I have a data frame like below:
id month type count
___ _______ ______ ______
1 1 1 10
1 1 2 09
1
This problem can be solved much more cleanly with facet_grid
:
library(tidyverse)
read_tsv("tmp.tsv", col_types = "ccci") %>%
ggplot(aes(x=month, y=count, fill=type)) + geom_col() + facet_grid(.~id)
Note that you have to specify the first three columns as "character" in the col_types
argument otherwise it won't look so good. It would be even better to replace the numeric codes with something meaningful (e.g. make the months into ordered factors "January", "February" instead of 1, 2; something similar for type and id).
Suppose you want to plot id
as x-axis, side by side for the month, and stack different types, you can split data frame by month, and add a bar layer for each month, shift the x
by an amount for the second month bars so they can be separated:
barwidth = 0.35
month_one <- filter(df, month == 1) %>%
group_by(id) %>% arrange(-type) %>%
mutate(pos = cumsum(count) - count / 2) # calculate the position of the label
month_two <- filter(df, month == 2) %>%
group_by(id) %>% arrange(-type) %>%
mutate(pos = cumsum(count) - count / 2)
ggplot() +
geom_bar(data = month_one,
mapping = aes(x = id, y = count, fill = as.factor(type)),
stat="identity",
position='stack',
width = barwidth) +
geom_text(data = month_one,
aes(x = id, y = pos, label = count )) +
geom_bar(data = filter(df, month==2),
mapping = aes(x = id + barwidth + 0.01, y = count, fill = as.factor(type)),
stat="identity",
position='stack' ,
width = barwidth) +
geom_text(data = month_two,
aes(x = id + barwidth + 0.01, y = pos, label = count )) +
labs(fill = "type")
gives:
dput(df)
structure(list(id = c(1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L,
2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L), month = c(1L, 1L, 1L, 2L, 2L,
2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L), type = c(1L,
2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L,
3L), count = c(10L, 9L, 26L, 60L, 90L, 80L, 10L, 9L, 26L, 60L,
90L, 80L, 10L, 9L, 26L, 60L, 90L, 80L)), .Names = c("id", "month",
"type", "count"), class = "data.frame", row.names = c(NA, -18L
))