Manually order x-axis labels within each facet in ggplot - r

I am trying to manually reorder the x-axis labels within each facet.
The data are as follows:
df = structure(list(block = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L,
4L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 5L, 5L, 5L, 5L), .Label = c("1",
"2", "3", "4", "5"), class = "factor"), item = structure(c(14L,
15L, 28L, 29L, 30L, 31L, 32L, 15L, 16L, 17L, 18L, 19L, 20L, 21L,
15L, 22L, 23L, 24L, 25L, 26L, 27L, 1L, 2L, 3L, 4L, 5L, 6L, 7L,
1L, 8L, 9L, 10L, 11L, 12L, 13L), .Label = c("p00e00d00", "p00e00d11",
"p00e00d12", "p00e00d13", "p00e00d21", "p00e00d22", "p00e00d23",
"p00e11d00", "p00e12d00", "p00e13d00", "p00e21d00", "p00e22d00",
"p00e23d00", "p01e00d00", "p11e00d00", "p11e00d11", "p11e00d12",
"p11e00d13", "p11e00d21", "p11e00d22", "p11e00d23", "p11e11d00",
"p11e12d00", "p11e13d00", "p11e21d00", "p11e22d00", "p11e23d00",
"p12e00d00", "p13e00d00", "p14e00d00", "p21e00d00", "p22e00d00"
), class = "factor"), response = structure(c(2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L), .Label = c("2",
"1"), class = "factor"), n = c(345L, 511L, 583L, 613L, 612L,
222L, 142L, 531L, 546L, 589L, 636L, 478L, 364L, 313L, 502L, 533L,
587L, 603L, 385L, 298L, 263L, 518L, 546L, 563L, 593L, 435L, 351L,
310L, 478L, 579L, 629L, 646L, 357L, 307L, 230L), freq = c(0.408284023668639,
0.604733727810651, 0.689940828402367, 0.725443786982249, 0.724260355029586,
0.262721893491124, 0.168047337278107, 0.628402366863905, 0.646153846153846,
0.697041420118343, 0.752662721893491, 0.565680473372781, 0.430769230769231,
0.370414201183432, 0.594082840236686, 0.630769230769231, 0.694674556213018,
0.713609467455621, 0.455621301775148, 0.352662721893491, 0.311242603550296,
0.61301775147929, 0.646153846153846, 0.666272189349112, 0.701775147928994,
0.514792899408284, 0.415384615384615, 0.366863905325444, 0.565680473372781,
0.685207100591716, 0.744378698224852, 0.764497041420118, 0.422485207100592,
0.363313609467456, 0.272189349112426)), class = c("tbl_df", "tbl",
"data.frame"), row.names = c(NA, -35L), .Names = c("block", "item",
"response", "n", "freq"))
There are five blocks, each block contains 7 items, and some items have the same names across blocks. I can therefore facet by block as follows:
df %>%
ggplot(aes(x = item, y = freq)) +
geom_bar(stat = "identity", position = "dodge", color = "black") +
facet_grid(.~block, scales = "free") +
coord_cartesian(ylim = c(0, 1), expand = F) + # need to add expanse = F to prevent zooming away
scale_y_continuous(labels = scales::percent) +
theme(axis.text.x = element_text(angle=45, hjust=1, vjust=1))
I also have vectors which states for each block the order that items should appear in. For example:
block_3_order = c("p11e13d00","p11e12d00", "p11e11d00", "p11e00d00", "p11e21d00", "p11e22d00","p11e23d00")
)
block_4_order = c("p00e00d13", "p00e00d12", "p00e00d11", "p00e00d00", "p00e00d21","p00e00d22","p00e00d23")
)
I tried to reorder the "item" factor, but to get the desired effect I would need to split the dataframe into subsets representing blocks. Otherwise I am having trouble grasping how you can integrate the ordering of factors with the ggplot treatment of item as a single factor across facets.
Any help is greatly appreciated.

To get a different custom axis order in each facet, you can create each "facet" as a separate plot and then lay them out together as if they were a single faceted plot.
library(tidyverse)
#devtools::install_github("baptiste/egg")
library(egg)
library(gridExtra)
library(grid)
theme_set(theme_bw())
First, create the custom orderings. The ones that are NULL will just be sorted alphabetically in the final plot.
b.order = list(b1 = NULL,
b2 = NULL,
b3 = c("p11e13d00","p11e12d00", "p11e11d00", "p11e00d00", "p11e21d00", "p11e22d00","p11e23d00"),
b4 = c("p00e00d13", "p00e00d12", "p00e00d11", "p00e00d00", "p00e00d21","p00e00d22","p00e00d23"),
b5 = NULL)
Create a list of plots, one for each block. We do this by splitting df by block. To get the custom ordering, we use factor to set the custom order based on the list b.order.
plist = map2(split(df, df$block), b.order,
~ .x %>% group_by(block) %>%
mutate(item = factor(item, levels=if(is.null(.y)) sort(unique(item)) else .y)) %>%
ggplot(aes(x = item, y = freq)) +
geom_bar(stat = "identity", position = "dodge", color = "black") +
facet_grid(.~block, scales = "free") +
coord_cartesian(ylim = c(0, 1), expand = F) + # need to add expanse = F to prevent zooming away
scale_y_continuous(labels = scales::percent) +
theme(axis.text.x = element_text(angle=45, hjust=1, vjust=1),
plot.margin=margin(b=-5)) +
labs(x=""))
Remove y-axis labels, title, and ticks from all but the left-most plot:
plist[2:length(plist)] = plist[2:length(plist)] %>%
map(~ .x + theme(axis.text.y=element_blank(),
axis.title.y=element_blank(),
axis.ticks.y=element_blank()))
Arrange the plots. We use ggarrange from the egg package in order to ensure that the plot panels all have the same horizontal width. We also need to add the Item label beneath the plot. However, ggarrange prints the plot to the output device, even inside arrangeGrob. So we create the object p, clear the device and then redraw the final plot.
p = arrangeGrob(ggarrange(plots=plist, ncol=length(plist)),
textGrob("Item"), heights=c(20,1))
grid.newpage()
grid.draw(p)

Related

How to add p values into grouped charts in ggplot?

When I want to add p values into my plots:
library(tidyverse)
library(ggpubr)
library(rstatix)
stat.test3 <- MP %>%
group_by(TBI) %>%
wilcox_test(age ~ mp_1) %>%
adjust_pvalue(method = "bonferroni") %>%
add_significance("p.adj")%>%
mutate(y.position = 35)
C2<- ggplot(data=MP, aes(x=TBI, y=age, fill=mp_1))+
geom_violin()+
geom_boxplot(width=.2, fatten=NULL, position = position_dodge(0.9))+
stat_summary(fun="median", geom="point", position = position_dodge(0.9))+
stat_summary(fun.data = "mean_se", geom = "errorbar", width=.1, position = position_dodge(0.9))+
scale_fill_brewer(name="Mind-pop", palette = "Accent")
C2+ stat_pvalue_manual(stat.test3, xmin = "TBI",xmax = NULL)
it gives me this error:
Error in FUN(X[[i]], ...) : object 'mp_1' not found
This error is shown after adding stat_pvalue to the object.
How should I fix it?
I'm not familiar with ggpubr so can't say I understand the underlying issue but it seems like color=mp_1 instead of fill=mp_1 might fix your issue. This is in the following line:
C2 <- ggplot(data=MP, aes(x=TBI, y=age, color=mp_1)).
The full code is below. I've also changed y.position so that the significance is at the top of the plot.
MP <- structure(list(age = c(55L, 54L, 56L, 60L, 55L, 53L, 61L, 56L,
58L, 58L, 56L, 58L, 58L, 58L, 59L, 57L, 56L, 60L, 57L, 58L, 61L,
60L),
mp_1 = structure(c(2L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L), .Label = c("No", "Yes"), class = "factor"),
TBI = structure(c(2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L), .Label = c("HC",
"TBI"), class = "factor")), class = "data.frame", row.names = c(NA, -22L))
library(tidyverse)
library(ggpubr)
library(rstatix)
stat.test3 <- MP %>%
group_by(TBI) %>%
wilcox_test(age ~ mp_1) %>%
adjust_pvalue(method = "bonferroni") %>%
add_significance("p.adj") %>%
mutate(y.position = 61.5)
C2 <- ggplot(data=MP, aes(x=TBI, y=age, color=mp_1))+
geom_violin() +
geom_boxplot(width=.2, fatten=NULL, position = position_dodge(0.9))+
stat_summary(fun="median", geom="point", position = position_dodge(0.9))+
stat_summary(fun.data = "mean_se", geom = "errorbar", width=.1, position = position_dodge(0.9))+
scale_fill_brewer(name="Mind-pop", palette = "Accent")
C2 + stat_pvalue_manual(stat.test3, xmin = "TBI",xmax = NULL)

Is there a way to create error bars on a ggplot bar graph that uses the fill option for a factor variable?

I have a data set that uses two factor variables to create a bar graph in ggplot. A factor variable of 5 levels provides the bar graph distinctions, while the factor variable of two levels provides the mean/average of each condition. An example graph looks like this :
The code to produce this is
plot <- ggplot(data = testdf, aes(x = condition, fill = DV)) + geom_bar(position = "fill", na.rm = TRUE) + theme_bw()
I would like to add error bars onto each of the bars, using 95% confidence intervals.
I've tried converting the DV variable to a numeric 1 or 0 and then analyzing using summarySE() to get CIs for each bar, like so:
se_test <- summarySE(testdf, measurevar = "numericDV", groupvars = c("condition"))
. I then change the ggplot function to read:
plot <- ggplot(data = testdf, aes(x = condition, fill = DV)) +
geom_bar(position = "fill", na.rm = TRUE) + theme_bw() +
geom_errorbar(aes(ymin = (DV - se_test$ci), ymax = (DV - se_test$ci)))
This leads to an error for the - and + to not be meaningful for factors. So the data is still being considered as a factor. Is there a way to keep this graph, while implementing the CI error bars? I'd like for the average displayed by the bars to act as the middle of the confidence intervals, while keeping the aesthetics of the fill conditions.
Thanks in advance.
Sample Data W/ Numeric DV:
testdf <- structure(list(condition = structure(c(4L, 3L, 3L, 2L, 5L, 1L,
5L, 4L, 4L, 3L, 4L, 1L, 2L, 5L, 5L, 1L, 4L, 3L, 2L, 5L, 4L, 3L,
3L, 2L, 2L, 3L, 2L, 3L, 5L, 1L, 3L, 3L, 3L, 4L, 4L, 1L, 4L, 2L,
4L, 3L), .Label = c("0", "1", "2", "3", "4"), class = "factor"),
DV = structure(c(1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L,
1L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 1L,
2L, 1L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 1L, 1L, 2L, 2L
), .Label = c("No", "Yes"), class = "factor"), numericDV = c(0,
1, 1, 1, 1, 1, 1, 1, 0, 1, 0, 1, 0, 0, 0, 1, 1, 1, 1, 1,
0, 1, 1, 1, 0, 1, 0, 0, 1, 0, 1, 0, 1, 0, 1, 0, 0, 0, 1,
1)), row.names = c(2L, 4L, 9L, 12L, 16L, 17L, 22L, 24L, 30L,
31L, 35L, 40L, 41L, 42L, 43L, 45L, 46L, 47L, 49L, 50L, 52L, 57L,
64L, 66L, 67L, 73L, 76L, 77L, 78L, 79L, 84L, 86L, 90L, 100L,
103L, 105L, 107L, 108L, 112L, 113L), class = "data.frame")
ggplot2 let's you combine several data frames in one 'screen-space' using just the variable names and values - that is you can add a layer to your plot which has a different data source.
testdf %>%
ggplot(aes(x = condition)) +
geom_bar(aes(fill = DV), position = "fill", na.rm = TRUE) +
geom_errorbar(aes(
ymin = numericDV - ci,
ymax = numericDV + ci),
data = Rmisc::summarySE(testdf, measurevar = "numericDV", groupvars = "condition")) +
theme_bw()
I'm not sure if the result looks really nice with the bars exceeding the 0-1 interval, but numerically it looks like what you wanted. I moved the fill aesthetic to the geom_bar layer, as DV is missing in the summarySE output.
you can try
library(tidyverse)
se_test <- Rmisc::summarySE(testdf, measurevar = "numericDV", groupvars = c("condition"))
testdf %>%
count(condition, DV) %>%
ggplot(aes(condition, n)) +
geom_col(aes( fill =DV)) +
geom_errorbar(data=se_test, aes(y=N, ymin = N - ci, ymax = N + ci))

Add secondary X-axis with facets

Seems that this topic has not been covered this since the ggplot2.2.2 update where old solutions like this one and this one no longer apply. Fortunately, the process is far simpler than before. One line of code and you have a secondary Y-axis (as shown here).
But I cannot get a secondary X-axis on my plots...
I am comparing a depth profile of metal concentrations along the sediment core. I would like to display carbon and phosphate concentrations as an geom_area behind the metal's concentration. The problem is that both carbon and phosphate concentrations are no on the same scale as the metal. Thus I need a second axis.
The theme is the following (taken from this website):
theme_new <- theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank(), panel.background = element_blank(), axis.line = element_line(colour = "black"), strip.text.x = element_text(size=10, angle=0, vjust=0), strip.background = element_blank(), strip.text.y = element_text(angle = 0), legend.position="none",panel.border = element_blank(), axis.text.x=element_text(angle=45,hjust=1)) # Axis tick label angle
And this code gives me a second Y-axis even though I specify it under X-axis.
ggplot(MasterTable)+
geom_line(aes(Depth,Conc.nM))+
geom_area(aes(Depth,Conc.uM, fill=Variable))+
scale_x_continuous("Depth (cm)", sec.axis = sec_axis(~ . *100, name = "Carbon & Phosphate"))+
scale_y_continuous("Metal concentration (nM)")+
coord_flip()+
theme_new+
theme(legend.position = "right")+
facet_grid(. ~ Assay, scales = "free")
Can anyone help me place the secondary axis on the top of the figure?
Thanks!!
dput of my MasterTable is the following:
structure(list(Depth = c(15L, 5L, 2L, -1L, -3L, -5L, -7L, -9L,
-11L, -13L, -15L, -17L, -19L, -21L, -23L, -25L, -27L, -29L, -31L,
15L, 5L, 2L, -1L, -3L, -5L, -7L, -9L, -11L, -13L, -15L, -17L,
-19L, -21L, -23L, -25L, -27L, -29L, -31L), Conc.nM = c(24L, 24L,
24L, 100L, 100L, 75L, 75L, 85L, 85L, 120L, 300L, 1000L, 200L,
240L, 240L, 800L, 1100L, 1500L, 2300L, 0L, 10L, 0L, 50L, 200L,
200L, 50L, 50L, 200L, 15L, 0L, 0L, 10L, 120L, 200L, 1500L, 2100L,
2000L, 2000L), Assay = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L), .Label = c("Instrument 1",
"Instrument 2"), class = "factor"), Conc.uM = c(0L, 0L, 0L, 1L,
4L, 10L, 10L, 10L, 5L, 7L, 10L, 14L, 14L, 14L, 14L, 13L, 12L,
12L, 12L, 1L, 1L, 1L, 4L, 6L, 9L, 11L, 11L, 8L, 8L, 8L, 20L,
10L, 9L, 9L, 9L, 10L, 10L, 10L), Variable = structure(c(2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L), .Label = c("Carbon", "Phosphate"), class = "factor")), .Names = c("Depth",
"Conc.nM", "Assay", "Conc.uM", "Variable"), class = "data.frame", row.names = c(NA,
-38L))
Thanks to Brian's answer, and modifying the theme proposed above, I got the following figure.
As he suggested, you have to first modify your data manually using something like this:
MasterTable$Conc.uM <- MasterTable$Conc.uM *100
Then, in the code, adjust your axis with the same correction factor as the one used above. Here is the code to make the figure.
ggplot(MasterTable)+
geom_line(aes(Depth,Conc.nM))+
geom_area(aes(Depth,Conc.uM, fill=Variable), alpha=0.6)+ #Area for second X-axis
geom_area(aes(Depth,Conc.nM), alpha=0.95)+
geom_point(aes(Depth,Conc.uM), size=1, shape=16, alpha=0.3)+ #Adding points for second X-axis
geom_point(aes(Depth,Conc.nM), size=1, shape=16, alpha=0.8)+
scale_fill_manual(values=colours) + scale_colour_manual(values=colours) +
labs(title="Sediment core", color="",fill="") + #Place legend title in both color="" and fill=""
scale_y_continuous("Metal concentration (nM)",
sec.axis = sec_axis(~ . /100, name = "[Pi] (uM) DOC (mg/L)"))+
scale_x_continuous("Depth (cm)", breaks=pretty_breaks(n=7))+
coord_flip()+ #Required to make a proper depth profile
theme_new+ #Reference to custom theme
facet_grid(. ~ Assay, scales = "free") #Scales makes that the axis size can change
Now I just have one problem left to solve. I would like for the tick marks and labels to be under the facet. Seems more logical and less busy than having it at the top of the figure.
From your code:
...
scale_x_continuous("Depth (cm)", sec.axis = sec_axis(~ . *100, name = "Carbon & Phosphate"))+
scale_y_continuous("Metal concentration (nM)") +
coord_flip() ...
Consider which primary axis you want "Carbon & Phosphate" to be parallel to. Also consider what "x-axis" and "y-axis" mean in the context of using coord_flip.
TL;DR: Just move your secondary axis into scale_y_continuous.

Plot text/labels centered on a dodged bar plot

I can't figure out how to display labels centered on each dodged bar in a barplot in ggplot2.
I know that I can dodge the bars using position = "dodge" and I know that in order for the labels to show up centered on each bar I need to add position = position_dodge(width = 1) in the geom_text() or geom_label() command.
But for some reason it doesn't work (see Figure below). I also added my data and code.
df <- structure(list(Measure = structure(c(2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L), .Label = c("1988",
"2017"), class = "factor"), Province = structure(c(1L, 2L, 3L,
4L, 5L, 6L, 7L, 8L, 9L, 10L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L,
9L, 10L), .Label = c("BC", "AB", "SK", "MB", "ON", "QC", "NB",
"PE", "NS", "NL"), class = "factor"), Value = c(363L, 61L, NA,
69L, NA, NA, 127L, 12L, 92L, 18L, 178L, 29L, 41L, 92L, 284L,
1019L, 267L, 27L, 77L, 22L)), .Names = c("Measure", "Province",
"Value"), row.names = 41:60, class = "data.frame")
ggplot(df, aes(x=Province, y=Value)) + geom_bar(aes(fill=Measure), position="dodge",
stat="identity") + geom_label(aes(label=Value), position = position_dodge(width=1))
I just realized (thanks to #aelwan answer) that the only thing I had to do is adding group=Measure in the aes() function, i.e.
ggplot(df, aes(x=Province, y=Value, group=Measure)) +
geom_bar(aes(fill=Measure),position="dodge", stat="identity") +
geom_label(aes(label=Value),position = position_dodge(width=1))
That gives:
Try this
ggplot(df, aes(x=Province, y=Value, group = Measure)) +
geom_col(aes(fill=Measure),
position ="dodge", width = 0.4)+
geom_text(aes(label= Value,
group = Measure
),vjust= 0, position = position_dodge(0.4) , color="black" )
This is a late answer, but the geom_text is not perfectly centered over the bars. One way to fix this is by also specifying the width of the bars position=position_dodge(width = 1).
geom_bar(aes(fill=Measure),position=position_dodge(width = 1), stat="identity")

How to center values in stackbar plot and add greek text to legend with ggplot

I have created a stacked-bar plot with 'ggplot' to display my karyotype (molecular) results from a transplant experiment, with each panel representing a location, and the x-axis is the various substrates, while the y-axis is the percentage of each of the three karyotypes.
I have looked over several examples of questions and answers from Stack Overflow and cannot figure out how to do the following:
centre the values (should be rounded to two decimal places) within each section of the stacked bars, right now I just have them offset from the top.
how to change my legend text from "BB" to the Greek "lower alpha, lower alpha", "BD" to Greek "lower alpha, lower beta", and "DD" to Greek "lower beta, lower beta".
Here is some sample data and code with a copy of the plot it generates.
Karotype.Data <- structure(list(Location = structure(c(1L, 1L, 3L, 3L, 1L, 1L, 1L, 1L, 1L, 1L, 4L, 4L, 1L, 1L, 1L, 4L, 2L, 1L, 2L, 1L, 2L, 2L, 2L, 2L, 2L), .Label = c("Kampinge", "Kaseberga", "Molle", "Steninge"), class = "factor"), Substrate = structure(c(1L, 1L, 1L, 1L, 1L, 2L, 2L, 3L, 4L, 2L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 3L, 2L, 1L, 4L, 2L), .Label = c("Kampinge", "Kaseberga", "Molle", "Steninge"), class = "factor"), Karyotype = structure(c(1L, 3L, 4L, 1L, 3L, 3L, 4L, 4L, 4L, 3L, 1L, 4L, 3L, 4L, 2L, 3L, 1L, 4L, 3L, 2L, 4L, 3L, 4L, 2L, 3L), .Label = c("", "BB", "BD", "DD"), class = "factor")), .Names = c("Location", "Substrate", "Karyotype"), row.names = c(135L, 136L, 137L, 138L, 139L, 165L, 166L, 167L, 168L, 169L, 236L, 237L, 238L, 239L, 240L, 326L, 327L, 328L, 329L, 330L, 426L, 427L, 428L, 429L, 430L), class = "data.frame")
z.counts <- Karotype.Data %>%
group_by(Location,Substrate,Karyotype) %>%
summarise(Frequency=n())
z.freq <- z.counts %>% filter(Karyotype != '') %>%
group_by(Location,Substrate) %>%
mutate(Percent=Frequency/sum(Frequency))
z.freq
ggplot(z.freq, aes(x=Substrate, y=Percent, fill=Karyotype )) +
geom_bar(stat="identity") +
geom_text(aes(label = Percent), size = 5, vjust = 1, position = "stack") +
facet_wrap(~ Location, ncol=2) +
scale_y_continuous(name="Percentage") +
theme(strip.text.x = element_text(colour="black", size=20, face="bold"),
axis.title.x = element_text(colour="black", size=20, face="bold", vjust=-0.5),
axis.text.x = element_text(colour="black", size=18),
axis.title.y = element_text(colour="black", size=20,face="bold", vjust=1),
axis.text.y = element_text(colour="black", size=18),
legend.title = element_text(colour="black", size=20, face="bold"),
legend.text = element_text(colour="black", size = 18),
legend.position="bottom")
To add greek letters to the legend, you can change the colour scale with scale_colour_manual():
test = data.frame(x=1:30,y=1:30,label=rep(c("BB","BD","DD"),each=10))
ggplot(test) + geom_point(aes(x=x,y=y,color=label)) + scale_colour_manual(values=c(1,2,3),breaks = c("BB","BD","DD"),labels = list(bquote(alpha~alpha),bquote(alpha~beta),bquote(beta~beta)))
argument values sets the colour, breaks sets your breakpoints (BB, BD and DD) and labels sets the greek letters you want.
To round the legend, you can add another column to your dataframe, setting values to round(Percent,digits=3), and use this column in the geom_text.
Informations concerning greek letters in ggplot2 can be found here

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