I'd like to remove the labels for the facets completely to create a sort of sparkline effect, as for the audience the labels are irrelevant, the best I can come up with is:
library(MASS)
library(ggplot2)
qplot(week,y,data=bacteria,group=ID, geom=c('point','line'), xlab='', ylab='') +
facet_wrap(~ID) +
theme(strip.text.x = element_text(size=0))
So can I get rid of the (now blank) strip.background completely to allow more space for the "sparklines"?
Or alternatively is there a better way to get this "sparkline" effect for a large number of binary valued time-series like this?
For ggplot v2.1.0 or higher, use element_blank() to remove unwanted elements:
library(MASS) # To get the data
library(ggplot2)
qplot(
week,
y,
data = bacteria,
group = ID,
geom = c('point', 'line'),
xlab = '',
ylab = ''
) +
facet_wrap(~ ID) +
theme(
strip.background = element_blank(),
strip.text.x = element_blank()
)
In this case, the element you're trying to remove is called strip.
Alternative using ggplot grob layout
In older versions of ggplot (before v2.1.0), the strip text occupies rows in the gtable layout.
element_blank removes the text and the background, but it does not remove the space that the row occupied.
This code removes those rows from the layout:
library(ggplot2)
library(grid)
p <- qplot(
week,
y,
data = bacteria,
group = ID,
geom = c('point', 'line'),
xlab = '',
ylab = ''
) +
facet_wrap(~ ID)
# Get the ggplot grob
gt <- ggplotGrob(p)
# Locate the tops of the plot panels
panels <- grep("panel", gt$layout$name)
top <- unique(gt$layout$t[panels])
# Remove the rows immediately above the plot panel
gt = gt[-(top-1), ]
# Draw it
grid.newpage()
grid.draw(gt)
I'm using ggplot2 version 1 and the commands required have changed.
Instead of
ggplot() ... +
opts(strip.background = theme_blank(), strip.text.x = theme_blank())
you now use
ggplot() ... +
theme(strip.background = element_blank(), strip.text = element_blank())
For more detail see http://docs.ggplot2.org/current/theme.html
Sandy's updated answer seems good but, possibly has been rendered obsolete by updates to ggplot? From what I can tell the following code (a simplified version of Sandy's original answer) reproduces Sean's original graph without any extra space:
library(ggplot2)
library(grid)
qplot(week,y,data=bacteria,group=ID, geom=c('point','line'), xlab='', ylab='') +
facet_wrap(~ID) +
theme(strip.text.x = element_blank())
I am using ggplot 2.0.0.
As near as I can tell, Sandy's answer is correct but I think it's worth mentioning that there seems to be a small difference the width of a plot with no facets and the width of a plot with the facets removed.
It isn't obvious unless you're looking for it but, if you stack plots using the viewport layouts that Wickham recommends in his book, the difference becomes apparent.
Related
I am trying to make a lollipop plot that includes a text 'condition' and a value associated. The issue I am having is that, because there is so much data, the labels overlap. Is there an easy fix for this?
This is my code (and my issue):
library(ggplot2)
df <- read.table(file = '24 hpi MP BP.tsv', sep = '\t', header = TRUE)
group <- df$Name
value <- df$Bgd.count
data <- data.frame(
x=group,
y=value
)
ggplot(data, aes(x=x, y=y)) +
geom_segment( aes(x=x, xend=x, y=0, yend=y), color="skyblue") +
geom_point( color="blue", size=4, alpha=0.6) +
theme_light() +
coord_flip() +
theme(
panel.grid.major.y = element_blank(),
panel.border = element_blank(),
axis.ticks.y = element_blank()
)
I am hoping to get a clear separation on the labels
Your question does not provide a reproducible example, so here a more general answer.
The problem is that you want to plot hundreds of discrete values. That is bound to yield a crowded graphic.
your options:
reduce the labels (don’t label all axis) and show only few labels .
focus only on few important data points - I think this would be my preferred approach, as you also give your “story” more justice.
Group your values and show “aggregate values” such as means/error bars
Make your graph appropriately large (change the height of the so called graphic device)
Use facets (but this will not really help with the crowding in all cases)
Shorten your labels
Make the font smaller
Last, but definitely not least, change your visualisation strategy.
I use R for most of my data analysis. Until now I used to export the results as a CSV and visualized them using Macs Numbers.
The reason: The Graphs are embeded in documents and there is a rather large border on the right side reserved for annotations (tufte handout style). Between the acutal text and the annotations column there is white space. The plot of the graphs needs to fit the width of text while the legend should be placed in the annotation column.
I would prefer to also create the plots within R for a better workflow and higher efficiency. Is it possible to create such a layout using plotting with R?
Here is an example of what I would like to achieve:
And here is some R Code as a starter:
library(tidyverse)
data <- midwest %>%
head(5) %>%
select(2,23:25) %>%
pivot_longer(cols=2:4,names_to="Variable", values_to="Percent") %>%
mutate(Variable=factor(Variable, levels=c("percbelowpoverty","percchildbelowpovert","percadultpoverty"),ordered=TRUE))
ggplot(data=data, mapping=aes(x=county, y=Percent, fill=Variable)) +
geom_col(position=position_dodge(width=0.85),width=0.8) +
labs(x="County") +
theme(text=element_text(size=9),
panel.background = element_rect(fill="white"),
panel.grid = element_line(color = "black",linetype="solid",size= 0.3),
panel.grid.minor = element_blank(),
panel.grid.major.x=element_blank(),
axis.line.x=element_line(color="black"),
axis.ticks= element_blank(),
legend.position = "right",
legend.title = element_blank(),
legend.box.spacing = unit(1.5,"cm") ) +
scale_y_continuous(breaks= seq(from=0, to=50,by=5),
limits=c(0,51),
expand=c(0,0)) +
scale_fill_manual(values = c("#CF232B","#942192","#000000"))
I know how to set a custom font, just left it out for easier saving.
Using ggsave
ggsave("Graph_with_R.jpeg",plot=last_plot(),device="jpeg",dpi=300, width=18, height=9, units="cm")
I get this:
This might resample the result aimed for in the actual case, but the layout and sizes do not fit exact. Also recognize the different text sizes between axis titles, legend and tick marks on y-axes. In addition I assume the legend width depends on the actual labels and is not fixed.
Update
Following the suggestion of tjebo I posted a follow-up question.
Can it be done? Yes. Is it convenient? No.
If you're working in ggplot2 you can translate the plot to a gtable, a sort of intermediate between the plot specifications and the actual drawing. This gtable, you can then manipulate, but is messy to work with.
First, we need to figure out where the relevant bits of our plot are in the gtable.
library(ggplot2)
library(gtable)
library(grid)
plt <- ggplot(mtcars, aes(factor(cyl), fill = factor(vs))) +
geom_bar(position = position_dodge2(preserve = "single"))
# Making gtable
gt <- ggplotGrob(plt)
gtable_show_layout(gt)
Then, we can make a new gtable with prespecified dimensions and place the bits of our old gtable into it.
# Making a new gtable
new <- gtable(widths = unit(c(12.5, 1.5, 4), "cm"),
heights = unit(9, "cm"))
# Adding main panel and axes in first cell
new <- gtable_add_grob(
new,
gt[7:9, 3:5], # If you see the layout above as a matrix, the main bits are in these rows/cols
t = 1, l = 1
)
# Finding the legend
legend <- gt$grobs[gt$layout$name == "guide-box"][[1]]
legend <- legend$grobs[legend$layout$name == "guides"][[1]]
# Adding legend in third cell
new <- gtable_add_grob(
new, legend, t = 1, l = 3
)
# Saving as raster
ragg::agg_png("test.png", width = 18, height = 9, units = "cm", res = 300)
grid.newpage(); grid.draw(new)
dev.off()
#> png
#> 2
Created on 2021-04-02 by the reprex package (v1.0.0)
The created figure should match the dimensions you're looking for.
Another option is to draw the three components as separate plots and stitch them together in the desired ratio.
The below comes quite close to the desired ratio, but not exactly. I guess you'd need to fiddle around with the values given the exact saving dimensions. In the example I used figure dimensions of 7x3.5 inches (which is similar to 18x9cm), and have added the black borders just to demonstrate the component limits.
library(tidyverse)
library(patchwork)
data <- midwest %>%
head(5) %>%
select(2,23:25) %>%
pivot_longer(cols=2:4,names_to="Variable", values_to="Percent") %>%
mutate(Variable=factor(Variable, levels=c("percbelowpoverty","percchildbelowpovert","percadultpoverty"),ordered=TRUE))
p1 <-
ggplot(data=data, mapping=aes(x=county, y=Percent, fill=Variable)) +
geom_col() +
scale_fill_manual(values = c("#CF232B","#942192","#000000"))
p_legend <- cowplot::get_legend(p1)
p_main <- p1 <-
ggplot(data=data, mapping=aes(x=county, y=Percent, fill=Variable)) +
geom_col(show.legend = FALSE) +
scale_fill_manual(values = c("#CF232B","#942192","#000000"))
p_main + plot_spacer() + p_legend +
plot_layout(widths = c(12.5, 1.5, 4)) &
theme(plot.margin = margin(),
plot.background = element_rect(colour = "black"))
Created on 2021-04-02 by the reprex package (v1.0.0)
update
My solution is only semi-satisfactory as pointed out by the OP. The problem is that one cannot (to my knowledge) define the position of the grob in the third panel.
Other ideas for workarounds:
One could determine the space needed for text (but this seems not so easy) and then to size the device accordingly
Create a fake legend - however, this requires the tiles / text to be aligned to the left with no margin, and this can very quickly become very hacky.
In short, I think teunbrand's solution is probably the most straight forward one.
Update 2
The problem with the left alignment should be fixed with Stefan's suggestion in this thread
I am trying to label the ticks on the x-axis using the following line of code:
scale_x_discrete("Results of the urine culture", labels=c(expression("<"~10^4~"CFU/ml"), expression(10^4~"-"~10^5~"CFU/ml"), expression(">"~10^6~"CFU/ml")))
The graph returns with the same value (the first in the expression, i.e. "<10^4 CFU/ml") for all three ticks. I have tried to find an answer using search but did not find the description of this problem. Could you please point out what is wrong with this code?
Thanks in advance.
Edit
DF %>%mutate(count=paste("N=", count, sep="")) %>%
group_by(uc.res) %>%
ggplot(mapping = aes(x = uc.res, y = tts.0)) +
geom_boxplot()+
scale_x_discrete("Results of the urine culture",
labels=c(expression("<"~10^4~"CFU/ml"), expression(10^4~"-"~10^5~"CFU/ml"), expression(">"~10^6~"CFU/ml")))+
facet_grid(~count, switch="y", space = "free_x", scales = "free_x")+
theme(panel.spacing = unit(0, "lines"), strip.background = element_blank(), strip.placement = "outside")
Dear all problem was in the line
facet_grid(~count, switch="y", space = "free_x", scales = "free_x")
But if I remove it, I lose the number of cases in each group, that I would like to avoid.
Update: Well, I have found the solution. I have removed the line with facet_grid and added some modifications to keep these numbers at the top of the graph. First, I tried to duplicate the x-axis using sec_axis to add the numbers of patients in each group on the secondary axis. But doesn't work because the x-axis was discrete and sec_axis works only with continuous axes. Then, I have tried simple geom_text, adding some modifications with coord_cartesian and plot.margin. So, the added modifications are:
+geom_text(aes(label=count, y=Inf), vjust=-0.5, size=5)+
coord_cartesian(clip = "off")+
theme(plot.margin = margin(20,15,15,15, unit = "pt"))
I am trying to write a script that produces four different plots in a single image. Specifically, I want to recreate this graphic as closely as possible:
My current script produces four plots similar to these but I cannot figure out how to allocate screen real-estate accordingly. I want to:
modify the height and width of the plots so that all four have uniform width, one is substantially taller than the others which have uniform height among them
define the position of the legends by coordinates so that I can use screen space effectively
modify the overall shape of my image explicitly as needed (maybe I will need it closer to square-shaped at some point)
GENERATE SOME DATA TO PLOT
pt_id = c(1:279) # DEFINE PATIENT IDs
smoke = rbinom(279,1,0.5) # DEFINE SMOKING STATUS
hpv = rbinom(279,1,0.3) # DEFINE HPV STATUS
data = data.frame(pt_id, smoke, hpv) # PRODUCE DATA FRAME
ADD ANATOMICAL SITE DATA
data$site = sample(1:4, 279, replace = T)
data$site[data$site == 1] = "Hypopharynx"
data$site[data$site == 2] = "Larynx"
data$site[data$site == 3] = "Oral Cavity"
data$site[data$site == 4] = "Oropharynx"
data$site_known = 1 # HACK TO FACILITATE PRODUCING BARPLOTS
ADD MUTATION FREQUENCY DATA
data$freq = sample(1:1000, 279, replace = F)
DEFINE BARPLOT
require(ggplot2)
require(gridExtra)
bar = ggplot(data, aes(x = pt_id, y = freq)) + geom_bar(stat = "identity") + theme(axis.title.x = element_blank(), axis.ticks.x = element_blank(), axis.text.x = element_blank()) + ylab("Number of Mutations")
# DEFINE BINARY PLOTS
smoke_status = ggplot(data, aes(x=pt_id, y=smoke, fill = "red")) + geom_bar(stat="identity") + theme(legend.position = "none", axis.title.x = element_blank(), axis.ticks.x = element_blank(), axis.text.x = element_blank()) + ylab("Smoking Status")
hpv_status = ggplot(data, aes(x=pt_id, y = hpv, fill = "red")) + geom_bar(stat="identity") + theme(legend.position = "none", axis.title.x = element_blank(), axis.ticks.x = element_blank(), axis.text.x = element_blank()) + ylab("HPV Status")
site_status = ggplot(data, aes(x=pt_id, y=site_known, fill = site)) + geom_bar(stat="identity")
PRODUCE FOUR GRAPHS TOGETHER
grid.arrange(bar, smoke_status, hpv_status, site_status, nrow = 4)
I suspect that the functions needed to accomplish these tasks are already included in ggplot2 and gridExtra but I have not been able to figure out how. Also, if any of my code is excessively verbose or there is a simpler, more-elegant way to do what I have already done - please feel free to comment on that as well.
Here are the steps to get the layout you describe:
1) Extract the legend as a separate grob ("graphical object"). We can then lay out the legend separately from the plots.
2) Left-align the edges of the four plots so that the left edges and the x-scales line up properly. The code to do that comes from this SO answer. That answer has a function to align an arbitrary number of plots, but I wasn't able to get that to work when I also wanted to change the proportional space allotted to each plot, so I ended up doing it the "long way" by adjusting each plot separately.
3) Lay out the plots and the legend using grid.arrange and arrangeGrob. The heights argument allocates different proportions of the total vertical space to each plot. We also use the widths argument to allocate horizontal space to the plots in one wide column and the legend in another narrow column.
4) Plot to a device in whatever size you desire. This is how you get a particular shape or aspect ratio.
library(gridExtra)
library(grid)
# Function to extract the legend from a ggplot graph as a separate grob
# Source: https://stackoverflow.com/a/12539820/496488
get_leg = function(a.gplot){
tmp <- ggplot_gtable(ggplot_build(a.gplot))
leg <- which(sapply(tmp$grobs, function(x) x$name) == "guide-box")
legend <- tmp$grobs[[leg]]
legend
}
# Get legend as a separate grob
leg = get_leg(site_status)
# Add a theme element to change the plot margins to remove white space between the plots
thm = theme(plot.margin=unit(c(0,0,-0.5,0),"lines"))
# Left-align the four plots
# Adapted from: https://stackoverflow.com/a/13295880/496488
gA <- ggplotGrob(bar + thm)
gB <- ggplotGrob(smoke_status + thm)
gC <- ggplotGrob(hpv_status + thm)
gD <- ggplotGrob(site_status + theme(plot.margin=unit(c(0,0,0,0), "lines")) +
guides(fill=FALSE))
maxWidth = grid::unit.pmax(gA$widths[2:5], gB$widths[2:5], gC$widths[2:5], gD$widths[2:5])
gA$widths[2:5] <- as.list(maxWidth)
gB$widths[2:5] <- as.list(maxWidth)
gC$widths[2:5] <- as.list(maxWidth)
gD$widths[2:5] <- as.list(maxWidth)
# Lay out plots and legend
p = grid.arrange(arrangeGrob(gA,gB,gC,gD, heights=c(0.5,0.15,0.15,0.21)),
leg, ncol=2, widths=c(0.8,0.2))
You can then determine the shape or aspect ratio of the final plot by setting the parameters of the output device. (You may have to adjust font sizes when you create the underlying plots in order to get the final layout to look the way you want it.) The plot pasted in below is a png saved directly from the RStudio graph window. Here's how you would save the plot as PDF file (but there are many other "devices" you can use (e.g., png, jpeg, etc.) to save in different formats):
pdf("myPlot.pdf", width=10, height=5)
p
dev.off()
You also asked about more efficient code. One thing you can do is create a list of plot elements that you use multiple times and then just add the name of the list object to each plot. For example:
my_gg = list(geom_bar(stat="identity", fill="red"),
theme(legend.position = "none",
axis.title.x = element_blank(),
axis.ticks.x = element_blank(),
axis.text.x = element_blank()),
plot.margin = unit(c(0,0,-0.5,0), "lines"))
smoke_status = ggplot(data, aes(x=pt_id, y=smoke)) +
labs(y="Smoking Status") +
my_gg
I am trying to plot a heat map with ggplot2 and I would like to resize the colorbar and increase the font.
Here is the relevant part of the code:
g <- ggplot(data=melt.m)
g2 <- g+geom_rect(aes(xmin=colInd-1, xmax=colInd,
ymin=rowInd-1, ymax=rowInd, fill=value))
g2 <- g2+scale_x_continuous('beta', breaks=c(1, ceiling(cols/2), rows)-0.5,
labels=c(1,ceiling(cols/2), rows))
g2 <- g2+scale_y_continuous('alpha', breaks=c(1, ceiling(rows/2), rows)-0.5,
labels=c(1, ceiling(rows/2), rows))
g2 <- g2+opts(panel.grid.minor=theme_line(colour=NA),
panel.grid.major=theme_line(colour=NA),
panel.background=theme_rect(fill=NA, colour=NA),
axis.text.x=theme_text(size=30),
axis.text.y=theme_text(size=30, angle=90),
axis.title.x=theme_text(size=30),
axis.title.y=theme_text(size=30, angle=90), title = title)
heatscale <- c(low='ghostwhite', high='steelblue')
g2 <- g2+scale_fill_gradient("", heatscale[1], heatscale[2], bias = 10)
It works fine, the problem is that the color legend on the right side is too small. Is there a way to make the color legend bigger and increase the font size of the legend?
Thanks,
kz
We don't have your melt.m data, so the code you give is not reproducible. Using the diamonds dataset that comes with ggplot2 as an example, though:
ggplot(diamonds, aes(x=table, y=price)) +
geom_bin2d() +
scale_fill_gradient("", 'ghostwhite', 'steelblue', bias=10) +
opts(legend.key.width=unit(1, "in"),
legend.text = theme_text(size=30))
legend.key.width and legend.text are what you are looking for. I have used exaggerated sizes to make it more obvious.
For more details on the options available, see https://github.com/hadley/ggplot2/wiki/+opts%28%29-List
I tried this and found that R or ggplot2 have changed in the last four years. It yielded the error:
Error: 'opts' is deprecated. Use 'theme' instead. (Defunct; last used in version 0.9.1)
Was able to get it to work with the following instead:
p + theme(legend.text = element_text(size=30),legend.key.size = unit(1, "in"))
Initially tried just changing the text size but had to change the key size with it or it becomes unreadable. Also, unit needs a library explicitly loaded with library(grid)