_blank(),axis.ticks=theme_blank(),
axis.title.x=theme_blank(),legend.title=theme_blank(),
axis.title.y=theme_blank())
This example will plot just the percentages, but you can paste together the counts as well via something like this:
dfTab$lab <- paste(dfTab$Freq,paste("(",dfTab$lab,"%)",sep=""),sep=" ")
Note that in the current version of ggplot2, opts is deprecated, so we would use theme and element_blank now.
Another solution is to use stat_count() when dealing with discrete variables (and stat_bin() with continuous ones).
ggplot(data = df, aes(x = x)) +
geom_bar(stat = "count") +
stat_count(geom = "text", colour = "white", size = 3.5,
aes(label = ..count..),position=position_stack(vjust=0.5))
So, this is our initial plot↓
library(ggplot2)
df <- data.frame(x=factor(c(TRUE,TRUE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE)))
p <- ggplot(df, aes(x = x, fill = x)) +
geom_bar()
p
As suggested by yuan-ning, we can use stat_count().
geom_bar() uses stat_count() by default. As mentioned in the ggplot2 reference, stat_count() returns two values: count for number of points in bin and prop for groupwise proportion. Since our groups match the x values, both props are 1 and aren’t useful. But we can use count (referred to as “..count..”) that actually denotes bar heights, in our geom_text(). Note that we must include “stat = 'count'” into our geom_text() call as well.
Since we want both counts and percentages in our labels, we’ll need some calculations and string pasting in our “label” aesthetic instead of just “..count..”. I prefer to add a line of code to create a wrapper percent formatting function from the “scales” package (ships along with “ggplot2”).
pct_format = scales::percent_format(accuracy = .1)
p <- p + geom_text(
aes(
label = sprintf(
'%d (%s)',
..count..,
pct_format(..count.. / sum(..count..))
)
),
stat = 'count',
nudge_y = .2,
colour = 'royalblue',
size = 5
)
p
Of course, you can further edit the labels with colour, size, nudges, adjustments etc.

changing ggplot legend unit scale

This question is motivated by a previous post illustrating various ways to change how axes scales are plotted in a ggplot figure, from the default exponential notation to the full integer value (when ones axes values are very large). While I am able to convert the axes scales from exponential notation to full values, I am unclear how one would achieve the same goal for the values appearing in the legend.
While I understand that one can manually change the length of the legend scale with "scale_color..." or "scale_fill..." followed by the "limits" argument, this does not appear to be a solution to getting my legend values to show "6000000000" rather than "6e+09" (or "0" rather than "0e+00" for that matter).
The following example should suffice. My hope is someone can point out how to implement the 'scales' package to apply for legend scales rather than axes scales.
Thanks very much.
library(ggplot2)
library(scales)
Data <- data.frame(
pi = c(2,71,828,1828,45904,523536,2874713,52662497,757247093,6999595749),
e = c(3,14,159,2653,58979,311599,7963468,54418516,1590576171, 99),
face = 1:10)
p <- ggplot(data = Data, aes(x=face, y=e, colour = pi))
myplot <- p + geom_point() +
scale_y_continuous(labels = comma) +
scale_color_gradientn(colours = rainbow(2), limits=c(0,7000000000))
myplot
Use the Comma formatter in scale_color_gradientn by setting labels = comma e.g.:
p <- ggplot(data = Data, aes(x=face, y=e, colour = pi))
myplot <- p + geom_point() +
scale_y_continuous(labels = comma) +
scale_color_gradientn(colours = rainbow(2), limits=c(0,7000000000), labels = comma)
myplot

Line up columns of bar graph with points of line plot with ggplot

Is there any way to line up the points of a line plot with the bars of a bar graph using ggplot when they have the same x-axis? Here is the sample data I'm trying to do it with.
library(ggplot2)
library(gridExtra)
data=data.frame(x=rep(1:27, each=5), y = rep(1:5, times = 27))
yes <- ggplot(data, aes(x = x, y = y))
yes <- yes + geom_point() + geom_line()
other_data = data.frame(x = 1:27, y = 50:76 )
no <- ggplot(other_data, aes(x=x, y=y))
no <- no + geom_bar(stat = "identity")
grid.arrange(no, yes)
Here is the output:
The first point of the line plot is to the left of the first bar, and the last point of the line plot is to the right of the last bar.
Thank you for your time.
Extending #Stibu's post a little: To align the plots, use gtable (Or see answers to your earlier question)
library(ggplot2)
library(gtable)
data=data.frame(x=rep(1:27, each=5), y = rep(1:5, times = 27))
yes <- ggplot(data, aes(x = x, y = y))
yes <- yes + geom_point() + geom_line() +
scale_x_continuous(limits = c(0,28), expand = c(0,0))
other_data = data.frame(x = 1:27, y = 50:76 )
no <- ggplot(other_data, aes(x=x, y=y))
no <- no + geom_bar(stat = "identity") +
scale_x_continuous(limits = c(0,28), expand = c(0,0))
gYes = ggplotGrob(yes) # get the ggplot grobs
gNo = ggplotGrob(no)
plot(rbind(gNo, gYes, size = "first")) # Arrange and plot the grobs
Edit To change heights of plots:
g = rbind(gNo, gYes, size = "first") # Combine the plots
panels <- g$layout$t[grepl("panel", g$layout$name)] # Get the positions for plot panels
g$heights[panels] <- unit(c(0.7, 0.3), "null") # Replace heights with your relative heights
plot(g)
I can think of (at least) two ways to align the x-axes in the two plots:
The two axis do not align because in the bar plot, the geoms cover the x-axis from 0.5 to 27.5, while in the other plot, the data only ranges from 1 to 27. The reason is that the bars have a width and the points don't. You can force the axex to align by explicitly specifying an x-axis range. Using the definitions from your plot, this can be achieved by
yes <- yes + scale_x_continuous(limits=c(0,28))
no <- no + scale_x_continuous(limits=c(0,28))
grid.arrange(no, yes)
limits sets the range of the x-axis. Note, though, that the alginment is still not quite perfect. The y-axis labels take up a little more space in the upper plot, because the numbers have two digits. The plot looks as follows:
The other solution is a bit more complicated but it has the advantage that the x-axis is drawn only once and that ggplot makes sure that the alignment is perfect. It makes use of faceting and the trick described in this answer. First, the data must be combined into a single data frame by
all <- rbind(data.frame(other_data,type="other"),data.frame(data,type="data"))
and then the plot can be created as follows:
ggplot(all,aes(x=x,y=y)) + facet_grid(type~.,scales = "free_y") +
geom_bar(data=subset(all,type=="other"),stat="identity") +
geom_point(data=subset(all,type=="data")) +
geom_line(data=subset(all,type=="data"))
The trick is to let the facets be constructed by the variable type which was used before to label the two data sets. But then each geom only gets the subset of the data that should be drawn with that specific geom. In facet_grid, I also used scales = "free_y" because the two y-axes should be independent. This plot looks as follows:
You can change the labels of the facets by giving other names when you define the data frame all. If you want to remove them alltogether, then add the following to your plot:
+ theme(strip.background = element_blank(), strip.text = element_blank())

How to put labels over geom_bar in R with ggplot2

I'd like to have some labels stacked on top of a geom_bar graph. Here's an example:
df <- data.frame(x=factor(c(TRUE,TRUE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE)))
ggplot(df) + geom_bar(aes(x,fill=x)) + opts(axis.text.x=theme_blank(),axis.ticks=theme_blank(),axis.title.x=theme_blank(),legend.title=theme_blank(),axis.title.y=theme_blank())
Now
table(df$x)
FALSE TRUE
3 5
I'd like to have the 3 and 5 on top of the two bars. Even better if I could have the percent values as well. E.g. 3 (37.5%) and 5 (62.5%). Like so:
(source: skitch.com)
Is this possible? If so, how?
To plot text on a ggplot you use the geom_text. But I find it helpful to summarise the data first using ddply
dfl <- ddply(df, .(x), summarize, y=length(x))
str(dfl)
Since the data is pre-summarized, you need to remember to change add the stat="identity" parameter to geom_bar:
ggplot(dfl, aes(x, y=y, fill=x)) + geom_bar(stat="identity") +
geom_text(aes(label=y), vjust=0) +
opts(axis.text.x=theme_blank(),
axis.ticks=theme_blank(),
axis.title.x=theme_blank(),
legend.title=theme_blank(),
axis.title.y=theme_blank()
)
As with many tasks in ggplot, the general strategy is to put what you'd like to add to the plot into a data frame in a way such that the variables match up with the variables and aesthetics in your plot. So for example, you'd create a new data frame like this:
dfTab <- as.data.frame(table(df))
colnames(dfTab)[1] <- "x"
dfTab$lab <- as.character(100 * dfTab$Freq / sum(dfTab$Freq))
So that the x variable matches the corresponding variable in df, and so on. Then you simply include it using geom_text:
ggplot(df) + geom_bar(aes(x,fill=x)) +
geom_text(data=dfTab,aes(x=x,y=Freq,label=lab),vjust=0) +
opts(axis.text.x=theme_blank(),axis.ticks=theme_blank(),
axis.title.x=theme_blank(),legend.title=theme_blank(),
axis.title.y=theme_blank())
This example will plot just the percentages, but you can paste together the counts as well via something like this:
dfTab$lab <- paste(dfTab$Freq,paste("(",dfTab$lab,"%)",sep=""),sep=" ")
Note that in the current version of ggplot2, opts is deprecated, so we would use theme and element_blank now.
Another solution is to use stat_count() when dealing with discrete variables (and stat_bin() with continuous ones).
ggplot(data = df, aes(x = x)) +
geom_bar(stat = "count") +
stat_count(geom = "text", colour = "white", size = 3.5,
aes(label = ..count..),position=position_stack(vjust=0.5))
So, this is our initial plot↓
library(ggplot2)
df <- data.frame(x=factor(c(TRUE,TRUE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE)))
p <- ggplot(df, aes(x = x, fill = x)) +
geom_bar()
p
As suggested by yuan-ning, we can use stat_count().
geom_bar() uses stat_count() by default. As mentioned in the ggplot2 reference, stat_count() returns two values: count for number of points in bin and prop for groupwise proportion. Since our groups match the x values, both props are 1 and aren’t useful. But we can use count (referred to as “..count..”) that actually denotes bar heights, in our geom_text(). Note that we must include “stat = 'count'” into our geom_text() call as well.
Since we want both counts and percentages in our labels, we’ll need some calculations and string pasting in our “label” aesthetic instead of just “..count..”. I prefer to add a line of code to create a wrapper percent formatting function from the “scales” package (ships along with “ggplot2”).
pct_format = scales::percent_format(accuracy = .1)
p <- p + geom_text(
aes(
label = sprintf(
'%d (%s)',
..count..,
pct_format(..count.. / sum(..count..))
)
),
stat = 'count',
nudge_y = .2,
colour = 'royalblue',
size = 5
)
p
Of course, you can further edit the labels with colour, size, nudges, adjustments etc.

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