问题
This is a simple question, but I'm having difficulty understanding the format required by ggplot2:
I have the following data.table
in R,
print(dt)
ID category A B C totalABC
1: 10 group1 1 3 0 4
2: 11 group1 1 11 1 13
3: 12 group2 15 20 2 37
4: 13 group2 6 12 2 20
5: 14 group2 17 83 6 106
...
My goal is to create a proportional stacked bar graph as in this example: https://rpubs.com/escott8908/RGC_Ch3_Gar_Graphs
where the percentages of X/totalABC, where X is category_type
either A, B, or C. I would also like to perform this by category, e.g. the x-axis values should be group1
, group2
, etc.
As a concrete example, in the case of group1
, there are 4+13=17 total elements.
The percentages would be percent_A = 11.7%, percent_B = 82.3%, percent_C = 5.9%
The correct ggplot2 solution appears to be:
library(ggplot2)
pp = ggplot(dt, aes(x=category, y=percentage, fill=category_type)) +
geom_bar(position="dodge", stat="identity")
My confusion: how would I create a single percentage
column that corresponds to three categorical values?
If the above is incorrect, how would I format my data.table
to create the stacked barplot?
回答1:
Here's a solution:
require(data.table)
require(ggplot2)
require(dplyr)
melt(dt,measure.vars = c("A","B","C"),
variable.name = "groups",value.name = "nobs") %>%
ggplot(aes(x=category,y=nobs,fill=groups)) +
geom_bar(stat = "identity",position="fill")
回答2:
You can use the following code:
melt(data.frame( #melt to get each variable (i.e. A, B, C) in a single row
dt[,-1] %>% #get rid of ID
group_by(category) %>% #group by category
summarise_each(funs(sum))), #get the summation for each variable
id.vars=c("category", "totalABC")) %>%
ggplot(aes(x=category,y=value/totalABC,fill=variable))+ #define the x and y
geom_bar(stat = "identity",position="fill") + #make the stacked bars
scale_y_continuous(labels = scales::percent) #change y axis to % format
which will plot:
Data:
dt <- structure(list(ID = 10:14, category = structure(c(1L, 1L, 2L,
2L, 2L), .Label = c("group1", "group2"), class = "factor"), A = c(1L,
1L, 15L, 6L, 17L), B = c(3L, 11L, 20L, 12L, 83L), C = c(0L, 1L,
2L, 2L, 6L), totalABC = c(4L, 13L, 37L, 20L, 106L)), .Names = c("ID",
"category", "A", "B", "C", "totalABC"), row.names = c(NA, -5L
), class = c("data.table", "data.frame"), .internal.selfref = <pointer: 0x0000000000100788>)
What if you want to stick to the code that you had for plotting?
In that case, you can use this to get the percentage:
df <- melt(data.frame( #melt to get each variable (i.e. A, B, C) in a single row
dt[,-1] %>% #get rid of ID
group_by(category) %>% #group by category
summarise_each(funs(sum))), #get the summation for each variable
id.vars=c("category", "totalABC")) %>%
mutate(percentage = dtf$value*100/dtf$totalABC)
But need to modify your ggplot
to get the stacked bars correctly:
#variable is the column carrying category_type
#position dodge make the bars to be plotted next to each other
#while fill makes the stacked bars
ggplot(df, aes(x=category, y=percentage, fill=variable)) +
geom_bar(position="fill", stat="identity")
来源:https://stackoverflow.com/questions/44764464/r-ggplot2-stacked-barplot-by-percentage-with-several-categorical-variables