I have a data set in R which I want to get an error bar on, however it isn't plotting correctly (see photo). I have also included my data set.
ant.d<-structure(list(group.name = structure(c(1L, 18L, 20L, 24L, 8L,
13L, 15L, 17L, 12L, 19L, 21L, 22L, 23L, 9L, 11L, 16L, 2L, 3L,
4L, 5L, 6L, 7L, 10L, 14L), .Label = c("group 1", "group 10",
"group 11", "group 12", "group 13", "group 14", "group 15 ",
"group 16 ", "group 17", "group 18", "group 19", "group 2", "group 20",
"group 21", "group 22", "group 23", "group 24", "group 3", "group 4 ",
"group 5 ", "group 6", "group 7 ", "group 8 ", "group 9 "), class = "factor"),
habitat.type = structure(c(3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L), .Label = c("edge", "forest", "Pasture"), class = "factor"),
species.richness = c(3L, 5L, 2L, 3L, 1L, 2L, 4L, 3L, 9L,
5L, 5L, 4L, 4L, 4L, 8L, 7L, 4L, 3L, 5L, 2L, 3L, 6L, 2L, 1L
), X = c(2.875, 2.875, 2.875, 2.875, 2.875, 2.875, 2.875,
2.875, 5.75, 5.75, 5.75, 5.75, 5.75, 5.75, 5.75, 5.75, 3.25,
3.25, 3.25, 3.25, 3.25, 3.25, 3.25, 3.25), se = c(2.32340059786604,
1.7996983644207, 2.84557296642458, 2.32340059786604, 4.02424788183988,
2.84557296642458, 2.01212394091994, 2.32340059786604, 1.34141596061329,
1.7996983644207, 1.7996983644207, 2.01212394091994, 2.01212394091994,
2.01212394091994, 1.42278648321229, 1.52102272991811, 2.01212394091994,
2.32340059786604, 1.7996983644207, 2.84557296642458, 2.32340059786604,
1.64289231816395, 2.84557296642458, 4.02424788183988)), .Names = c("group.name",
"habitat.type", "species.richness", "X", "se"), row.names = c(NA,
-24L), class = "data.frame")
What am I doing wrong? I've spent some time reading about error bars in R and I've not been successful.
ant.d$se <- 1.96*(sd(ant.d$species.richness, na.rm=T)/sqrt(ant.d$species.richness))
p<-ggplot(data = ant.d, aes(y = species.richness, x = habitat.type)) +
geom_bar(stat="identity",position="dodge")
p
p + geom_bar(position=dodge) + geom_errorbar(aes(ymax = species.richness + se, ymin=species.richness - se), position=dodge, width=0.25)
If I understand you correctly about what you are trying to achieve, then it's probably best to aggregate your data before plotting:
df <- aggregate(cbind(species.richness,se) ~ habitat.type, ant.d, mean)
ggplot(data = df, aes(x = habitat.type, y = species.richness)) +
geom_bar(stat="identity", fill="grey") +
geom_errorbar(stat="identity", aes(ymax = species.richness + se, ymin=species.richness - se), width=0.25)
which gives:
If you want groups within each habitat.type, you could something like this:
ggplot(data = ant.d, aes(x = habitat.type, y = species.richness, fill = group.name)) +
geom_bar(stat="identity", position=position_dodge(0.8)) +
geom_errorbar(stat="identity", aes(ymax = species.richness + se, ymin=species.richness - se), width=0.25,
position=position_dodge(0.8)) +
scale_fill_discrete(guide = guide_legend(ncol=2))
which gives:
Related
I found some online datasets and managed to make some complex box plots that had most of the features I was looking for. I'd appreciate the community's help in making these plots look better, such as:
removing axes lines,
adding tick marks and making them point inwards,
changing the background color or font of facet_wrap,
and removing "Label" in my attached plots.
The program Veusz allows you to change whisker mode to (e.g. I.5 IQR, 9/91 percentile, 1 stddev) and it would be nice to have that option as well. I also don't understand why the data points in my first box plot (linked below) are off center.
Linked below are screen shots of some grouped box plots that I made from my own data. I learn best by breaking and fixing things, and if someone has the time to write out the code for a box plot with lots of features, I will deconstruct it to see what each part does and search for the code online to get a better understanding of how it works.
Box plot of my data 1
Box plot of my data 2
Box plot of my data 3
structure(list(X. = structure(c(1L, 12L, 23L, 34L, 45L, 56L,
67L, 71L, 72L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 13L,
14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 24L, 25L, 26L, 27L,
28L, 29L, 30L, 31L, 32L, 33L, 35L, 36L, 37L, 38L, 39L, 40L, 41L,
42L, 43L, 44L, 46L, 47L, 48L, 49L, 50L, 51L, 52L, 53L, 54L, 55L,
57L, 58L, 59L, 60L, 61L, 62L, 63L, 64L, 65L, 66L, 68L, 69L, 70L
), .Label = c("# 1", "# 10", "# 11", "# 12", "# 13", "# 14",
"# 15", "# 16", "# 17", "# 18", "# 19", "# 2", "# 20", "# 21",
"# 22", "# 23", "# 24", "# 25", "# 26", "# 27", "# 28", "# 29",
"# 3", "# 30", "# 31", "# 32", "# 33", "# 34", "# 35", "# 36",
"# 37", "# 38", "# 39", "# 4", "# 40", "# 41", "# 42", "# 43",
"# 44", "# 45", "# 46", "# 47", "# 48", "# 49", "# 5", "# 50",
"# 51", "# 52", "# 53", "# 54", "# 55", "# 56", "# 57", "# 58",
"# 59", "# 6", "# 60", "# 61", "# 62", "# 63", "# 64", "# 65",
"# 66", "# 67", "# 68", "# 69", "# 7", "# 70", "# 71", "# 72",
"# 8", "# 9"), class = "factor"), Label = structure(c(1L, 1L,
1L, 1L, 1L, 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, 2L, 2L, 2L, 2L, 2L, 3L, 3L,
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
3L, 3L, 3L, 3L, 3L, 3L), .Label = c("Sample 1", "Sample 2", "Sample 3"
), class = "factor"), Rescan = structure(c(1L, 1L, 1L, 1L, 1L,
1L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L,
4L, 4L, 4L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 3L,
3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 1L, 1L, 1L, 1L, 1L,
1L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L,
4L, 4L, 4L), .Label = c("Rescan 0", "Rescan 1", "Rescan 2", "Rescan 3"
), class = "factor"), Porosity = c(15.19, 15.72, 15.83, 15.57,
15.11, 14.15, 17.24, 17.53, 18.21, 18.8, 18.32, 19.59, 17.4,
17.98, 19.33, 18.94, 18.32, 18.17, 19.67, 20.55, 19.04, 18.18,
19.59, 18.19, 18.97, 18.64, 18.83, 17.24, 18.09, 17.74, 22.28,
22.29, 21.35, 21.96, 23.12, 22.9, 22.9, 21.06, 23.34, 22.82,
21.42, 20.48, 21.22, 22.75, 21.62, 22.24, 24.28, 20.48, 14.79,
13.69, 13.4, 14.46, 14.13, 13.55, 20.67, 19.81, 21.2, 20.77,
22.29, 21.94, 19.49, 19.29, 19.43, 20.31, 21.77, 19.39, 22.37,
21.46, 21.86, 21.58, 21.82, 23.02)), class = "data.frame", row.names = c(NA,
-72L))
Here's an example of your plot with the things you wanted to do. I suppose you can adjust the code to your needs from here:
ggplot(mydata, aes(Label,Porosity,fill=Label))+
geom_boxplot()+
# shift strips down
facet_wrap(~Rescan, strip.position = "bottom")+
# add exact points
geom_point(alpha=0.2)+
# add your preferred colors here (hexcode also works fine)
scale_fill_manual(values=c("red","blue","green"))+
# appearance
theme_classic()+
# legend options
theme(legend.title = element_blank(),
legend.text = element_text(color ="black", size = 8),
legend.position = "top", # "bottom" or "right"
legend.key.size = unit(1, "cm"),
legend.spacing.x = unit(5, "mm"),
legend.direction = "horizontal", # or "vertical"
legend.background = element_blank())+
# reverse legend keys
guides(fill = guide_legend(reverse = F))+ # set T to take action
# scaling y-axis
scale_y_continuous(expand = c(0, 0), limits = c(0,max(mydata$Porosity)),breaks = seq(0,max(mydata$Porosity,10)))+
# paramaters of the axes
theme(
axis.text = element_text(color = "black", angle = 0, hjust = 0.5, vjust = 0.5, size = 8),
# axis.title = element_blank(), # activate for no axis titles
axis.line = element_line(color = "black", size = 0.5), # use element_blank() for no lines
axis.ticks.length=unit(-0.1, "cm"), # negative values turn them inside
plot.background = element_blank(),
text = element_text(family = "Arial"),
strip.background = element_blank(),
strip.placement = "outside")+ # or "inside"
# name your axes
ylab("your y lab")+
xlab("your x lab")+
# add x-axis in each facet
annotate("segment", y=0,yend=0,x=0,xend=Inf)
Hopefulyy this answers some of the questions, but to be honest it's hard to pull out the individual questions you are asking. Perhaps put them in dot points?
overall look:
There are some pre-made themes you can try, I like:
theme_void() - removes most things
theme_classic() - makes the background nicer to look at
theme_minimal() - removes the outer border and makes the background prettier
You can add them as a layer with + theme_void() on the end of the plotting code.
For all other specific customisations look at ?theme() as there are a whole bunch of things you can do.
labels:
To remove the title 'label' add labs(legend = '') as a layer. You can also use this to modify the x, y, caption and title text.
If you want to remove the legend entirely, you can add show.legend = F inside your geom_jitter() layer. (e.g. geom_jitter(show.legend = F)) This will mean it shows on the graph, but nothing appears in the legend.
facets:
To change the colour of the background in facte_wrap use theme(strip.background = element_rect(color = 'desired_colour'))
To change the colour of the text in facte_wrap use theme(strip.text = element_text(color = 'desired_colour'))
axis lines:
add theme(axis.line = element_blank())
points:
Your points are off center due to the geom_jitter(). Try geom_point() instead.
When entering the following code, I get a weird ggplot where it plots vertical lines.
ggplot(data = otherdata, aes(x = subject, y = pct_.below)) + geom_point(aes(colour = subgroup))
When doing geom_point rather than geom_line, I get the other graph. I have no idea why this happens. There are more points than there are subgroups but that's not the solution to the issue. What do I do to fix this ggplot?
# dummy data
set.seed(45)
df <- data.frame(x=rep(1:5, 9), val=sample(1:100, 45),
variable=rep(paste0("category", 1:9), each=5))
# plot
ggplot(data = df, aes(x=x, y=val)) + geom_line(aes(colour=variable))
That code that I just posted works but I have no idea what the difference is between the two codes.
First 20 rows of the data:
structure(list(subject = structure(c(1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L), .Label = c("Algebra II",
"Biology I", "Chemistry", "English I", "English II", "English III",
"Geometry", "Int Math I", "Int Math II", "Int Math III", "US History"
), class = "factor"), pct_.below = c(0, 12.5, 12.4, 12.5, 0,
0, 12.5, 8.4, 11.1, 12.8, 11.9, 0, 11.5, 9, 100, 66.7, 100, 100,
100, 50), subgroup = structure(c(2L, 3L, 4L, 5L, 7L, 10L, 11L,
12L, 13L, 15L, 16L, 17L, 18L, 19L, 3L, 4L, 5L, 8L, 10L, 11L), .Label = c("All Students",
"Asian", "Black or African Amer", "Black/Hispanic/Native Amer",
"ED", "English Learner T 1-2", "English Learner T 1-4", "English Learners",
"English Learners with T 1-2", "English Learners with T 1-4",
"Hispanic", "Non-Black/Hispanic/Native Amer", "Non-ED", "Non-English Learners/T 1-2",
"Non-English Learners/T 1-4", "Non-Students with Disabilities",
"Students with Disabilities", "Super Subgroup", "White"), class = "factor")), row.names = c(2L,
3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 32L,
33L, 34L, 35L, 36L, 37L), class = "data.frame")
I am trying to create this figure that animates over time using the gganimate library, going from the 'baseline' timepoint to the 'late' timepoint'. However for some reason, the image changes between frames 22-24 and again between 42-44. It throws off the visualization. But I am not sure how to fix it. Many thanks!
library(ggplot2)
library(tweenr)
library(gganimate)
library(treemapify)
set.seed(1)
colors <- c("turquoise", "gold", "yellowgreen", "dodgerblue", "firebrick", "orchid4",
"grey74", "forestgreen", "deeppink2", "grey0", "slateblue", "sienna2",
"khaki2", "steelblue", "darksalmon", "darksalmon")
tweened <- tween_states(list(PID50baseline, PID50late, PID50baseline),
tweenlength = 8, statelength = 8,
ease = 'cubic-in-out', nframes = 50)
animated_plot <- ggplot(tweened,
aes(area = Number, fill = Cluster.Name,
subgroup=Type, frame = .frame)) +
geom_treemap(fixed = T) +
geom_treemap_subgroup_border(fixed = T) +
geom_treemap_subgroup_text(place = "centre", grow = T, alpha = 0.5,
colour = "black", fontface = "italic",
min.size = 0,fixed = T) +
scale_fill_manual(values = colors) +
theme(legend.position = "bottom")
animation::ani.options(interval = 1/10)
gganimate(animated_plot, "animated_treemap_PID50.gif", title_frame = T,
ani.width = 200, ani.height = 200)
The data I used for this:
dput(PID50baseline)
structure(list(Cluster.Name = structure(c(13L, 14L, 1L, 2L, 3L,
4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 15L, 15L), .Label = c("Cluster
13", "Cluster 14", "Cluster 17", "Cluster 18", "Cluster 19", "Cluster 20",
"Cluster 27", "Cluster 35", "Cluster 36", "Cluster 40", "Cluster 41",
"Cluster 42", "Cluster 5", "Cluster 6", "Non-clonal"), class = "factor"),
Number = c(5L, 9L, 0L, 0L, 1L, 2L, 0L, 2L, 3L, 2L, 1L, 0L,
0L, 0L, 1L, 28L), Type = structure(c(1L, 1L, 1L, 1L, 1L,
1L, 1L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 2L, 1L), .Label = c("Defective",
"Intact"), class = "factor")), .Names = c("Cluster.Name",
"Number", "Type"), class = "data.frame", row.names = c(NA, -16L))
dput(PID50late)
structure(list(Cluster.Name = structure(c(13L, 14L, 1L, 2L, 3L,
4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 15L, 15L), .Label = c("Cluster 13",
"Cluster 14", "Cluster 17", "Cluster 18", "Cluster 19", "Cluster 20",
"Cluster 27", "Cluster 35", "Cluster 36", "Cluster 40", "Cluster 41",
"Cluster 42", "Cluster 5", "Cluster 6", "Non-clonal"), class = "factor"),
Number = c(2L, 10L, 2L, 2L, 1L, 0L, 5L, 0L, 5L, 0L, 3L, 3L,
2L, 2L, 18L, 59L), Type = structure(c(1L, 1L, 1L, 1L, 1L,
1L, 1L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 2L, 1L), .Label = c("Defective",
"Intact"), class = "factor")), .Names = c("Cluster.Name",
"Number", "Type"), class = "data.frame", row.names = c(NA, -16L))
I believe treemapify omits areas with a size of 0. This could be the reason for your problem. In other words, replacing 0 with a small positive value greater than 0 (and using 16 distinct colors) gives you something like this:
tweened$Number[tweened$Number==0] <- 1e-10
colors <- unname(randomcoloR::distinctColorPalette(nlevels(tweened$Cluster.Name)))
I can't figure out how to get the fill order to reverse. Basically, I'm trying to get the guide and the fill to match an intrinsic order of the words from positive to negative:
The guide, and the fill order, from top to bottom should be:
"Far better than I expected", (Filled at very top, at top of legend)
"A little better than I expected",
"About what I expected",
"A little worse than I expected",
"Far worse than I expected" (Filled at very bottom, at bottom of legend)
You'll need sample data:
dat <- structure(list(Banner = structure(c(2L, 2L, 2L, 2L, 2L, 1L, 1L,
1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L,
2L, 2L, 1L, 1L, 1L, 1L, 1L), .Label = c("Other", "Some Company"
), class = "factor"), Response = structure(c(1L, 2L, 3L, 4L,
5L, 1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L,
1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L),
.Label = c(
"Far better than I expected",
"A little better than I expected",
"About what I expected",
"A little worse than I expected",
"Far worse than I expected"), class = "factor"), Frequency = c(1L,
6L, 9L, 0L, 0L, 29L, 71L, 149L, 32L, 6L, 1L, 7L, 16L, 1L, 0L,
38L, 90L, 211L, 24L, 6L, 0L, 0L, 8L, 1L, 1L, 6L, 13L, 109L, 35L,
9L), Proportion = c(6, 38, 56, 0, 0, 10, 25, 52, 11, 2, 4, 28,
64, 4, 0, 10, 24, 57, 7, 2, 0, 0, 80, 10, 10, 3, 8, 63, 20, 5
), Phase = c("Phase 1", "Phase 1", "Phase 1", "Phase 1", "Phase 1",
"Phase 1", "Phase 1", "Phase 1", "Phase 1", "Phase 1", "Phase 2",
"Phase 2", "Phase 2", "Phase 2", "Phase 2", "Phase 2", "Phase 2",
"Phase 2", "Phase 2", "Phase 2", "Phase 3", "Phase 3", "Phase 3",
"Phase 3", "Phase 3", "Phase 3", "Phase 3", "Phase 3", "Phase 3",
"Phase 3")), .Names = c("Banner", "Response", "Frequency", "Proportion",
"Phase"),
row.names = c(NA, 30L),
sig = character(0),
comment = "Overall, my experience was... by Company", q1 = "", q2 = "",
class = c("survcsub", "data.frame"))
Position labels
dat <- ddply(dat, .(Banner, Phase), function(x) {
x$Pos <- (cumsum(x$Proportion) - 0.5*x$Proportion)
x
})
Plot
ggplot(dat, aes(Banner, Proportion/100, fill=Response,
label=ifelse(Proportion > 5, percent(Proportion/100), ""))) +
geom_bar(position="fill", stat="identity") +
geom_text(aes(Banner, Pos/100)) +
facet_grid(~Phase) +
scale_y_continuous(labels=percent) +
labs(x="\nCompany", y="\nProportion")
What I've tried:
dat$Response <- factor(dat$Response, levels=rev(dat$Response))
# No dice, reverses the colour of the scale but not the position of the fill
To change the order of values in stacked barplot you should use argument order= in aes() of geom_bar() and set name of column necessary for ordering (in this case Response). With function desc() you can set reverse order of bars.
Using your original data frame (without last line of factor()).
ggplot(dat, aes(Banner, Proportion/100, fill=Response,
label=ifelse(Proportion > 5, percent(Proportion/100), ""))) +
geom_bar(position="fill", stat="identity",aes(order=desc(Response))) +
geom_text(aes(Banner, Pos/100)) +
facet_grid(~Phase) +
scale_y_continuous(labels=percent) +
labs(x="\nCompany", y="\nProportion")
To get correct placement of labels, changed calculation of positions:
dat <- ddply(dat, .(Banner, Phase), function(x) {
x$Pos <- (100-cumsum(x$Proportion) + 0.5*x$Proportion)
x
})
I have the following data frame:
structure(list(X1 = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 4L, 4L,
4L, 4L, 4L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 6L, 6L, 6L
), .Label = c("1", "2", "3", "4", "5", "6"), class = "factor"),
X2 = structure(c(1L, 6L, 8L, 10L, 12L, 13L, 3L, 4L, 1L, 6L,
7L, 9L, 10L, 12L, 13L, 3L, 4L, 5L, 10L, 12L, 13L, 4L, 1L,
6L, 12L, 13L, 3L, 1L, 6L, 7L, 8L, 10L, 11L, 12L, 13L, 2L,
3L, 11L, 12L, 13L), .Label = c("I1", "I10", "I11", "I12",
"I13", "I2", "I3", "I4", "I5", "I6", "I7", "I8", "I9"), class = "factor")), .Names = c("X1",
"X2"), row.names = c(NA, -40L), class = "data.frame")
Where in X1 is the person number and in X2 the group to which the person belongs to. One person can be in different groups.
Now I want to draw a line from each person to each group he belongs to. With plot() I solved it this way:
plot(0, xlim=c(0,1), ylim=c(0,1), type="n", axes=FALSE, xlab="", ylab="")
factor.to.int <- function(f) {
(as.integer(f) - 1) / (length(levels(f)) - 1)
}
segments(factor.to.int(data$X1), 0, factor.to.int(data$X2), 1, col=data$X1)
axis(1, at = seq(0, 1, by = 1 / (length(levels(data$X1)) - 1)), labels = levels(data$X1))
axis(3, at = seq(0, 1, by = 1 / (length(levels(data$X2)) - 1)), labels = levels(data$X2))
The result looks like this:
Now I wondering how I can do this with ggplot2?
Thanks for your help!
A simple ggplot2 version of your graph is possible by using geom_segment() and transforming the data much like you did for the base graphics version. I've also included an arguably more polished version, using some of the more advanced customization options in ggplot2.
# Using ggplot2 version 0.9.2.1
library(ggplot2)
dat$x1_norm = rangeTransform(as.integer(dat$X1))
dat$x2_norm = rangeTransform(as.integer(dat$X2))
dat$y1 = 0
dat$y2 = 1
# Simple version.
p1 = ggplot(dat, aes(x=x1_norm, xend=x2_norm, y=y1, yend=y2, colour=X1)) +
geom_segment(size=1.2) +
scale_colour_brewer(palette="Set1", name="Person")
ggsave(plot=p1, filename="plot_1.png", height=3.5, width=6)
# Fancy version.
# Create separate data.frames to manually specify axis ticks and axis text.
axis_1 = data.frame(x=rangeTransform(as.integer(unique(dat$X1))),
y=0, label=as.character(unique(dat$X1)))
axis_2 = data.frame(x=rangeTransform(as.integer(unique(dat$X2))),
y=1, label=as.character(unique(dat$X2)))
p2 = ggplot(data=dat) +
theme_bw() +
theme(axis.title=element_blank()) +
theme(axis.text=element_blank()) +
theme(axis.ticks=element_blank()) +
theme(panel.grid=element_blank()) +
geom_segment(aes(x=x1_norm, xend=x2_norm, y=y1, yend=y2, colour=X1),
size=1.2) +
geom_segment(x=0, xend=1, y=0, yend=0, size=0.7) +
geom_segment(x=0, xend=1, y=1, yend=1, size=0.7) +
scale_colour_brewer(palette="Set1", name="Person") +
scale_y_continuous(limits=c(-0.2, 1.2), expand=c(0, 0)) +
geom_segment(data=axis_1, aes(x=x, xend=x, y=y, yend=y-0.025), size=0.7) +
geom_segment(data=axis_2, aes(x=x, xend=x, y=y, yend=y+0.025), size=0.7) +
geom_text(data=axis_1, aes(label=label, x=x, y=y - 0.075)) +
geom_text(data=axis_2, aes(label=label, x=x, y=y + 0.075))
ggsave(plot=p2, filename="plot_2.png", height=3.5, width=6)