The main goal of this plot is to make a comparison between A and B in three groups, but I want to have one, two, and three besides them, as well. Using below code, I can make a grouped barplot which is almost what I want. But I need to have the names of each bar below it since the legend is so ugly.
How can I do it?
m.names <- c("A1","B1","one","A2","B2","two","A3","B3","three")
m.group <- c(1,1,1,2,2,2,3,3,3)
m.value <- c(5,10,1,20,15,2,10,20,3)
df <- data.frame(m.names, m.group, m.value)
df
ggplot(df, aes(x = m.group, y = m.value)) +
geom_bar(aes(fill = m.names), position = "dodge", stat = "identity") +
scale_fill_manual(values=c("gray75", "gray75","gray75", "gray40","gray40","gray40", "blue", "red", "green" ))
Adding geom_text and making sure it's dodged in the same way as the bars:
# width = 0.9 should be the default for dodged bars but set
# it explicitly to be sure
dodger = position_dodge(width = 0.9)
ggplot(df, aes(x = m.group, y = m.value)) +
geom_bar(aes(fill = m.names), position = dodger, stat = "identity") +
scale_fill_manual(values=c("gray75", "gray75","gray75", "gray40","gray40","gray40", "blue", "red", "green" ),
guide = "none") +
geom_text(aes(x = m.group, group = m.names, label = m.names, y = 0),
position = dodger,
vjust = 1, colour = "black")
Faceting by group may work for this case as well:
fill.values = c("gray75", "gray75","gray75",
"gray40","gray40","gray40",
"blue", "red", "green")
names(fill.values) = levels(df$m.names)
> fill.values
A1 A2 A3 B1 B2 B3 one three two
"gray75" "gray75" "gray75" "gray40" "gray40" "gray40" "blue" "red" "green"
ggplot(df,
aes(x = m.names, y = m.value, fill = m.names)) +
geom_col() +
scale_fill_manual(values = fill.values, guide = F) +
facet_wrap(~m.group, scales = "free_x") +
theme_bw()
Seems like you might want this:
require(ggplot2)
ggplot(df, aes(x = m.names, y = m.value)) +
geom_bar(aes(fill = m.names), stat = "identity") +
scale_fill_manual(values=c("gray75", "gray75","gray75", "gray40",
"gray40","gray40", "blue", "red", "green" )) +
facet_grid(~m.group, scales = "free_x", space = "free_x") +
theme(strip.text.x = element_blank(),
panel.spacing = unit(0, "lines"))
Output:
The trick is to plot x by m.names here instead of m.groups. Then later we can facet the bars by m.group to keep them presented the way you want.
We could use geom_label
dodger = position_dodge(width = 0.9)
ggplot(df, aes(x = m.group, y = m.value)) +
geom_bar(aes(fill = m.names), position = dodger, stat = "identity") +
scale_fill_manual(values=c("gray75", "gray75","gray75",
"gray40","gray40","gray40", "blue", "red", "green" ),
guide = "none") +
theme(axis.text.x=element_blank(),
axis.ticks.x=element_blank()) +
geom_label(aes(x = m.group, group = m.names, label = m.names, y = 0),
position = dodger,
vjust = 1, colour = "black")
Related
i need the plan legend
How to add a legend manually for geom_line
ggplot(data = impact_end_Current_yr_m_actual, aes(x = month, y = gender_value)) +
geom_col(aes(fill = gender))+theme_classic()+
geom_line(data = impact_end_Current_yr_m_plan, aes(x=month, y= gender_value, group=1),color="#288D55",size=1.2)+
geom_point(data = impact_end_Current_yr_m_plan, aes(x=month, y=gender_value))+
theme(axis.line.y = element_blank(),axis.ticks = element_blank(),legend.position = "bottom", axis.text.x = element_text(face = "bold", color = "black", size = 10, angle = 0, hjust = 1))+
labs(x="", y="End Beneficiaries (in Num)", fill="")+
scale_fill_manual(values=c("#284a8d", "#00B5CE","#0590eb","#2746c2"))+
scale_y_continuous(labels = function(x) format(x, scientific = FALSE)
The neatest way to do it I think is to add colour = "[label]" into the aes() section of geom_line() then put the manual assigning of a colour into scale_colour_manual() here's an example from mtcars (apologies that it uses stat_summary instead of geom_line but does the same trick):
library(tidyverse)
mtcars %>%
ggplot(aes(gear, mpg, fill = factor(cyl))) +
stat_summary(geom = "bar", fun = mean, position = "dodge") +
stat_summary(geom = "line",
fun = mean,
size = 3,
aes(colour = "Overall mean", group = 1)) +
scale_fill_discrete("") +
scale_colour_manual("", values = "black")
Created on 2020-12-08 by the reprex package (v0.3.0)
The limitation here is that the colour and fill legends are necessarily separate. Removing labels (blank titles in both scale_ calls) doesn't them split them up by legend title.
In your code you would probably want then:
...
ggplot(data = impact_end_Current_yr_m_actual, aes(x = month, y = gender_value)) +
geom_col(aes(fill = gender))+
geom_line(data = impact_end_Current_yr_m_plan,
aes(x=month, y= gender_value, group=1, color="Plan"),
size=1.2)+
scale_color_manual(values = "#288D55") +
...
(but I cant test on your data so not sure if it works)
I have a geom_jitter plot showing Variables between 2 samples, I would like to include the Group-variable parameters on the left of the plot, setting a separation by lines like in the figure below. Thus, Variables are organised by Group.
Here is a reproducible example:
data<- tibble::tibble(
Variable = c("A","B","C","D","E", "F"),
Group = c("Asia","Asia","Europe","Europe","Africa","America"),
sample1 = c(0.38,0.22,0.18,0.12,0.1,0),
sample2 = c(0.23,0.2,0,0.12,0.11,0.15))
library(reshape2)
data2<- melt(data,
id.vars=c("Variable", "Group"),
measure.vars=c("sample1", "sample2"),
variable.name="Sample",
value.name="value")
data22[is.na(data22)] <- 0
library(ggplot2)
ggplot(data2, aes(x = Sample, y = Variable, label=NA)) +
geom_point(aes(size = value, colour = value)) +
geom_text(hjust = 1, size = 2) +
# scale_size(range = c(1,3)) +
theme_bw()+
scale_color_gradient(low = "lightblue", high = "darkblue")
Here is the current output I have:
And this is the format I would like:
To get a polished version of the plot most similar to your ideal plot, you can use facet_grid() plus some theme() customization.
ggplot(data2, aes(x = Sample, y = Variable, label=NA)) +
geom_point(aes(size = value, colour = value)) +
geom_text(hjust = 1, size = 2) +
# scale_size(range = c(1,3)) +
theme_bw()+
scale_color_gradient(low = "lightblue", high = "darkblue") +
facet_grid(Group~., scales = "free", switch = "y") +
theme(strip.placement = "outside",
strip.text.y = element_text(angle = 180),
panel.spacing = unit(0, "cm"))
I'm working on some data on party polarization (something like this) and used geom_dumbbell from ggalt and ggplot2. I keep getting the same aes error and other solutions in the forum did not address this as effectively. This is my sample data.
df <- data_frame(policy=c("Not enough restrictions on gun ownership", "Climate change is an immediate threat", "Abortion should be illegal"),
Democrats=c(0.54, 0.82, 0.30),
Republicans=c(0.23, 0.38, 0.40),
diff=sprintf("+%d", as.integer((Democrats-Republicans)*100)))
I wanted to keep order of the plot, so converted policy to factor and wanted % to be shown only on the first line.
df <- arrange(df, desc(diff))
df$policy <- factor(df$policy, levels=rev(df$policy))
percent_first <- function(x) {
x <- sprintf("%d%%", round(x*100))
x[2:length(x)] <- sub("%$", "", x[2:length(x)])
x
}
Then I used ggplot that rendered something close to what I wanted.
gg2 <- ggplot()
gg2 <- gg + geom_segment(data = df, aes(y=country, yend=country, x=0, xend=1), color = "#b2b2b2", size = 0.15)
# making the dumbbell
gg2 <- gg + geom_dumbbell(data=df, aes(y=country, x=Democrats, xend=Republicans),
size=1.5, color = "#B2B2B2", point.size.l=3, point.size.r=3,
point.color.l = "#9FB059", point.color.r = "#EDAE52")
I then wanted the dumbbell to read Democrat and Republican on top to label the two points (like this). This is where I get the error.
gg2 <- gg + geom_text(data=filter(df, country=="Government will not control gun violence"),
aes(x=Democrats, y=country, label="Democrats"),
color="#9fb059", size=3, vjust=-2, fontface="bold", family="Calibri")
gg2 <- gg + geom_text(data=filter(df, country=="Government will not control gun violence"),
aes(x=Republicans, y=country, label="Republicans"),
color="#edae52", size=3, vjust=-2, fontface="bold", family="Calibri")
Any thoughts on what I might be doing wrong?
I think it would be easier to build your own "dumbbells" with geom_segment() and geom_point(). Working with your df and changing the variable refences "country" to "policy":
library(tidyverse)
# gather data into long form to make ggplot happy
df2 <- gather(df,"party", "value", Democrats:Republicans)
ggplot(data = df2, aes(y = policy, x = value, color = party)) +
# our dumbell
geom_path(aes(group = policy), color = "#b2b2b2", size = 2) +
geom_point(size = 7, show.legend = FALSE) +
# the text labels
geom_text(aes(label = party), vjust = -1.5) + # use vjust to shift text up to no overlap
scale_color_manual(values = c("Democrats" = "blue", "Republicans" = "red")) + # named vector to map colors to values in df2
scale_x_continuous(limits = c(0,1), labels = scales::percent) # use library(scales) nice math instead of pasting
Produces this plot:
Which has some overlapping labels. I think you could avoid that if you use just the first letter of party like this:
ggplot(data = df2, aes(y = policy, x = value, color = party)) +
geom_path(aes(group = policy), color = "#b2b2b2", size = 2) +
geom_point(size = 7, show.legend = FALSE) +
geom_text(aes(label = gsub("^(\\D).*", "\\1", party)), vjust = -1.5) + # just the first letter instead
scale_color_manual(values = c("Democrats" = "blue", "Republicans" = "red"),
guide = "none") +
scale_x_continuous(limits = c(0,1), labels = scales::percent)
Only label the top issue with names:
ggplot(data = df2, aes(y = policy, x = value, color = party)) +
geom_path(aes(group = policy), color = "#b2b2b2", size = 2) +
geom_point(size = 7, show.legend = FALSE) +
geom_text(data = filter(df2, policy == "Not enough restrictions on gun ownership"),
aes(label = party), vjust = -1.5) +
scale_color_manual(values = c("Democrats" = "blue", "Republicans" = "red")) +
scale_x_continuous(limits = c(0,1), labels = scales::percent)
I use bars and line to create my plot. The demo code is:
timestamp <- seq(as.Date('2010-01-01'),as.Date('2011-12-01'),by="1 mon")
data1 <- rnorm(length(timestamp), 3000, 30)
data2 <- rnorm(length(timestamp), 30, 3)
df <- data.frame(timestamp, data1, data2)
p <- ggplot()
p <- p + geom_histogram(data=df,aes(timestamp,data1),colour="black",stat="Identity",bindwidth=10)
p <- p + geom_line(data=df,aes(timestamp,y=data2*150),colour="red")
p <- p + scale_y_continuous(sec.axis = sec_axis(~./150, name = "data2"))
p <- p + scale_colour_manual(name="Parameter", labels=c("data1", "data2"), values = c('black', 'red'))
p <- p+ scale_shape_manual(name="Parameter", labels=c("data1", "data2"), values = c(15,95))
p
This results in a plot like this:
This figure does not have a legend. I followed this answer to create a customized legend but it is not working in my case. I want a square and line shape in my legend corresponding to bars and line. How can we get it?
I want legend as shown in below image:
For the type of data you want to display, geom_bar is a better fit then geom_histogram. When you to manipulate the appaerance of the legend(s), you need to place the colour = ... parts inside the aes. To get the desired result it probably best to use different types of legend for the line and the bars. In that way you are better able to change the appearance of the legends with guide_legend and override.aes.
A proposal for your problem:
ggplot(data = df) +
geom_bar(aes(x = timestamp, y = data1, colour = "black"),
stat = "Identity", fill = NA) +
geom_line(aes(x = timestamp, y = data2*150, linetype = "red"), colour = "red", size = 1) +
scale_y_continuous(sec.axis = sec_axis(~./150, name = "data2")) +
scale_linetype_manual(labels = "data2", values = "solid") +
scale_colour_manual(name = "Parameter\n", labels = "data1", values = "black") +
guides(colour = guide_legend(override.aes = list(colour = "black", size = 1),
order = 1),
linetype = guide_legend(title = NULL,
override.aes = list(linetype = "solid",
colour = "red",
size = 1),
order = 2)) +
theme_minimal() +
theme(legend.key = element_rect(fill = "white", colour = NA),
legend.spacing = unit(0, "lines"))
which gives:
This is my data:
> sum.ex
Timepoint mean n sd Time Group
A1 A1-All 1.985249 26 1.000180 A1 All
A1-pT2D A1-pT2D 1.913109 13 1.012633 A1 pT2D
A1-Control A1-Control 2.934105 13 2.472951 A1 Control
B1 B1-All 2.555601 25 1.939970 B1 All
B1-pT2D B1-pT2D 2.057389 13 1.023416 B1 pT2D
B1-Control B1-Control 2.145555 12 1.089522 B1 Control
This is my code:
png('ex')
ggplot(sum.ex, aes(x = Timepoint, y = mean)) +
geom_bar(width = 0.5, position = position_dodge(width = 200), stat="identity", aes(fill = Group)) +
geom_errorbar(aes(ymin=mean-sd, ymax=mean+sd), size = 1, shape = 1, width = 0.2) +
scale_fill_manual(values = c("#333333", "#FF0000", "#0000FF")) +
xlab(NULL) +
ggtitle("PLIN1") + theme_bw() + theme(panel.grid.major = element_blank())
dev.off()
This is the output:
However, I want to have Black+Red+Blue really close, then a space and then Black+Red+Blue really close again.
Thank you!
I think this is easiest to achieve if you use x = Time and fill = Group. Something like:
dodge <- position_dodge(width = 0.5)
ggplot(df, aes(x = Time, y = mean, fill = Group)) +
geom_bar(width = 0.5, stat="identity", position = dodge) +
geom_errorbar(aes(ymin=mean-sd, ymax=mean+sd),
position = dodge, size = 1, shape = 1, width = 0.2) +
scale_fill_manual(values = c("#333333", "#FF0000", "#0000FF")) +
theme_bw() +
theme(panel.grid.major = element_blank())
Plot against Time only, then position_dodge has meaning for the bars (there are 3 observations per group). Use position_dodge with width close to the bar width. Add group=Group to make the errorbars behave like the bars (you need it since they don't have colour aesthetic to distinguish them). Use the same position_dodge width as before to align them properly.
ggplot(sum.ex, aes(x = Time, y = mean)) +
geom_bar(width = 0.5, position = position_dodge(width = 0.5), stat = "identity", aes(fill = Group)) +
geom_errorbar(aes(ymin=mean-sd, ymax=mean+sd, group=Group), position=position_dodge(width = 0.5), size = 1, shape = 1, width = 0.2) +
scale_fill_manual(values = c("#333333", "#FF0000", "#0000FF")) +
xlab(NULL) +
ggtitle("PLIN1") + theme_bw() + theme(panel.grid.major = element_blank())