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()
Related
I have a data frame with three continuous variables (x,y,z). I want a column plot in which x defines the x-axis position of the columns, y defines the length of the columns, and the column colors (function of y) are defined by z. The test code below shows the set up.
`require(ggplot2)
require(viridis)
# Create a dummy data frame
x <- c(rep(0.0, 5),rep(0.5,10),rep(1.0,15))
y <- c(seq(0.0,-5,length.out=5),
seq(0.0,-10,length.out=10),
seq(0.0,-15,length.out=15))
z <- c(seq(10,0,length.out=5),
seq(8,0,length.out=10),
seq(6,0,length.out=15))
df <- data.frame(x=x, y=y, z=z)
pbase <- ggplot(df, aes(x=x, y=y, fill=z))
ptest <- pbase + geom_col(width=0.5, position="identity") +
scale_fill_viridis(option="turbo",
limits = c(0,10),
breaks=seq(0,10,2.5),
labels=c("0","2.5","5.0","7.5","10.0"))
print(ptest)`
The legend has the correct colors but the columns do not. Perhaps this is not the correct way to do this type of plot. I tried using geom_bar() which creates a bars with the correct colors but the y-values are incorrect.
It looks like you have 3 X values that each appear 5, 10, or 15 times. Do you want the bars to be overlaid on top of one another, as they are now? If you add an alpha = 0.5 to the geom_col call you'll see the overlapping bars.
Alternatively, you might use dodging to show the bars next to one another instead of on top of one another.
ggplot(df, aes(x=x, y=y, fill=z, group = z)) +
geom_col(width=0.5, position=position_dodge()) +
scale_fill_viridis_c(option="turbo", # added with ggplot 3.x in 2018
limits = c(0,10),
breaks=seq(0,10,2.5),
labels=c("0","2.5","5.0","7.5","10.0"))
Or you might plot the data in order of y so that the smaller bars appear on top, visibly:
ggplot(dplyr::arrange(df,y), aes(x=x, y=y, fill=z))+
geom_col(width=0.5, position="identity") +
scale_fill_viridis_c(option="turbo",
limits = c(0,10),
breaks=seq(0,10,2.5),
labels=c("0","2.5","5.0","7.5","10.0"))
I solved this by using geom_tile() in place of geom_col().
This is should be very simple question!
I would like to make a barplot with errorbars and I'm using the following code:
ggplot(data = bars, aes(x=c("1","2","3"), y=V2, fill = names)) +
geom_bar(position=position_dodge(), stat="identity", alpha = 0.7) +
geom_errorbar(aes(ymin=V1, ymax=V3))+
theme(legend.position='none')+
coord_cartesian(ylim=c(0,10))
However, I have 2 problems:
1. I would like the bars to start at y = 0
2. I don't like the ticks in the y axis. I would like numbers with just one decimal and less ticks.
this is my actual plot: Bars with error bars
For the first problem (if I understand it correctly) you can use ylim
... + ylim(0.2, NA)
NA leaves the upper bound free.
For the second, I suggest to use pretty_breaks from scale
library(scales)
... + scale_y_continuous(breaks=pretty_breaks(n=5))
I have some code that is plots a histogram of some values, along with a few horizontal lines to represent reference points to compare against. However, ggplot is not generating a legend for the lines.
library(ggplot2)
library(dplyr)
## Siumlate an equal mix of uniform and non-uniform observations on [0,1]
x <- data.frame(PValue=c(runif(500), rbeta(500, 0.25, 1)))
y <- c(Uniform=1, NullFraction=0.5) %>% data.frame(Line=names(.) %>% factor(levels=unique(.)), Intercept=.)
ggplot(x) +
aes(x=PValue, y=..density..) + geom_histogram(binwidth=0.02) +
geom_hline(aes(yintercept=Intercept, group=Line, color=Line, linetype=Line),
data=y, alpha=0.5)
I even tried reducing the problem to just plotting the lines:
ggplot(y) +
geom_hline(aes(yintercept=Intercept, color=Line)) + xlim(0,1)
and I still don't get a legend. Can anyone explain why my code isn't producing plots with legends?
By default show_guide = FALSE for geom_hline. If you turn this on then the legend will appear. Also, alpha needs to be inside of aes otherwise the colours of the lines will not be plotted properly (on the legend). The code looks like this:
ggplot(x) +
aes(x=PValue, y=..density..) + geom_histogram(binwidth=0.02) +
geom_hline(aes(yintercept=Intercept, colour=Line, linetype=Line, alpha=0.5),
data=y, show_guide=TRUE)
And output:
I want a nice density (that sums to 1) histogram for some discrete data. I have tried a couple of ways to do this, but none were entirely satisfactory.
Generate some data:
#data
set.seed(-999)
d.test = data.frame(score = round(rnorm(100,1)))
mean.score = mean(d.test[,1])
d1 = as.data.frame(prop.table(table(d.test)))
The first gives the right placement of bars -- centered on top of the number -- but the wrong placement of vline(). This is because the x-axis is discrete (factor) and so the mean is plotted using the number of levels, not the values. The mean value is .89.
ggplot(data=d1, aes(x=d.test, y=Freq)) +
geom_bar(stat="identity", width=.5) +
geom_vline(xintercept=mean.score, color="blue", linetype="dashed")
The second gives the correct vline() placement (because the x-axis is continuous), but wrong placement of bars and the width parameter does not appear to be modifiable when x-axis is continuous (see here). I also tried the size parameter which also has no effect. Ditto for hjust.
ggplot(d.test, aes(x=score)) +
geom_histogram(aes(y=..count../sum(..count..)), width=.5) +
geom_vline(xintercept=mean.score, color="blue", linetype="dashed")
Any ideas? My bad idea is to rescale the mean so that it fits with the factor levels and use the first solution. This won't work well in case some of the factor levels are 'missing', e.g. 1, 2, 4 with no factor for 3 because no datapoint had that value. If the mean is 3.5, rescaling this is odd (x-axis is no longer an interval scale).
Another idea is this:
ggplot(d.test, aes(x=score)) +
stat_bin(binwidth=.5, aes(y= ..density../sum(..density..)), hjust=-.5) +
scale_x_continuous(breaks = -2:5) + #add ticks back
geom_vline(xintercept=mean.score, color="blue", linetype="dashed")
But this requires adjusting the breaks, and the bars are still in the wrong positions (not centered). Unfortunately, hjust does not appear to work.
How do I get everything I want?
density sums to 1
bars centered above values
vline() at the correct number
width=.5
With base graphics, one could perhaps solve this problem by plotting twice on the x-axis. Is there some similar way here?
It sounds like you just want to make sure that your x-axis values are numeric rather than factors
ggplot(data=d1, aes(x=as.numeric(as.character(d.test)), y=Freq)) +
geom_bar(stat="identity", width=.5) +
geom_vline(xintercept=mean.score, color="blue", linetype="dashed") +
scale_x_continuous(breaks=-2:3)
which gives
I am trying to use the excellent ggplot2 using the bar geom to plot the probability mass rather than the count. However, using aes(y=..density..) the distribution does not sum to one (but is close). I think the problem might be due to the default binwidth for factors. Here is an example of the problem,
age <- c(rep(0,4), rep(1,4))
mppf <- c(1,1,1,0,1,1,0,0)
data.test <- as.data.frame(cbind(age,mppf))
data.test$age <- as.factor(data.test$age)
data.test$mppf <- as.factor(data.test$mppf)
p.test.density <- ggplot(data.test, aes(mppf, group=age, fill=age)) +
geom_bar(aes(y=..density..), position='dodge') +
scale_y_continuous(limits=c(0,1))
dev.new()
print(p.test.density)
I can get around this problem by keeping the x-variable as continuous and setting binwidth=1, but it doesn't seem very elegant.
data.test$mppf.numeric <- as.numeric(data.test$mppf)
p.test.density.numeric <- ggplot(data.test, aes(mppf.numeric, group=age, fill=age)) +
geom_histogram(aes(y=..density..), position='dodge', binwidth=1)+
scale_y_continuous(limits=c(0,1))
dev.new()
print(p.test.density.numeric)
I think you almost have it figured out, and would have once you realized you needed a bar plot and not a histogram.
The default width for bars with categorical data is .9 (See ?stat_bin. The help page for geom_bar doesn't give the default bar width but does send you to stat_bin for further reading.). Given that, your plots show the correct density for a bar width of .9. Simply change to a width of 1 and you will see the density values you expected to see.
ggplot(data.test, aes(x = mppf, group = age, fill = age)) +
geom_bar(aes(y=..density..), position = "dodge", width = 1) +
scale_y_continuous(limits=c(0,1))