I would like to change specific colours (oder than rainbow default) to each column "Sector" in the code below
I've read that geom_area doesn't allow changes in colour? if so is there another way to plot this graph without using ggplot2 package?
Sector <- rep(c("S01","S02","S03","S04","S05","S06","S07"),times=7)
Year <- as.numeric(rep(c("1950","1960","1970","1980","1990","2000","2010"),each=7))
Value <- runif(49, 10, 100)
data <- data.frame(Sector,Year,Value)
data
ggplot(data, aes(x=Year, y=Value, fill=Sector)) +
geom_area(stat="identity")
There are a lot of ways to change the color scale in ggplot.
Here's a way where you can specify exactly which colors you want:
Sector <- rep(c("S01","S02","S03","S04","S05","S06","S07"),times=7)
Year <- as.numeric(rep(c("1950","1960","1970","1980","1990","2000","2010"),each=7))
Value <- runif(49, 10, 100)
data <- data.frame(Sector,Year,Value)
data
ggplot(data, aes(x=Year, y=Value, fill=Sector)) + geom_area(stat="identity") +
scale_fill_manual(values = c("black","blue","gray","orange","tan","purple","darkgray"))
Related
I would like to have a separate scale bar for each variable.
I have measurements taken throughout the water column for which the means have been calculated into 50cm bins. I would like to use geom_tile to show the variation of each variable in each bin throughout the water column, so the plot has the variable (categorical) on the x-axis, the depth on the y-axis and a different colour scale for each variable representing the value. I am able to do this for one variable using
ggplot(data, aes(x=var, y=depth, fill=value, color=value)) +
geom_tile(size=0.6)+ theme_classic()+scale_y_continuous(limits = c(0,11), expand = c(0, 0))
But if I put all variables onto one plot, the legend is scaled to the min and max of all values so the variation between bins is lost.
To provide a reproducible example, I have used the mtcars, and I have included alpha = which, of course, doesn't help much because the scale of each variable is so different
data("mtcars")
# STACKS DATA
library(reshape2)
dat2b <- melt(mtcars, id.vars=1:2)
dat2b
ggplot(dat2b) +
geom_tile(aes(x=variable , y=cyl, fill=variable, alpha = value))
Which produces
Is there a way I can add a scale bar for each variable on the plot?
This question is similar to others (e.g. here and here), but they do not use a categorical variable on the x-axis, so I have not been able to modify them to produce the desired plot.
Here is a mock-up of the plot I have in mind using just four of the variables, except I would have all legends horizontal at the bottom of the plot using theme(legend.position="bottom")
Hope this helps:
The function myfun was originally posted by Duck here: R ggplot heatmap with multiple rows having separate legends on the same graph
library(purrr)
library(ggplot2)
library(patchwork)
data("mtcars")
# STACKS DATA
library(reshape2)
dat2b <- melt(mtcars, id.vars=1:2)
dat2b
#Split into list
List <- split(dat2b,dat2b$variable)
#Function for plots
myfun <- function(x)
{
G <- ggplot(x, aes(x=variable, y=cyl, fill = value)) +
geom_tile() +
theme(legend.direction = "vertical", legend.position="bottom")
return(G)
}
#Apply
List2 <- lapply(List,myfun)
#Plot
reduce(List2, `+`)+plot_annotation(title = 'My plot')
patchwork::wrap_plots(List2)
We are presenting outcome data using boxplots and group these for different approaches using facet_grid with ggplot2 and geom_boxplot.
We would like to add more space between the boxplots and the frame of the facet_grid as shown in the graphic below.
The code we used included ggplot_build and gglot_table.
Which parameter of ggplot_build needs to be set to get more space in the panels?
require(ggplot2)
require(grid)
dat <- rbind(data.frame(approach=1,product=1,value=seq(1,20,0.5)),
data.frame(approach=1,product=2,value=seq(5,15,0.3)),
data.frame(approach=1,product=3,value=seq(5,17,0.2)),
data.frame(approach=2,product=1,value=seq(1,13,0.3)),
data.frame(approach=2,product=2,value=seq(3,18,0.5)),
data.frame(approach=2,product=3,value=seq(4,25,0.7)),
data.frame(approach=3,product=1,value=seq(1,15,0.6)),
data.frame(approach=3,product=2,value=seq(3,16,0.5)),
data.frame(approach=3,product=3,value=seq(1,10,0.1)))
dat$product<-as.factor(dat$product)
gg1<-ggplot(dat, aes(x =product, y = value)) +
geom_boxplot() +
facet_grid(cols=vars(approach))
gt = ggplot_gtable(ggplot_build(gg1))
grid.draw(gt)
ggplot(dat, aes(x =product, y = value)) +
geom_boxplot() +
coord_cartesian(xlim = c(1.2, 2, 2.8)) +
facet_grid(cols=vars(approach))
I have a data.frame which I'd like to scatter plot using ggplot.
The data have 3 factors whose levels I'd like to show in the legend, although the color of the points will only be according to one of these factors (df$group below).
Here's what I have so far:
set.seed(1)
df <- data.frame(x=rnorm(100),y=rnorm(100),
group=LETTERS[sample(5,100,replace=T)],
type=letters[sample(3,100,replace=T)],
background=sample(4,100,replace=T),stringsAsFactors=F)
df$group <- factor(df$group,LETTERS[1:5])
df$type <- factor(df$type,;etters[1:3])
df$background <- factor(df$background,c(1:4))
I manually specify colors:
require(RColorBrewer)
require(scales)
all.colors <- hcl(h=seq(0,(12-1)/(12),length=12)*360,c=100,l=65,fixup=TRUE)
group.colors <- all.colors[1:5]
type.colors <- all.colors[6:8]
background.colors <- all.colors[9:12]
This is what I have for showing the 3 factors in the legend (df$group and df$type):
require(ggplot2)
ggplot(df,aes(x=x,y=y,colour=group,fill=type,alpha=background))+geom_point(cex=2,shape=1,stroke=1)+
theme_bw()+theme(strip.background=element_blank())+scale_color_manual(drop=FALSE,values=group.colors,name="group")+
guides(fill=guide_legend(override.aes=list(colour=type.colors,pch=0)))
So my question is how to get background.colors appear in the legend under "background" rather than the gray scale colors chosen by default that currently appear there.
ggplot(df,aes(x=x, y=y, colour=group, fill=type, alpha=background))+
geom_point(cex=2, shape=1, stroke=1) +
theme_bw() +
theme(strip.background=element_blank()) +
scale_color_manual(drop=FALSE, values=group.colors, name="group") +
guides(fill=guide_legend(override.aes=list(colour=type.colors,pch=0)),
alpha=guide_legend(override.aes=list(colour=background.colors,pch=0)))
I want to make a line chart in plotly so that it does not have the same color on its whole length. The color is given continuous scale. It is easy in ggplot2 but when I translate it to plotly using ggplotly function the variable determining color behaves like categorical variable.
require(dplyr)
require(ggplot2)
require(plotly)
df <- data_frame(
x = 1:15,
group = rep(c(1,2,1), each = 5),
y = 1:15 + group
)
gg <- ggplot(df) +
aes(x, y, col = group) +
geom_line()
gg # ggplot2
ggplotly(gg) # plotly
ggplot2 (desired):
plotly:
I found one work-around that, on the other hand, behaves oddly in ggplot2.
df2 <- df %>%
tidyr::crossing(col = unique(.$group)) %>%
mutate(y = ifelse(group == col, y, NA)) %>%
arrange(col)
gg2 <- ggplot(df2) +
aes(x, y, col = col) +
geom_line()
gg2
ggplotly(gg2)
I also did not find a way how to do this in plotly directly. Maybe there is no solution at all. Any ideas?
It looks like ggplotly is treating group as a factor, even though it's numeric. You could use geom_segment as a workaround to ensure that segments are drawn between each pair of points:
gg2 = ggplot(df, aes(x,y,colour=group)) +
geom_segment(aes(x=x, xend=lead(x), y=y, yend=lead(y)))
gg2
ggplotly(gg2)
Regarding #rawr's (now deleted) comment, I think it would make sense to have group be continuous if you want to map line color to a continuous variable. Below is an extension of the OP's example to a group column that's continuous, rather than having just two discrete categories.
set.seed(49)
df3 <- data_frame(
x = 1:50,
group = cumsum(rnorm(50)),
y = 1:50 + group
)
Plot gg3 below uses geom_line, but I've also included geom_point. You can see that ggplotly is plotting the points. However, there are no lines, because no two points have the same value of group. If we hadn't included geom_point, the graph would be blank.
gg3 <- ggplot(df3, aes(x, y, colour = group)) +
geom_point() + geom_line() +
scale_colour_gradient2(low="red",mid="yellow",high="blue")
gg3
ggplotly(gg3)
Switching to geom_segment gives us the lines we want with ggplotly. Note, however, that line color will be based on the value of group at the first point in the segment (whether using geom_line or geom_segment), so there might be cases where you want to interpolate the value of group between each (x,y) pair in order to get smoother color gradations:
gg4 <- ggplot(df3, aes(x, y, colour = group)) +
geom_segment(aes(x=x, xend=lead(x), y=y, yend=lead(y))) +
scale_colour_gradient2(low="red",mid="yellow",high="blue")
ggplotly(gg4)
I have a simplified dataframe
library(ggplot2)
df <- data.frame(wins=c(1,1,3,1,1,2,1,2,1,1,1,3))
ggplot(df,aes(x=wins))+geom_histogram(binwidth=0.5,fill="red")
I would like to get the final value in the sequence,3, shown with either a different fill or alpha. One way to identify its value is
tail(df,1)$wins
In addition, I would like to have the histogram bars shifted so that they are centered over the number. I tried unsuccesfully subtracting from the wins value
You can do this with a single geom_histogram() by using aes(fill = cond).
To choose different colours, use one of the scale_fill_*() functions, e.g. scale_fill_manual(values = c("red", "blue").
library(ggplot2)
df <- data.frame(wins=c(1,1,3,1,1,2,11,2,11,15,1,1,3))
df$cond <- df$wins == tail(df,1)$wins
ggplot(df, aes(x=wins, fill = cond)) +
geom_histogram() +
scale_x_continuous(breaks=df$wins+0.25, labels=df$wins) +
scale_fill_manual(values = c("red", "blue"))
1) To draw bins in different colors you can use geom_histogram() for subsets.
2) To center bars along numbers on the x axis you can invoke scale_x_continuous(breaks=..., labels=...)
So, this code
library(ggplot2)
df <- data.frame(wins=c(1,1,3,1,1,2,11,2,11,15,1,1,3))
cond <- df$wins == tail(df,1)$wins
ggplot(df, aes(x=wins)) +
geom_histogram(data=subset(df,cond==FALSE), binwidth=0.5, fill="red") +
geom_histogram(data=subset(df,cond==TRUE), binwidth=0.5, fill="blue") +
scale_x_continuous(breaks=df$wins+0.25, labels=df$wins)
produces the plot: