Data:
df <- data.frame(
type = c("T", "F", "P", "T", "F", "P", "T", "F", "P", "T", "F", "P"),
size = c("50%", "50%", "50%", "100%", "100%", "100%", "150%", "150%", "150%", "200%", "200%", "200%"),
amount = c(48.4, 48.1, 46.8, 25.9, 26, 24.9, 21.1, 21.4, 20.1, 20.8, 21.5, 16.5)
)
I need to plot a bargraph of the above data using ggplot (x-axis -> type
, y-axis -> amount
, group by size
). When I used the following code, I am not getting the variable type
and as well as size
in the order shown in the data. Please see the figure. I have used the following code for that.
ggplot(df, aes(type, amount , fill=type, group=type, shape=type, facets=size)) +
geom_col(width=0.5, position = position_dodge(width=0.6)) +
facet_grid(.~size) +
theme_bw() +
scale_fill_manual(values = c("darkblue","steelblue1","steelblue4"),
labels = c("T", "F", "P"))
.
For fixing the order issue, I have used a factor method for the variable "type" using the following. Please see the figure also.
temp$new = factor(temp$type, levels=c("T","F","P"), labels=c("T","F","P"))
However, now I don't know how to fix the order for the variable size
. It should be 50%, 100%. 150%, and 200%.
There are a couple of good solutions here.
Similar to the answer from Harpal, but within the facet, so doesn't require any change to underlying data or pre-plotting manipulation:
# Change this code:
facet_grid(.~size) +
# To this code:
facet_grid(~factor(size, levels=c('50%','100%','150%','200%')))
This is flexible, and can be implemented for any variable as you change what element is faceted, no underlying change in the data required.
Here's a solution that keeps things within a dplyr pipe chain. You sort the data in advance, and then using mutate_at to convert to a factor. I've modified the data slightly to show how this solution can be applied generally, given data that can be sensibly sorted:
# the data
temp <- data.frame(type=rep(c("T", "F", "P"), 4),
size=rep(c("50%", "100%", "200%", "150%"), each=3), # cannot sort this
size_num = rep(c(.5, 1, 2, 1.5), each=3), # can sort this
amount=c(48.4, 48.1, 46.8,
25.9, 26.0, 24.9,
20.8, 21.5, 16.5,
21.1, 21.4, 20.1))
temp %>%
arrange(size_num) %>% # sort
mutate_at(vars(size), funs(factor(., levels=unique(.)))) %>% # convert to factor
ggplot() +
geom_bar(aes(x = type, y=amount, fill=type),
position="dodge", stat="identity") +
facet_grid(~ size)
You can apply this solution to arrange the bars within facets, too, though you can only choose a single, preferred order:
temp %>%
arrange(size_num) %>%
mutate_at(vars(size), funs(factor(., levels=unique(.)))) %>%
arrange(desc(amount)) %>%
mutate_at(vars(type), funs(factor(., levels=unique(.)))) %>%
ggplot() +
geom_bar(aes(x = type, y=amount, fill=type),
position="dodge", stat="identity") +
facet_grid(~ size)
ggplot() +
geom_bar(aes(x = type, y=amount, fill=type),
position="dodge", stat="identity") +
facet_grid(~ size)
Source: Stackoverflow.com