In R I'm trying to generate a plot where I want to apply unique colors, line types, transparencies, and line thicknesses by case grouping. As currently implemented two legend plots are generated instead of one. The second legend plot is the only one that I can change the legend title. Presumably I've made a mistake any help would be greatly appreciated.
Ultimately I want to generate a single legend and have the style changes and labeling changes take effect.
library(ggplot2)
temp_df <- data.frame(year = integer(50), value = numeric(50), case = character(50))
temp_df$year <- 1:50
temp_df$value <- runif(50)
temp_df$case <- "A"
df <- temp_df
temp_df$value <- runif(50)
temp_df$case <- "B"
df <- rbind(df, temp_df)
LineTypes <- c("solid", "dotted")
colors <- c("red", "black")
linealphas <- c(1, .8)
linesizes <- c(1, 2)
Plot <- ggplot(df, aes(x = year, y = value, group = case))+
geom_line(aes(linetype = case, color = case, size = case, alpha = case))+
scale_linetype_manual(values = LineTypes)+
scale_color_manual(values = colors)+
scale_y_continuous(limits = c(0, 1), labels = scales::percent)+
scale_alpha_manual(values = linealphas)+
scale_size_manual(values = linesizes)+
xlab("Year")+
ylab("Percentage%")+
labs(color = "Scenario")+
theme_minimal()
Plot
If you want ggplot to merge the legends then they all have to have the same title. You can specify the legend title with the name argument in the scales:
ggplot(df, aes(x = year, y = value, group = case))+
geom_line(aes(linetype = case, color = case, size = case, alpha = case)) +
scale_linetype_manual(values = LineTypes, name = "Scenario")+
scale_color_manual(values = colors, name = "Scenario")+
scale_y_continuous(limits = c(0, 1), labels = scales::percent)+
scale_alpha_manual(values = linealphas, name = "Scenario")+
scale_size_manual(values = linesizes, name = "Scenario")+
xlab("Year")+
ylab("Percentage%")+
theme_minimal()
A coworker pointed out a resolution to me the key was to remove the guides so that only one of styles that I had defined was being used for the legend.
guides(size = FALSE)+
guides(alpha = FALSE)+
guides(linetype = FALSE)+
His explanation for this was that R doesn't recognize that the vector of factors defining the properties of the plot are necessarily related. As a result it will generate multiple legends when only one is desired.
library(ggplot2)
temp_df<-data.frame(year=integer(50),value=numeric(50),case=character(50))
temp_df$year<-1:50
temp_df$value<-runif(50)
temp_df$case<-"A"
df<-temp_df
temp_df$value<-runif(50)
temp_df$case<-"B"
df<-rbind(df,temp_df)
LineTypes<-c("solid","dotted")
colors<-c("red","black")
linealphas<-c(1,.8)
linesizes<-c(1,2)
Plot<-ggplot(df,aes(x=year,y=value,group=case))+
geom_line(aes(linetype=case, color=case, size=case, alpha =case))+
scale_linetype_manual(values=LineTypes)+
scale_color_manual(values=colors)+
scale_y_continuous(limits=c(0,1),labels = scales::percent)+
scale_alpha_manual(values=linealphas)+
scale_size_manual(values=linesizes)+
xlab("Year")+
ylab("Percentage%")+
labs(color = "Scenario")+
guides(size = FALSE)+
guides(alpha = FALSE)+
guides(linetype = FALSE)+
theme_minimal()
Plot
Can't you just remove the line "labs(color = "Scenario")"?
This is the plot that gets generated. Not sure if it's missing anything that you need.
The result seems fine to me:
Related
I am trying to make a bar chart with line plots as well. The graph has created fine but the legend does not want to add the line plots to the legend.
I have tried so many different ways of adding these to the legend including:
ggplot Legend Bar and Line in Same Graph
None of which have worked. show.legend also seems to have been ignored in the geom_line aes.
My code to create the graph is as follows:
ggplot(first_q, aes(fill = Segments)) +
geom_bar(aes(x= Segments, y= number_of_new_customers), stat =
"identity") + theme(axis.text.x = element_blank()) +
scale_y_continuous(expand = c(0, 0), limits = c(0,3000)) +
ylab('Number of Customers') + xlab('Segments') +
ggtitle('Number Customers in Q1 by Segments') +theme(plot.title =
element_text(hjust = 0.5)) +
geom_line(aes(x= Segments, y=count) ,stat="identity",
group = 1, size = 1.5, colour = "darkred", alpha = 0.9, show.legend =
TRUE) +
geom_line(aes(x= Segments, y=bond_count)
,stat="identity", group = 1, size = 1.5, colour = "blue", alpha =
0.9) +
geom_line(aes(x= Segments, y=variable_count)
,stat="identity", group = 1, size = 1.5, colour = "darkgreen",
alpha = 0.9) +
geom_line(aes(x= Segments, y=children_count)
,stat="identity", group = 1, size = 1.5, colour = "orange", alpha
= 0.9) +
guides(fill=guide_legend(title="Segments")) +
scale_color_discrete(name = "Prod", labels = c("count", "bond_count", "variable_count", "children_count)))
I am fairly new to R so if any further information is required or if this question could be better represented then please let me know.
Any help is greatly appreciated.
Alright, you need to remove a little bit of your stuff. I used the mtcars dataset, since you did not provide yours. I tried to keep your variable names and reduced the plot to necessary parts. The code is as follows:
first_q <- mtcars
first_q$Segments <- mtcars$mpg
first_q$val <- seq(1,nrow(mtcars))
first_q$number_of_new_costumers <- mtcars$hp
first_q$type <- "Line"
ggplot(first_q) +
geom_bar(aes(x= Segments, y= number_of_new_costumers, fill = "Bar"), stat =
"identity") + theme(axis.text.x = element_blank()) +
scale_y_continuous(expand = c(0, 0), limits = c(0,3000)) +
geom_line(aes(x=Segments,y=val, linetype="Line"))+
geom_line(aes(x=Segments,y=disp, linetype="next line"))
The answer you linked already gave the answer, but i try to explain. You want to plot the legend by using different properties of your data. So if you want to use different lines, you can declare this in your aes. This is what get's shown in your legend. So i used two different geom_lines here. Since the aes is both linetype, both get shown at the legend linetype.
the plot:
You can adapt this easily to your use. Make sure you using known keywords for the aesthetic if you want to solve it this way. Also you can change the title names afterwards by using:
labs(fill = "costum name")
If you want to add colours and the same line types, you can do customizing by using scale_linetype_manual like follows (i did not use fill for the bars this time):
library(ggplot2)
first_q <- mtcars
first_q$Segments <- mtcars$mpg
first_q$val <- seq(1,nrow(mtcars))
first_q$number_of_new_costumers <- mtcars$hp
first_q$type <- "Line"
cols = c("red", "green")
ggplot(first_q) +
geom_bar(aes(x= Segments, y= number_of_new_costumers), stat =
"identity") + theme(axis.text.x = element_blank()) +
scale_y_continuous(expand = c(0, 0), limits = c(0,3000)) +
geom_line(aes(x=Segments,y=val, linetype="solid"), color = "red", alpha = 0.4)+
geom_line(aes(x=Segments,y=disp, linetype="second"), color ="green", alpha = 0.5)+
scale_linetype_manual(values = c("solid","solid"),
guide = guide_legend(override.aes = list(colour = cols)))
I have a chart that shows mobile usage by operating system. I'd like to add vertical lines to identify when those operating systems were released. I'll go through the chart and then the code.
The chart -
The code -
dev %>%
group_by(os) %>%
mutate(monthly_change = prop - lag(prop)) %>%
ggplot(aes(month, monthly_change, color = os)) +
geom_line() +
geom_vline(xintercept = as.numeric(ymd("2013-10-01"))) +
geom_text(label = "KitKat", x = as.numeric(ymd("2013-10-01")) + 80, y = -.5)
Instead of adding the text in the plot, I'd like to create a legend to identify each of the lines. I'd like to give each of them its own color and then have a legend to identify each. Something like this -
Can I make my own custom legend like that?
1) Define a data frame that contains the line data and then use geom_vline with it. Note that BOD is a data frame that comes with R.
line.data <- data.frame(xintercept = c(2, 4), Lines = c("lower", "upper"),
color = c("red", "blue"), stringsAsFactors = FALSE)
ggplot(BOD, aes( Time, demand ) ) +
geom_point() +
geom_vline(aes(xintercept = xintercept, color = Lines), line.data, size = 1) +
scale_colour_manual(values = line.data$color)
2) Alternately put the labels right on the plot itself to avoid an extra legend. Using the line.data frame above. This also has the advantage of avoiding possible multiple legends with the same aesthetic.
ggplot(BOD, aes( Time, demand ) ) +
geom_point() +
annotate("text", line.data$xintercept, max(BOD$demand), hjust = -.25,
label = line.data$Lines) +
geom_vline(aes(xintercept = xintercept), line.data, size = 1)
3) If the real problem is that you want two color legends then there are two packages that can help.
3a) ggnewscale Any color geom that appears after invoking new_scale_color will get its own scale.
library(ggnewscale)
BOD$g <- gl(2, 3, labels = c("group1", "group2"))
line.data <- data.frame(xintercept = c(2, 4), Lines = c("lower", "upper"),
color = c("red", "blue"), stringsAsFactors = FALSE)
ggplot(BOD, aes( Time, demand ) ) +
geom_point(aes(colour = g)) +
scale_colour_manual(values = c("red", "orange")) +
new_scale_color() +
geom_vline(aes(xintercept = xintercept, colour = line.data$color), line.data,
size = 1) +
scale_colour_manual(values = line.data$color)
3b) relayer The experimental relayer package (only on github) allows one to define two color aethetics, color and color2, say, and then have separate scales for each one.
library(dplyr)
library(relayer)
BOD$g <- gl(2, 3, labels = c("group1", "group2"))
ggplot(BOD, aes( Time, demand ) ) +
geom_point(aes(colour = g)) +
geom_vline(aes(xintercept = xintercept, colour2 = line.data$color), line.data,
size = 1) %>% rename_geom_aes(new_aes = c("colour" = "colour2")) +
scale_colour_manual(aesthetics = "colour", values = c("red", "orange")) +
scale_colour_manual(aesthetics = "colour2", values = line.data$color)
You can definitely make your own custom legend, but it is a bit complicated, so I'll take you through it step-by-step with some fake data.
The fake data contained 100 samples from a normal distribution (monthly_change for your data), 5 groupings (similar to the os variable in your data) and a sequence of dates from a random starting point.
library(tidyverse)
library(lubridate)
y <- rnorm(100)
df <- tibble(y) %>%
mutate(os = factor(rep_len(1:5, 100)),
date = seq(from = ymd('2013-01-01'), by = 1, length.out = 100))
You already use the colour aes for your call to geom_line, so you will need to choose a different aes to map onto the calls to geom_vline. Here, I use linetype and a call to scale_linetype_manual to manually edit the linetype legend to how I want it.
ggplot(df, aes(x = date, y = y, colour = os)) +
geom_line() +
# set `xintercept` to your date and `linetype` to the name of the os which starts
# at that date in your `aes` call; set colour outside of the `aes`
geom_vline(aes(xintercept = min(date),
linetype = 'os 1'), colour = 'red') +
geom_vline(aes(xintercept = median(date),
linetype = 'os 2'), colour = 'blue') +
# in the call to `scale_linetype_manual`, `name` will be the legend title;
# set `values` to 1 for each os to force a solid vertical line;
# use `guide_legend` and `override.aes` to change the colour of the lines in the
# legend to match the colours in the calls to `geom_vline`
scale_linetype_manual(name = 'lines',
values = c('os 1' = 1,
'os 2' = 1),
guide = guide_legend(override.aes = list(colour = c('red',
'blue'))))
And there you go, a nice custom legend. Please do remember next time that if you can provide your data, or a minimally reproducible example, we can better answer your question without having to generate fake data.
I plot a 2 geom_point graph with the following code:
source("http://www.openintro.org/stat/data/arbuthnot.R")
library(ggplot2)
ggplot() +
geom_point(aes(x = year,y = boys),data=arbuthnot,colour = '#3399ff') +
geom_point(aes(x = year,y = girls),data=arbuthnot,shape = 17,colour = '#ff00ff') +
xlab(label = 'Year') +
ylab(label = 'Rate')
I simply want to know how to add a legend on the right side. With the same shape and color. Triangle pink should have the legend "woman" and blue circle the legend "men". Seems quite simple but after many trial I could not do it. (I'm a beginner with ggplot).
If you rename your columns of the original data frame and then melt it into long format withreshape2::melt, it's much easier to handle in ggplot2. By specifying the color and shape aesthetics in the ggplot command, and specifying the scales for the colors and shapes manually, the legend will appear.
source("http://www.openintro.org/stat/data/arbuthnot.R")
library(ggplot2)
library(reshape2)
names(arbuthnot) <- c("Year", "Men", "Women")
arbuthnot.melt <- melt(arbuthnot, id.vars = 'Year', variable.name = 'Sex',
value.name = 'Rate')
ggplot(arbuthnot.melt, aes(x = Year, y = Rate, shape = Sex, color = Sex))+
geom_point() + scale_color_manual(values = c("Women" = '#ff00ff','Men' = '#3399ff')) +
scale_shape_manual(values = c('Women' = 17, 'Men' = 16))
This is the trick that I usually use. Add colour argument to the aes and use it as an indicator for the label names.
ggplot() +
geom_point(aes(x = year,y = boys, colour = 'Boys'),data=arbuthnot) +
geom_point(aes(x = year,y = girls, colour = 'Girls'),data=arbuthnot,shape = 17) +
xlab(label = 'Year') +
ylab(label = 'Rate')
Here is a way of doing this without using reshape::melt. reshape::melt works, but you can get into a bind if you want to add other things to the graph, such as line segments. The code below uses the original organization of data. The key to modifying the legend is to make sure the arguments to scale_color_manual(...) and scale_shape_manual(...) are identical otherwise you will get two legends.
source("http://www.openintro.org/stat/data/arbuthnot.R")
library(ggplot2)
library(reshape2)
ptheme <- theme (
axis.text = element_text(size = 9), # tick labels
axis.title = element_text(size = 9), # axis labels
axis.ticks = element_line(colour = "grey70", size = 0.25),
panel.background = element_rect(fill = "white", colour = NA),
panel.border = element_rect(fill = NA, colour = "grey70", size = 0.25),
panel.grid.major = element_line(colour = "grey85", size = 0.25),
panel.grid.minor = element_line(colour = "grey93", size = 0.125),
panel.margin = unit(0 , "lines"),
legend.justification = c(1, 0),
legend.position = c(1, 0.1),
legend.text = element_text(size = 8),
plot.margin = unit(c(0.1, 0.1, 0.1, 0.01), "npc") # c(bottom, left, top, right), values can be negative
)
cols <- c( "c1" = "#ff00ff", "c2" = "#3399ff" )
shapes <- c("s1" = 16, "s2" = 17)
p1 <- ggplot(data = arbuthnot, aes(x = year))
p1 <- p1 + geom_point(aes( y = boys, color = "c1", shape = "s1"))
p1 <- p1 + geom_point(aes( y = girls, color = "c2", shape = "s2"))
p1 <- p1 + labs( x = "Year", y = "Rate" )
p1 <- p1 + scale_color_manual(name = "Sex",
breaks = c("c1", "c2"),
values = cols,
labels = c("boys", "girls"))
p1 <- p1 + scale_shape_manual(name = "Sex",
breaks = c("s1", "s2"),
values = shapes,
labels = c("boys", "girls"))
p1 <- p1 + ptheme
print(p1)
output results
Here is an answer based on the tidyverse package. Where one can use the pipe, %>%, to chain functions together. Creating the plot in one continues manner, omitting the need to create temporarily variables. More on the pipe can be found in this post What does %>% function mean in R?
As far as I know, legends in ggplot2 are only based on aesthetic variables. So to add a discrete legend one uses a category column, and change the aesthetics according to the category. In ggplot this is for example done by aes(color=category).
So to add two (or more) different variables of a data frame to the legends, one needs to transform the data frame such that we have a category column telling us which column (variable) is being plotted, and a second column that actually holds the value. The tidyr::gather function, that was also loaded by tidyverse, does exactly that.
Then one creates the legend by just specifying which aesthetics variables need to be different. In this example the code would look as follows:
source("http://www.openintro.org/stat/data/arbuthnot.R")
library(tidyverse)
arbuthnot %>%
rename(Year=year,Men=boys,Women=girls) %>%
gather(Men,Women,key = "Sex",value = "Rate") %>%
ggplot() +
geom_point(aes(x = Year, y=Rate, color=Sex, shape=Sex)) +
scale_color_manual(values = c("Men" = "#3399ff","Women"= "#ff00ff")) +
scale_shape_manual(values = c("Men" = 16, "Women" = 17))
Notice that tidyverse package also automatically loads in the ggplot2 package. An overview of the packages installed can be found on their website tidyverse.org.
In the code above I also used the function dplyr::rename (also loaded by tidyverse) to first rename the columns to the wanted labels. Since the legend automatically takes the labels equal to the category names.
There is a second way to renaming labels of legend, which involves specifying the labels explicitly in the scale_aesthetic_manual functions by the labels = argument. For examples see legends cookbook. But is not recommended since it gets messy quickly with more variables.
I want to remove the color line from a fill legend for a ggplot. I usually use guide_legend(override.aes = ...) to modify legend aesthetics - works great for points, lines, alpha, etc., but it's not working for my color aesthetic. What am I doing wrong?
# generate data
set.seed(47)
data = data.frame(year = rep(2000:2004, 3),
value = runif(15),
group = rep(c("A", "B", "C"), each = 5))
# create the plot
p = ggplot(data, aes(x = year, y = value, fill = group)) +
geom_area(position = position_fill(), color = "white") +
scale_fill_grey()
# this should modify the fill legend to remove the colored line
# but the line is still there
p + guides(fill = guide_legend(override.aes = list(color = NA)))
This was one of the cases where colour needed to be spelt with u. Adding the u made override.aes work just fine. ggplot2 releases since 2016 have fixed this bug, and you can use either spelling.
p + guides(fill = guide_legend(override.aes = list(colour = NA)))
I plot a 2 geom_point graph with the following code:
source("http://www.openintro.org/stat/data/arbuthnot.R")
library(ggplot2)
ggplot() +
geom_point(aes(x = year,y = boys),data=arbuthnot,colour = '#3399ff') +
geom_point(aes(x = year,y = girls),data=arbuthnot,shape = 17,colour = '#ff00ff') +
xlab(label = 'Year') +
ylab(label = 'Rate')
I simply want to know how to add a legend on the right side. With the same shape and color. Triangle pink should have the legend "woman" and blue circle the legend "men". Seems quite simple but after many trial I could not do it. (I'm a beginner with ggplot).
If you rename your columns of the original data frame and then melt it into long format withreshape2::melt, it's much easier to handle in ggplot2. By specifying the color and shape aesthetics in the ggplot command, and specifying the scales for the colors and shapes manually, the legend will appear.
source("http://www.openintro.org/stat/data/arbuthnot.R")
library(ggplot2)
library(reshape2)
names(arbuthnot) <- c("Year", "Men", "Women")
arbuthnot.melt <- melt(arbuthnot, id.vars = 'Year', variable.name = 'Sex',
value.name = 'Rate')
ggplot(arbuthnot.melt, aes(x = Year, y = Rate, shape = Sex, color = Sex))+
geom_point() + scale_color_manual(values = c("Women" = '#ff00ff','Men' = '#3399ff')) +
scale_shape_manual(values = c('Women' = 17, 'Men' = 16))
This is the trick that I usually use. Add colour argument to the aes and use it as an indicator for the label names.
ggplot() +
geom_point(aes(x = year,y = boys, colour = 'Boys'),data=arbuthnot) +
geom_point(aes(x = year,y = girls, colour = 'Girls'),data=arbuthnot,shape = 17) +
xlab(label = 'Year') +
ylab(label = 'Rate')
Here is a way of doing this without using reshape::melt. reshape::melt works, but you can get into a bind if you want to add other things to the graph, such as line segments. The code below uses the original organization of data. The key to modifying the legend is to make sure the arguments to scale_color_manual(...) and scale_shape_manual(...) are identical otherwise you will get two legends.
source("http://www.openintro.org/stat/data/arbuthnot.R")
library(ggplot2)
library(reshape2)
ptheme <- theme (
axis.text = element_text(size = 9), # tick labels
axis.title = element_text(size = 9), # axis labels
axis.ticks = element_line(colour = "grey70", size = 0.25),
panel.background = element_rect(fill = "white", colour = NA),
panel.border = element_rect(fill = NA, colour = "grey70", size = 0.25),
panel.grid.major = element_line(colour = "grey85", size = 0.25),
panel.grid.minor = element_line(colour = "grey93", size = 0.125),
panel.margin = unit(0 , "lines"),
legend.justification = c(1, 0),
legend.position = c(1, 0.1),
legend.text = element_text(size = 8),
plot.margin = unit(c(0.1, 0.1, 0.1, 0.01), "npc") # c(bottom, left, top, right), values can be negative
)
cols <- c( "c1" = "#ff00ff", "c2" = "#3399ff" )
shapes <- c("s1" = 16, "s2" = 17)
p1 <- ggplot(data = arbuthnot, aes(x = year))
p1 <- p1 + geom_point(aes( y = boys, color = "c1", shape = "s1"))
p1 <- p1 + geom_point(aes( y = girls, color = "c2", shape = "s2"))
p1 <- p1 + labs( x = "Year", y = "Rate" )
p1 <- p1 + scale_color_manual(name = "Sex",
breaks = c("c1", "c2"),
values = cols,
labels = c("boys", "girls"))
p1 <- p1 + scale_shape_manual(name = "Sex",
breaks = c("s1", "s2"),
values = shapes,
labels = c("boys", "girls"))
p1 <- p1 + ptheme
print(p1)
output results
Here is an answer based on the tidyverse package. Where one can use the pipe, %>%, to chain functions together. Creating the plot in one continues manner, omitting the need to create temporarily variables. More on the pipe can be found in this post What does %>% function mean in R?
As far as I know, legends in ggplot2 are only based on aesthetic variables. So to add a discrete legend one uses a category column, and change the aesthetics according to the category. In ggplot this is for example done by aes(color=category).
So to add two (or more) different variables of a data frame to the legends, one needs to transform the data frame such that we have a category column telling us which column (variable) is being plotted, and a second column that actually holds the value. The tidyr::gather function, that was also loaded by tidyverse, does exactly that.
Then one creates the legend by just specifying which aesthetics variables need to be different. In this example the code would look as follows:
source("http://www.openintro.org/stat/data/arbuthnot.R")
library(tidyverse)
arbuthnot %>%
rename(Year=year,Men=boys,Women=girls) %>%
gather(Men,Women,key = "Sex",value = "Rate") %>%
ggplot() +
geom_point(aes(x = Year, y=Rate, color=Sex, shape=Sex)) +
scale_color_manual(values = c("Men" = "#3399ff","Women"= "#ff00ff")) +
scale_shape_manual(values = c("Men" = 16, "Women" = 17))
Notice that tidyverse package also automatically loads in the ggplot2 package. An overview of the packages installed can be found on their website tidyverse.org.
In the code above I also used the function dplyr::rename (also loaded by tidyverse) to first rename the columns to the wanted labels. Since the legend automatically takes the labels equal to the category names.
There is a second way to renaming labels of legend, which involves specifying the labels explicitly in the scale_aesthetic_manual functions by the labels = argument. For examples see legends cookbook. But is not recommended since it gets messy quickly with more variables.