How might the angle of x-axis labels follow the same angle as the outer x-axis using the coor_polar projection in ggplot? This is similar to rotate x-axis text in ggplot2 when using coord_polar(), but I don't understand the math well enough to adapt it. I found a trial-and-error solution below that sort of works, where angle = c(c(1:3)*c(-14,-22.3,-22),-90,c(3:1)*c(22,22.3,14),c(1:3)*c(-14,-22.3,-22),90,c(3:1)*c(22,22.3,14)). It would also be okay for the x-axis labels to rotate in the same direction all the way around. If all else fails, I might give up on rotating the labels and just add a second legend, as in Two legends for polar ggplot (with one customized). Thanks for the help!
require(ggplot2)
df.test <- data.frame(Names=c("name01", "name02", "name03", "name04", "name05", "name06", "name07", "name08", "name09", "name10", "name11", "name12", "name13", "name14"),Values=rep(1,24))
p <- ggplot(df.test, aes(Names, fill=Values))
p + coord_polar(theta="x", direction=1) +
geom_bar(stat="bin", colour="gray", alpha=.7) +
theme(axis.text.x = element_text(angle = c(c(1:3)*c(-14,-22.3,-22),-90,c(3:1)*c(22,22.3,14),c(1:3)*c(-14,-22.3,-22),90,c(3:1)*c(22,22.3,14))))
I'm not exactly clear what your goal is but see if this answers the question:
+ theme(axis.text.x = element_text(angle =
360/(2*pi)*rev( seq( pi/14, 2*pi-pi/14, len=14))))
That would make the names "tangential" to the splits. If you wanted them "perpendicular" (as in the illustration in the linked answer) you just add pi/2 radians to the angle. (Didn't we all take geometry in high school?)
+ theme(axis.text.x = element_text(angle =
360/(2*pi)*rev( pi/2 + seq( pi/14, 2*pi-pi/14, len=14))))
(BTW: The data argument that you specified had an error. I changed "24" to "14".)
Let me know if the first 7 labels look right, but you want the ones on the LHS of the figure flipped.
So you want the bottom 6 rotated by pi radians (=pi*360/2*pi degrees):
+theme(axis.text.x = element_text(angle = 360/(2*pi)*rev(
seq(pi/14,2*pi-pi/14, len=14))+
360/(2*pi)*c( rep(0, 4),rep(pi,6), rep(0,4)) ))
# the rotation "back" of the lower items
(I really do not understand the decision to use degrees rather than radians.)
Here's a small example how the solution of #42- could be implemented. Would have been useful for me.
mtcars$gear <- factor(mtcars$gear)
mtcars$cyl <- factor(mtcars$cyl)
ax <- length(unique(mtcars$gear))
ggplot(mtcars, aes(x = gear, y = cyl)) +
geom_point() +
coord_polar() +
theme(
axis.text.x = element_text(
angle = 360/(2*pi)*rev(seq(pi/ax,2*pi-pi/ax, len=ax)) + 360/(2*pi)*c(rep(0, round(ax/3)),rep(pi,ax-2*round(ax/3)), rep(0,round(ax/3)))
)
) +
scale_y_discrete(
breaks = levels(mtcars$cyl),
limits = c(" ", levels(mtcars$cyl))
)
Related
I have a plot where the x-axis is a factor whose labels are long. While probably not an ideal visualization, for now I'd like to simply rotate these labels to be vertical. I've figured this part out with the code below, but as you can see, the labels aren't totally visible.
data(diamonds)
diamonds$cut <- paste("Super Dee-Duper",as.character(diamonds$cut))
q <- qplot(cut,carat,data=diamonds,geom="boxplot")
q + opts(axis.text.x=theme_text(angle=-90))
Change the last line to
q + theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust=1))
By default, the axes are aligned at the center of the text, even when rotated. When you rotate +/- 90 degrees, you usually want it to be aligned at the edge instead:
The image above is from this blog post.
Use coord_flip()
data(diamonds)
diamonds$cut <- paste("Super Dee-Duper",as.character(diamonds$cut))
qplot(cut, carat, data = diamonds, geom = "boxplot") +
coord_flip()
Add str_wrap()
# wrap text to no more than 15 spaces
library(stringr)
diamonds$cut2 <- str_wrap(diamonds$cut, width = 15)
qplot(cut2, carat, data = diamonds, geom = "boxplot") +
coord_flip()
In Ch 3.9 of R for Data Science, Wickham and Grolemund speak to this exact question:
coord_flip() switches the x and y axes. This is useful (for example), if you want horizontal boxplots. It’s also useful for long labels: it’s hard to get them to fit without overlapping on the x-axis.
ggplot 3.3.0 fixes this by providing guide_axis(angle = 90) (as guide argument to scale_.. or as x argument to guides):
library(ggplot2)
data(diamonds)
diamonds$cut <- paste("Super Dee-Duper", as.character(diamonds$cut))
ggplot(diamonds, aes(cut, carat)) +
geom_boxplot() +
scale_x_discrete(guide = guide_axis(angle = 90)) +
# ... or, equivalently:
# guides(x = guide_axis(angle = 90)) +
NULL
From the documentation of the angle argument:
Compared to setting the angle in theme() / element_text(), this also
uses some heuristics to automatically pick the hjust and vjust that
you probably want.
Alternatively, it also provides guide_axis(n.dodge = 2) (as guide argument to scale_.. or as x argument to guides) to overcome the over-plotting problem by dodging the labels vertically. It works quite well in this case:
library(ggplot2)
data(diamonds)
diamonds$cut <- paste("Super Dee-Duper",as.character(diamonds$cut))
ggplot(diamonds, aes(cut, carat)) +
geom_boxplot() +
scale_x_discrete(guide = guide_axis(n.dodge = 2)) +
NULL
To make the text on the tick labels fully visible and read in the same direction as the y-axis label, change the last line to
q + theme(axis.text.x=element_text(angle=90, hjust=1))
I'd like to provide an alternate solution, a robust solution similar to what I am about to propose was required in the latest version of ggtern, since introducing the canvas rotation feature.
Basically, you need to determine the relative positions using trigonometry, by building a function which returns an element_text object, given angle (ie degrees) and positioning (ie one of x,y,top or right) information.
#Load Required Libraries
library(ggplot2)
library(gridExtra)
#Build Function to Return Element Text Object
rotatedAxisElementText = function(angle,position='x'){
angle = angle[1];
position = position[1]
positions = list(x=0,y=90,top=180,right=270)
if(!position %in% names(positions))
stop(sprintf("'position' must be one of [%s]",paste(names(positions),collapse=", ")),call.=FALSE)
if(!is.numeric(angle))
stop("'angle' must be numeric",call.=FALSE)
rads = (angle - positions[[ position ]])*pi/180
hjust = 0.5*(1 - sin(rads))
vjust = 0.5*(1 + cos(rads))
element_text(angle=angle,vjust=vjust,hjust=hjust)
}
Frankly, in my opinion, I think that an 'auto' option should be made available in ggplot2 for the hjust and vjust arguments, when specifying the angle, anyway, lets demonstrate how the above works.
#Demonstrate Usage for a Variety of Rotations
df = data.frame(x=0.5,y=0.5)
plots = lapply(seq(0,90,length.out=4),function(a){
ggplot(df,aes(x,y)) +
geom_point() +
theme(axis.text.x = rotatedAxisElementText(a,'x'),
axis.text.y = rotatedAxisElementText(a,'y')) +
labs(title = sprintf("Rotated %s",a))
})
grid.arrange(grobs=plots)
Which produces the following:
The ggpubr package offers a shortcut that does the right thing by default (right align text, middle align text box to tick):
library(ggplot2)
diamonds$cut <- paste("Super Dee-Duper", as.character(diamonds$cut))
q <- qplot(cut, carat, data = diamonds, geom = "boxplot")
q + ggpubr::rotate_x_text()
Created on 2018-11-06 by the reprex package (v0.2.1)
Found with a GitHub search for the relevant argument names: https://github.com/search?l=R&q=element_text+angle+90+vjust+org%3Acran&type=Code
OUTDATED - see this answer for a simpler approach
To obtain readable x tick labels without additional dependencies, you want to use:
... +
theme(axis.text.x = element_text(angle = 90, hjust = 1, vjust = 0.5)) +
...
This rotates the tick labels 90° counterclockwise and aligns them vertically at their end (hjust = 1) and their centers horizontally with the corresponding tick mark (vjust = 0.5).
Full example:
library(ggplot2)
data(diamonds)
diamonds$cut <- paste("Super Dee-Duper",as.character(diamonds$cut))
q <- qplot(cut,carat,data=diamonds,geom="boxplot")
q + theme(axis.text.x = element_text(angle = 90, hjust = 1, vjust = 0.5))
Note, that vertical/horizontal justification parameters vjust/hjust of element_text are relative to the text. Therefore, vjust is responsible for the horizontal alignment.
Without vjust = 0.5 it would look like this:
q + theme(axis.text.x = element_text(angle = 90, hjust = 1))
Without hjust = 1 it would look like this:
q + theme(axis.text.x = element_text(angle = 90, vjust = 0.5))
If for some (wired) reason you wanted to rotate the tick labels 90° clockwise (such that they can be read from the left) you would need to use: q + theme(axis.text.x = element_text(angle = -90, vjust = 0.5, hjust = -1)).
All of this has already been discussed in the comments of this answer but I come back to this question so often, that I want an answer from which I can just copy without reading the comments.
An alternative to coord_flip() is to use the ggstance package.
The advantage is that it makes it easier to combine the graphs with other graph types and you can, maybe more importantly, set fixed scale ratios for your coordinate system.
library(ggplot2)
library(ggstance)
diamonds$cut <- paste("Super Dee-Duper", as.character(diamonds$cut))
ggplot(data=diamonds, aes(carat, cut)) + geom_boxploth()
Created on 2020-03-11 by the reprex package (v0.3.0)
Also with ggplot2 3.3+, we can make horizontal plots without coord_flip() as it supports bi-directional geoms, simply swapping x and y axis. https://cmdlinetips.com/2020/03/ggplot2-2-3-0-is-here-two-new-features-you-must-know/
I have a plot where the x-axis is a factor whose labels are long. While probably not an ideal visualization, for now I'd like to simply rotate these labels to be vertical. I've figured this part out with the code below, but as you can see, the labels aren't totally visible.
data(diamonds)
diamonds$cut <- paste("Super Dee-Duper",as.character(diamonds$cut))
q <- qplot(cut,carat,data=diamonds,geom="boxplot")
q + opts(axis.text.x=theme_text(angle=-90))
Change the last line to
q + theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust=1))
By default, the axes are aligned at the center of the text, even when rotated. When you rotate +/- 90 degrees, you usually want it to be aligned at the edge instead:
The image above is from this blog post.
Use coord_flip()
data(diamonds)
diamonds$cut <- paste("Super Dee-Duper",as.character(diamonds$cut))
qplot(cut, carat, data = diamonds, geom = "boxplot") +
coord_flip()
Add str_wrap()
# wrap text to no more than 15 spaces
library(stringr)
diamonds$cut2 <- str_wrap(diamonds$cut, width = 15)
qplot(cut2, carat, data = diamonds, geom = "boxplot") +
coord_flip()
In Ch 3.9 of R for Data Science, Wickham and Grolemund speak to this exact question:
coord_flip() switches the x and y axes. This is useful (for example), if you want horizontal boxplots. It’s also useful for long labels: it’s hard to get them to fit without overlapping on the x-axis.
ggplot 3.3.0 fixes this by providing guide_axis(angle = 90) (as guide argument to scale_.. or as x argument to guides):
library(ggplot2)
data(diamonds)
diamonds$cut <- paste("Super Dee-Duper", as.character(diamonds$cut))
ggplot(diamonds, aes(cut, carat)) +
geom_boxplot() +
scale_x_discrete(guide = guide_axis(angle = 90)) +
# ... or, equivalently:
# guides(x = guide_axis(angle = 90)) +
NULL
From the documentation of the angle argument:
Compared to setting the angle in theme() / element_text(), this also
uses some heuristics to automatically pick the hjust and vjust that
you probably want.
Alternatively, it also provides guide_axis(n.dodge = 2) (as guide argument to scale_.. or as x argument to guides) to overcome the over-plotting problem by dodging the labels vertically. It works quite well in this case:
library(ggplot2)
data(diamonds)
diamonds$cut <- paste("Super Dee-Duper",as.character(diamonds$cut))
ggplot(diamonds, aes(cut, carat)) +
geom_boxplot() +
scale_x_discrete(guide = guide_axis(n.dodge = 2)) +
NULL
To make the text on the tick labels fully visible and read in the same direction as the y-axis label, change the last line to
q + theme(axis.text.x=element_text(angle=90, hjust=1))
I'd like to provide an alternate solution, a robust solution similar to what I am about to propose was required in the latest version of ggtern, since introducing the canvas rotation feature.
Basically, you need to determine the relative positions using trigonometry, by building a function which returns an element_text object, given angle (ie degrees) and positioning (ie one of x,y,top or right) information.
#Load Required Libraries
library(ggplot2)
library(gridExtra)
#Build Function to Return Element Text Object
rotatedAxisElementText = function(angle,position='x'){
angle = angle[1];
position = position[1]
positions = list(x=0,y=90,top=180,right=270)
if(!position %in% names(positions))
stop(sprintf("'position' must be one of [%s]",paste(names(positions),collapse=", ")),call.=FALSE)
if(!is.numeric(angle))
stop("'angle' must be numeric",call.=FALSE)
rads = (angle - positions[[ position ]])*pi/180
hjust = 0.5*(1 - sin(rads))
vjust = 0.5*(1 + cos(rads))
element_text(angle=angle,vjust=vjust,hjust=hjust)
}
Frankly, in my opinion, I think that an 'auto' option should be made available in ggplot2 for the hjust and vjust arguments, when specifying the angle, anyway, lets demonstrate how the above works.
#Demonstrate Usage for a Variety of Rotations
df = data.frame(x=0.5,y=0.5)
plots = lapply(seq(0,90,length.out=4),function(a){
ggplot(df,aes(x,y)) +
geom_point() +
theme(axis.text.x = rotatedAxisElementText(a,'x'),
axis.text.y = rotatedAxisElementText(a,'y')) +
labs(title = sprintf("Rotated %s",a))
})
grid.arrange(grobs=plots)
Which produces the following:
The ggpubr package offers a shortcut that does the right thing by default (right align text, middle align text box to tick):
library(ggplot2)
diamonds$cut <- paste("Super Dee-Duper", as.character(diamonds$cut))
q <- qplot(cut, carat, data = diamonds, geom = "boxplot")
q + ggpubr::rotate_x_text()
Created on 2018-11-06 by the reprex package (v0.2.1)
Found with a GitHub search for the relevant argument names: https://github.com/search?l=R&q=element_text+angle+90+vjust+org%3Acran&type=Code
OUTDATED - see this answer for a simpler approach
To obtain readable x tick labels without additional dependencies, you want to use:
... +
theme(axis.text.x = element_text(angle = 90, hjust = 1, vjust = 0.5)) +
...
This rotates the tick labels 90° counterclockwise and aligns them vertically at their end (hjust = 1) and their centers horizontally with the corresponding tick mark (vjust = 0.5).
Full example:
library(ggplot2)
data(diamonds)
diamonds$cut <- paste("Super Dee-Duper",as.character(diamonds$cut))
q <- qplot(cut,carat,data=diamonds,geom="boxplot")
q + theme(axis.text.x = element_text(angle = 90, hjust = 1, vjust = 0.5))
Note, that vertical/horizontal justification parameters vjust/hjust of element_text are relative to the text. Therefore, vjust is responsible for the horizontal alignment.
Without vjust = 0.5 it would look like this:
q + theme(axis.text.x = element_text(angle = 90, hjust = 1))
Without hjust = 1 it would look like this:
q + theme(axis.text.x = element_text(angle = 90, vjust = 0.5))
If for some (wired) reason you wanted to rotate the tick labels 90° clockwise (such that they can be read from the left) you would need to use: q + theme(axis.text.x = element_text(angle = -90, vjust = 0.5, hjust = -1)).
All of this has already been discussed in the comments of this answer but I come back to this question so often, that I want an answer from which I can just copy without reading the comments.
An alternative to coord_flip() is to use the ggstance package.
The advantage is that it makes it easier to combine the graphs with other graph types and you can, maybe more importantly, set fixed scale ratios for your coordinate system.
library(ggplot2)
library(ggstance)
diamonds$cut <- paste("Super Dee-Duper", as.character(diamonds$cut))
ggplot(data=diamonds, aes(carat, cut)) + geom_boxploth()
Created on 2020-03-11 by the reprex package (v0.3.0)
Also with ggplot2 3.3+, we can make horizontal plots without coord_flip() as it supports bi-directional geoms, simply swapping x and y axis. https://cmdlinetips.com/2020/03/ggplot2-2-3-0-is-here-two-new-features-you-must-know/
I'm having some issues with ggplot2 and y axis tick marks - if someone can provide any input I'd really appreciate it.
I'm trying to create a 'stacked' plot with independent y axis for publication I'm working on. The idea is to have N plots stacked with a common X axis but distinct Y axes for each subplot while making it seem like a single contiguous plot.
I would like inverted tick marks on the x axis (for the bottom most subplot) and all the y axes. Problem is while the tick marks show up on the yaxis breifly in the plot generation they seem to be overwritten at the last stage and become invisible. Its such a minor thing and I could just leave them off but I'd really like to know what is going on for my own sanity...
Below is some sample code that should reproduce the problem and here is an imgur link highlighting the plot style and missing tick marks.
On a tangent, if anyone knows how to customize the axis.line.y.right / axis.line.x.top without using a dummy 'second axis' let me know (it seems a very verbose way of doing something that should be simple).
Thanks for your help
ylim=c(-5,5)
xlim=c(3,12)
ybreaks=c(-2,2)
base <- ggplot() +
theme_bw() +
scale_y_continuous(limits=ylim, breaks=ybreaks) +
scale_x_continuous(limits=xlim) +
labs(x="", y="") +
theme( panel.grid.major=element_line("gray78",0.5,1),
panel.border=element_blank(),
axis.text.x=element_blank(),
axis.text.y=element_text(margin=unit(c(0,3,0,0), "mm")))
bottom <- base + xlab("xlab") +
theme( axis.ticks.length.y=unit(-2,"mm"),
axis.ticks.length.x=unit(-2,"mm"),
axis.line.y=element_line(),
axis.line.x=element_line(),
plot.margin=unit(c(0,5,5,5),"mm"),
axis.text.x=element_text(margin=unit(c(3,0,0,0), "mm")))
middle <- base +
theme( axis.ticks.length.y=unit(-2,"mm"),
axis.ticks.length.x=unit(0,"mm"),
axis.line.y=element_line(),
axis.line.x=element_line(linetype=3),
plot.margin=unit(c(0,5,0,5),"mm"),
axis.title=element_blank())
top <- base +
theme( axis.ticks.length.y=unit(-2,"mm"),
axis.ticks.length.x=unit(0,"mm"),
axis.line.y=element_line(),
axis.line.x=element_line(linetype=3),
plot.margin=unit(c(5,5,0,5),"mm"),
axis.title=element_blank())
ggarrange(top,middle,bottom,ncol=1)
The easiest and more ggplot-y way would be to use facets.
I recommend using labs(x=NULL, y=NULL), because using = '' actually is drawing something.
I am removing the facet strips in the plot, but I generally think your graph may be slightly less confusing when you keep the labels and also keep a bit of distance between those graphs.
In order to add the dashed lines between your facets, you could simply add annotations, e.g., with annotate(geom = 'segment')
library(ggplot2)
ylim=c(-5,5)
xlim=c(3,12)
ybreaks=c(-2,2)
ggplot(data.frame(facet = letters[1:3])) +
theme_bw() +
annotate(geom = 'segment', x = -Inf, xend = Inf, y = -Inf, yend = -Inf, linetype = 3)+
scale_y_continuous(limits=ylim, breaks=ybreaks) +
scale_x_continuous(limits=xlim) +
labs(x=NULL, y=NULL) +
theme( panel.grid.major=element_line("gray78",0.5,1),
panel.border=element_blank(),
axis.text.x=element_blank(),
axis.text.y=element_text(margin=unit(c(0,3,0,0), "mm")),
panel.spacing = unit(0, "lines"),
strip.background = element_blank(),
strip.text = element_blank(),axis.line.y=element_line(),
axis.line.x=element_line(),
axis.ticks.length.y=unit(-2,"mm"),
axis.ticks.length.x=unit(-2,"mm"),
plot.margin=unit(c(b = 5, t = 5, r = 5, l = 5),"mm")) +
facet_wrap(~facet, nrow = 3)
Created on 2020-02-22 by the reprex package (v0.3.0)
This question already has an answer here:
draw straight line between any two point when using coord_polar() in ggplot2 (R)
(1 answer)
Closed 2 years ago.
I am making a polar violin plot. I would like to add lines and labels to the plot to annotate what each spoke means.
I'm running into two problems.
The first is that when I try to create line segments, if x != xend, then the segments are drawn as curves rather than as lines.
For example:
data.frame(
x = rnorm(1000),
spoke = factor(sample(1:6, 1000, replace=T))
) %>%
ggplot(aes(x = spoke, fill=spoke, y = x)) +
geom_violin() +
coord_polar() +
annotate("segment", x=1.1, xend=1.3, y=0, yend=3, color="black", size=0.6) +
theme_minimal()
The second problem that arises occurs when I try to add an annotation between the last spoke and the first. In this case, the annotation causes the coordinate scale to shift, so that spokes are no longer evenly distributed.
See as here:
data.frame(
x = rnorm(1000),
spoke = factor(sample(1:5, 1000, replace=T))
) %>%
ggplot(aes(x = spoke, fill=spoke, y = x)) +
geom_violin() +
coord_polar() +
scale_x_discrete(limits = 1:5) +
annotate("segment", x=5.9, xend=5.7, y=0, yend=3, color="black", size=0.6) +
theme_minimal()
Any assistance is greatly appreciated!
(PS: I do understand that there are perceptual issues with plots like these. I have a good reason...)
You want an 'generic annotation' as shown here
You basically have to overlay your plots and not use the layer facility, if you don't want to exactly calculate the distance in radians of each x for each y.
With cowplot
require(ggplot2) #again, you should specify your required packages in your question as well
require(cowplot)
my_dat <- data.frame(x = rnorm(1000),
spoke = factor(sample(1:6, 1000, replace=T)))
my_annot <- data.frame(para = c('start','end'), x = c(0,0.4), y = c(0,0.2))
#first point x/y = c(0,0) because this makes positioning easier
When I edited your question and removed the piping - that was not only a matter of good style, but also makes it much easier to then work with your different plots. So - I would suggest you should remove the pipe.
p1 <- ggplot(my_dat, aes(x = spoke, fill=spoke, y = x)) +
geom_violin() +
theme_minimal()+
coord_polar()
p2 <- ggplot(my_annot) +
geom_line(aes(x,y)) +
coord_cartesian(xlim = c(0,2), ylim =c(0,2)) +
# the limits change the length of your line too
theme_void()
ggdraw() +
draw_plot(p1) +
draw_plot(p2, x = 0.55, y = 0.6)
Obviously - you can now play around with both length of your line and its position within draw_plot()
I am having a strange situation when I am trying to plot a heatmap on a dataset that I have which can be found here.
I am using the following code to plot the heat map:
xaxis<-c('density')
midrange<-range(red[,xaxis])
xaxis <- c(xaxis,'quality')
molten<-melt(red[,xaxis],'quality')
p <- ggplot(molten, aes(x = value, y = quality))
p <- p + geom_tile(aes(fill = value), colour = "white")
p <- p + theme_minimal()
# turn y-axis text 90 degrees (optional, saves space)
p <- p + theme(axis.text.y = element_text(angle = 90, hjust = 0.5))
# remove axis titles, tick marks, and grid
p <- p + theme(axis.title = element_blank())
p <- p + theme(axis.ticks = element_blank())
p <- p + theme(panel.grid = element_blank())
p <- p + scale_y_discrete(expand = c(0, 0))
# optionally remove row labels (not useful depending on molten)
p <- p + theme(axis.text.x = element_blank())
# get diverging color scale from colorbrewer
# #008837 is green, #7b3294 is purple
palette <- c("#008837", "#b7f7f4", "#b7f7f4", "#7b3294")
if(midrange[1] == midrange[2]) {
# use a 3 color gradient instead
p <- p + scale_fill_gradient2(low = palette[1], mid = palette[2], high = palette[4], midpoint = midrange[1]) +
xlim(midrange[1],midrange[2])
}else{
# use a 4 color gradient (with a swath of white in the middle)
p <- p + scale_fill_gradientn(colours = palette, values = c(0, midrange[1], midrange[2], 1)) +
xlim(midrange[1],midrange[2])
}
p
I am trying to plot the heat map on the variable Density and would like to use the variable quality as separation in my heat map. When I use the above code, I get the following plot:
It can be clearly seen that it is a blank image. This is happening because the range of the variable Density is very low, it doesn't happen if I change the variable to the one having a wider range (pH for example).
Should ggplot automatically adjust to this? If not, how can I get ggplot to show the real plot?
Any help in this regard will be much appreciated.
So there are (at least) two problems here.
First, you have almost 1600 tiles in the x-direction, so specifying color="white" for the outline means that all you see is the outline, hence, white. Try taking this out.
Second, in your values=c(...) argument to scale_fill_gradientn(...) you seem to expect the midrange[1] and midrange[2] to be between (0,1), but midrange[2] = 1.003.
After taking out color="white" from the call to geom_tile(...), I get this: