Removing unused levels in ggplot boxplot with facets AND flipped coordinates? - r

In R, I'm trying to make a boxplot in ggplot with flipped coordinates (horizontal boxes) grouped using facets. When I build this without flipping coordinates, ggplot will drop unused factor levels within facets with scales="free", but this doesn't seem to work when I also include coord_flip.
Minimal example:
library('ggplot2')
dat <- data.frame(RESP=rnorm(60), GROUP=rep(letters[1:6],each=10), FACET=c(rep(LETTERS[1:2],each=25),rep(LETTERS[3],10)))
The normal faceted boxplot wihtout dropping unused levels works (but not what I want):
ggplot(dat, aes(x=GROUP, y=RESP)) +
geom_boxplot() +
facet_grid(.~FACET)
The normal faceted boxplot with dropped levels also works fine (not what I want):
ggplot(dat, aes(x=GROUP, y=RESP)) +
geom_boxplot() +
facet_grid(.~FACET, scales="free", space="free")
The faceted boxplot with flipped coordinates (what I want) does not drop the unused levels:
ggplot(dat, aes(x=GROUP, y=RESP)) +
geom_boxplot() +
facet_grid(FACET~., scales="free", space="free") +
coord_flip()
Re-arranging the order of the ggplot commands doesn't fix it. I suspect the answer is in some adjustment of the FACET~. formula, but can't solve it.


It is an issue of ggplot2: coord_flip and free scales don't work
You can read a discussion about this matter here:
How to drop unused factors in faceted R ggplot boxplot?
In ggplot2, coord_flip and free scales don't work together

Related

Ggplot2 Boxplot width setting changes x-axis

I have produced a boxplot with a continuous x-axis unsing geom_boxplot() in ggplot2. However, as there are many boxes they appear as skinny lines. Another stackoverflow chain (see here) suggested using the width= argument to make all the boxes the same width. However, when I use this argument it changes the x-axis and some of the boxes just disappear!
For example, take this example dataframe. I apologise for the number of observations this has but I think the quantity has to do with the problem as I couldn't reproduce it with a more simple boxplot:
Lat<- c(50.70228,50.70228,50.70228,51.82067,51.82067,51.82067,52.45893,52.45893,52.45893,52.76478,52.76478,52.76478,52.78354,52.78354,52.78354,53.56102,53.56102,53.56102,53.65364,53.65364,53.65364,53.63130,53.63130,53.63130,54.19035,54.19035,54.19035,54.25751,54.25751,54.25751,54.23526,54.23526,54.23526,54.62469,54.62469,54.62469,54.67831,54.67831,54.67831,54.67900,54.67900,54.67900,54.94908,54.94908,54.94908,55.19456,55.19456,55.19456,54.79198,54.79198,54.79198,55.34981,55.34981,55.34981,55.85655,55.85655,55.85655,56.06078,56.06078,56.06078,55.84553,55.84553,55.84553,56.00197,56.00197,56.00197,56.71842,56.71842,56.71842,57.00116,57.00116,57.00116,57.06942,57.06942,57.06942,57.26815,57.26815,57.26815,57.45532,57.45532,57.45532,57.88596,57.88596,57.88596,51.07711,51.07711,51.07711,51.07801,51.07621,51.11159,51.11159,51.11159,52.02484,52.02484,52.02484,52.02581,52.02581,52.02581,52.02685,52.02685,52.02685,52.05353,52.05353,52.05626,52.05353,52.05353,52.05353,52.05353,52.05353,52.05353,51.93541,51.93541,51.93541,51.93541,51.93541,51.93541,51.93541,51.93541,52.92425,52.92425,52.92425,52.92425,52.92425,52.92425,52.92425,52.92425,52.92425,52.92425,52.92425,52.92425,52.92425,52.92425,52.90810,52.90810,52.90810,52.90810,52.90810,52.90810,52.78968,52.78778,52.78968,52.78968,52.78881,52.78883,52.78883,52.78883,52.78970,52.78970,52.79506,52.79506,52.79506,53.77270,53.77276,53.77109,53.77109,53.77276,53.76845,53.76845,53.77109,53.76845,53.77109,53.87020,53.87020,53.87020,53.87103,53.88205,53.88205,53.88205,53.88205,53.87701,53.87701,53.87098,53.87098,53.87098,53.86932,53.86932,53.86932,56.51869,56.51869,56.51869,56.55870,56.55870,56.55870,56.55964,56.55964,56.55964,57.51056,57.49542,57.49542,57.50878,57.50878,57.50878,57.45201,57.45477,57.45192,57.45192,57.45192)
y <- c(33.45407,21.40954,27.73487,20.38318,26.65483,31.68201,23.95467,20.77363,32.94192,22.71228,25.78824,28.39449,35.60615,24.29325,22.95047,25.65343,30.23262,22.05534,37.20565,35.53812,38.20211,39.38034,35.16619,38.82336,29.72370,38.25754,26.51339,39.38283,29.57483,31.80111,24.52967,34.83037,21.75038,35.50868,39.41830,21.96971,22.82504,32.69746,35.10747,27.75669,34.96690,37.61921,37.17226,20.50448,39.26582,22.08668,28.41502,36.69530,23.69404,23.18052,33.27420,23.04157,33.17285,32.00579,21.83845,22.97143,32.27190,21.53771,38.65481,20.14341,33.62718,39.86755,39.77881,30.59810,27.65909,24.11646,34.56981,29.30249,34.99361,32.39553,28.90443,34.88775,22.77049,36.44468,30.64496,35.81501,31.77673,24.19058,39.36298,21.47219,23.02268,31.37647,27.28457,33.14749,23.20842,39.73427,39.81399,35.51515,24.55080,39.41190,29.59987,38.46791,20.94479,37.22109,26.36060,30.91641,39.25975,39.88288,22.59061,30.24439,21.66110,30.36878,28.76901,38.75561,33.80408,31.05842,26.18921,21.30804,35.02966,33.85981,30.84373,31.67341,35.07605,37.93820,31.30481,21.45117,37.13626,25.70964,25.64736,38.58381,31.24448,26.55902,23.90817,33.70300,26.48909,37.73200,32.52413,22.44440,28.19878,32.46415,25.13711,26.66075,28.16254,20.40673,39.89327,30.83327,32.40196,39.81218,39.80391,21.87316,34.95792,33.38958,38.18441,22.03114,35.64410,34.90643,24.23056,36.66581,29.35813,20.86880,30.02044,36.13727,24.65558,39.43175,29.00154,29.78185,22.89196,37.15204,35.88188,28.73920,28.04934,37.50701,30.36306,28.39842,35.20973,26.54260,29.57763,26.03163,26.90440,27.60110,25.80086,39.98019,21.59970,28.83825,32.01711,20.50812,38.43331,32.41898,27.68722,32.59905,24.18150,29.05701,22.38512,32.93342,37.66694,37.65391,34.19613,23.89985,36.90012,20.74244,27.08511,29.21433,35.83771,35.59557,33.74533,27.08854,38.38994)
V3 <-c(1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2)
df <- as.data.frame(cbind(Lat, y, as.factor(V3)))
head(df)
I plot it on a continuous x-axis as so:
df_plot <- ggplot(df, aes(x=Lat, y=y, group=Lat))+
geom_boxplot(aes(colour=as.factor(V3)))+
theme_classic()
df_plot
Which produces:
As you can see the boxes are represented as skinny lines.
Therefore I tried to use the width= argument as so:
df_plot2 <- ggplot(df, aes(x=Lat, y=y, group=Lat))+
geom_boxplot(aes(colour=as.factor(V3)), width=1)+
theme_classic()
df_plot2
The output is:
The main thing to notice here is that the x-axis range has suddenly changed! Some of the boxes are no longer plotted whilst others seem to be placed at different values of the x-axis.
The range of the x-axis should be:
range(df$Lat)
[1] 50.70228 57.88596
I am completley perplexed as to why the x-axis would change by simply adding the width= argument in geom_boxplot(). I therefore tried to force the limits of the x-axis scale as so:
df_plot3 <- ggplot(df, aes(x=Lat, y=y, group=Lat))+
geom_boxplot(aes(colour=as.factor(V3)), width=1)+
xlim(50,58)+
theme_classic()
df_plot3
ouput:
Please send help!

I think the strange behaviour comes from ggplot trying to automatically dodge your boxplots apart. By setting position = position_dodge(width = 0) the plot seems to be created as expected without changing the placement of boxes along the x-axis. (But gives a warning about overlapping x intervals)
Lat<- c(50.70228,50.70228,50.70228,51.82067,51.82067,51.82067,52.45893,52.45893,52.45893,52.76478,52.76478,52.76478,52.78354,52.78354,52.78354,53.56102,53.56102,53.56102,53.65364,53.65364,53.65364,53.63130,53.63130,53.63130,54.19035,54.19035,54.19035,54.25751,54.25751,54.25751,54.23526,54.23526,54.23526,54.62469,54.62469,54.62469,54.67831,54.67831,54.67831,54.67900,54.67900,54.67900,54.94908,54.94908,54.94908,55.19456,55.19456,55.19456,54.79198,54.79198,54.79198,55.34981,55.34981,55.34981,55.85655,55.85655,55.85655,56.06078,56.06078,56.06078,55.84553,55.84553,55.84553,56.00197,56.00197,56.00197,56.71842,56.71842,56.71842,57.00116,57.00116,57.00116,57.06942,57.06942,57.06942,57.26815,57.26815,57.26815,57.45532,57.45532,57.45532,57.88596,57.88596,57.88596,51.07711,51.07711,51.07711,51.07801,51.07621,51.11159,51.11159,51.11159,52.02484,52.02484,52.02484,52.02581,52.02581,52.02581,52.02685,52.02685,52.02685,52.05353,52.05353,52.05626,52.05353,52.05353,52.05353,52.05353,52.05353,52.05353,51.93541,51.93541,51.93541,51.93541,51.93541,51.93541,51.93541,51.93541,52.92425,52.92425,52.92425,52.92425,52.92425,52.92425,52.92425,52.92425,52.92425,52.92425,52.92425,52.92425,52.92425,52.92425,52.90810,52.90810,52.90810,52.90810,52.90810,52.90810,52.78968,52.78778,52.78968,52.78968,52.78881,52.78883,52.78883,52.78883,52.78970,52.78970,52.79506,52.79506,52.79506,53.77270,53.77276,53.77109,53.77109,53.77276,53.76845,53.76845,53.77109,53.76845,53.77109,53.87020,53.87020,53.87020,53.87103,53.88205,53.88205,53.88205,53.88205,53.87701,53.87701,53.87098,53.87098,53.87098,53.86932,53.86932,53.86932,56.51869,56.51869,56.51869,56.55870,56.55870,56.55870,56.55964,56.55964,56.55964,57.51056,57.49542,57.49542,57.50878,57.50878,57.50878,57.45201,57.45477,57.45192,57.45192,57.45192)
y <- c(33.45407,21.40954,27.73487,20.38318,26.65483,31.68201,23.95467,20.77363,32.94192,22.71228,25.78824,28.39449,35.60615,24.29325,22.95047,25.65343,30.23262,22.05534,37.20565,35.53812,38.20211,39.38034,35.16619,38.82336,29.72370,38.25754,26.51339,39.38283,29.57483,31.80111,24.52967,34.83037,21.75038,35.50868,39.41830,21.96971,22.82504,32.69746,35.10747,27.75669,34.96690,37.61921,37.17226,20.50448,39.26582,22.08668,28.41502,36.69530,23.69404,23.18052,33.27420,23.04157,33.17285,32.00579,21.83845,22.97143,32.27190,21.53771,38.65481,20.14341,33.62718,39.86755,39.77881,30.59810,27.65909,24.11646,34.56981,29.30249,34.99361,32.39553,28.90443,34.88775,22.77049,36.44468,30.64496,35.81501,31.77673,24.19058,39.36298,21.47219,23.02268,31.37647,27.28457,33.14749,23.20842,39.73427,39.81399,35.51515,24.55080,39.41190,29.59987,38.46791,20.94479,37.22109,26.36060,30.91641,39.25975,39.88288,22.59061,30.24439,21.66110,30.36878,28.76901,38.75561,33.80408,31.05842,26.18921,21.30804,35.02966,33.85981,30.84373,31.67341,35.07605,37.93820,31.30481,21.45117,37.13626,25.70964,25.64736,38.58381,31.24448,26.55902,23.90817,33.70300,26.48909,37.73200,32.52413,22.44440,28.19878,32.46415,25.13711,26.66075,28.16254,20.40673,39.89327,30.83327,32.40196,39.81218,39.80391,21.87316,34.95792,33.38958,38.18441,22.03114,35.64410,34.90643,24.23056,36.66581,29.35813,20.86880,30.02044,36.13727,24.65558,39.43175,29.00154,29.78185,22.89196,37.15204,35.88188,28.73920,28.04934,37.50701,30.36306,28.39842,35.20973,26.54260,29.57763,26.03163,26.90440,27.60110,25.80086,39.98019,21.59970,28.83825,32.01711,20.50812,38.43331,32.41898,27.68722,32.59905,24.18150,29.05701,22.38512,32.93342,37.66694,37.65391,34.19613,23.89985,36.90012,20.74244,27.08511,29.21433,35.83771,35.59557,33.74533,27.08854,38.38994)
V3 <-c(1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2)
library(ggplot2)
df <- as.data.frame(cbind(Lat, y, as.factor(V3)))
df_plot <- ggplot(df) +
geom_boxplot(aes(colour=as.factor(V3), x=Lat, y=y, group=as.factor(Lat)),
position=position_dodge(width = 0),
width=1) +
theme_classic()

R Order of stacked areas with ggplot geom_area

I needed to reinstall R and I now encounter a little problem with ggplot. I am sure there is a simple solution to it and I appreciate all hints!
I am using the stacked area plot quite often, and usually I got the desired stacking and legend order by defining the factor levels and plotting in reverse order. However, this is not working any more after the re-installation.
Here is an example:
dx <- data.frame(x=rep(1:8,3),y=rep(c(2,3,2,4,3,5,3,2),3),z=c(rep("bread",8),rep("butter",8),rep("fish",8)))
ggplot() + geom_area(data=dx, aes(x=x, y=y, fill=z, order=-as.numeric(z)))
This gives the following plot:
It looks as if "order" did not have any impact on the plot.
The desired plot would stack the areas as shown in the legend, i.e. red area on top, blue area at the bottom.
Where is my mistake?
Many thanks in advance!

You can either use (the colors will also be reversed):
dx$z <- factor(dx$z, levels = rev(levels(dx$z)))
ggplot() + geom_area(data=dx, aes(x=x, y=y, fill=z))
Or directly use this (without reversing the factor levels, which won't change the color):
ggplot() + geom_area(data=dx, aes(x=x, y=y, fill=z)) +
guides(fill = guide_legend(reverse=TRUE))

How to replicate histograms from ggplot code

I have the following code using ggplot:
ggplot(sub9, aes(x=YR,y=Freq)) +
scale_y_continuous(limit=c(0,15),expand=c(0, 0)) +
geom_bar(stat='identity') +
xlab(" ") + ylab("No of papers") +
theme_bw(base_size = 16) +
theme(axis.text.x=element_text(angle=45,hjust=1,size=13)) +
annotate("text",x=3.5,y=14,label="Pollution",cex=7)
I have 25 plots like this, and need to plot many plots within the same graph page. This usually works well in R, using e.g. par(mfrow=c(4,4)) for a 4 x 4 plot. This code doesn't work with ggplot, where I have to use the function multiplot, which doesn't work that well as it doesn't scale all the text and legends accordingly.
Therefore I ask if some of you out there could help me replicate the exact same plot using hist.The x (YR) is a factor, and the y (Freq) is numerical.

Not sure if you're asking for putting multiple ggplots on the same page or asking for how to run histogram.
Anyway, here's an example of histogram with iris data.
library(ggplot2)
library(gridExtra)
g1 <- ggplot(iris, aes(x=Sepal.Length)) + geom_histogram(binwidth=0.5)
I'd used grid.arrange to create a 3x2 layout of 6 replicated plots:
grid.arrange (g1, g1, g1, g1, g1, g1, ncol=3)

Use facet_wrap and facet_grid
You might be looking for facet_wrap or facet_grid, which allow you to create multiple plots for different values of a factor or other categorical variable. Of course this also works for histograms.
Example from documentation
ggplot(mpg, aes(displ, cty)) + geom_point() + facet_grid(drv ~ cyl)

how to remove line from fill scale legend using geom_vline and geom_histogram r ggplot2

Basics:
Using R statistical software, ggplot2, geom_vline, and geom_histogram to visualize some data. The issue is with the legend keys.
I'm trying to plot a pair of histograms from some stochastic simulations, and on top of that plot a couple of lines representing the result of a deterministic simulation. I've got the data plotted, but the legend keys for the histograms have an unnecessary black line through the middle of them. Can you help me remove those black lines? Some sample code reproducing the issue is here:
df1 <- data.frame(cond = factor( rep(c("A","B"), each=200) ),
rating = c(rnorm(200),rnorm(200, mean=.8)))
df2 <- data.frame(x=c(.5,1),cond=factor(c("A","B")))
ggplot(df1, aes(x=rating, fill=cond)) +
geom_histogram(binwidth=.5, position="dodge") +
geom_vline(data=df2,aes(xintercept=x,linetype=factor(cond)),
show_guide=TRUE) +
labs(fill='Stochastic',linetype='Deterministic')
Edit: added image
Cheers,
Ryan

One workaround is to change the order of geom_histogram() and geom_vline(). Then add another geom_vline() without aes(), just giving xintercept= and linetype=. This will not remove lines but will hide them under the color legend entries.
ggplot(data=df1, aes(x=rating, fill=cond)) +
geom_vline(data=df2,aes(xintercept=x,linetype=factor(cond)),
show_guide=TRUE) +
geom_histogram(binwidth=.5, position="dodge") +
geom_vline(xintercep=df2$x,linetype=c(1,3))+
labs(fill='Stochastic',linetype='Deterministic')

How can I move facet labels to top of my graph?

I can create a faceted plot like so, with 3 plots stacked vertically:
ggplot(iris, aes(Petal.Length)) + stat_bin() + facet_grid(Species ~ .)
Is it possible to move the labels to the top of each graph, like they would be if I'd done horizontal stacking with facet_grid(. ~ Species)?
The reason I want this is that my plots are long time series plots, so I want the full width for each one, but the labels (which essentially function as titles to explain the facets) for each plot are too long to fit in the small label area at the right of the plot.

Yes. Use facet_wrap instead of facet_grid and be sure to also specify the argument ncol=1:
ggplot(iris, aes(Petal.Length)) + stat_bin() + facet_wrap(~Species, ncol=1)

Try this:
ggplot(iris, aes(Petal.Length)) + stat_bin() + facet_wrap(~Species,nrow = 3)

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