I am trying to make a bar graph where the largest bar would be nearest to the y axis and the shortest bar would be furthest. So this is kind of like the Table I have
Name Position 1 James Goalkeeper 2 Frank Goalkeeper 3 Jean Defense 4 Steve Defense 5 John Defense 6 Tim Striker
So I am trying to build a bar graph that would show the number of players according to position
p <- ggplot(theTable, aes(x = Position)) + geom_bar(binwidth = 1)
but the graph shows the goalkeeper bar first then the defense, and finally the striker one. I would want the graph to be ordered so that the defense bar is closest to the y axis, the goalkeeper one, and finally the striker one. Thanksrggplot2r-faq
You just need to specify the
Position column to be an ordered factor where the levels are ordered by their counts:
theTable <- transform( theTable, Position = ordered(Position, levels = names( sort(-table(Position)))))
(Note that the
table(Position) produces a frequency-count of the
ggplot function will show the bars in decreasing order of count.
I don't know if there's an option in
geom_bar to do this without having to explicitly create an ordered factor.
The key with ordering is to set the levels of the factor in the order you want. An ordered factor is not required; the extra information in an ordered factor isn't necessary and if these data are being used in any statistical model, the wrong parametrisation might result — polynomial contrasts aren't right for nominal data such as this.
## set the levels in order we want theTable <- within(theTable, Position <- factor(Position, levels=names(sort(table(Position), decreasing=TRUE)))) ## plot ggplot(theTable,aes(x=Position))+geom_bar(binwidth=1)
In the most general sense, we simply need to set the factor levels to be in the desired order. If left unspecified, the levels of a factor will be sorted alphabetically. However, there are multiple ways to change the order to a specific sequence depending on the situation. For instance, we could do:
levels(theTable$Position) <- c(...)
and simply list the levels in the desired order on the right hand side. You can also specify the level order within the call to factor as above:
theTable$Position <- factor(theTable$Position, levels = c(...))
reorder is a powerful and effective solution for this:
ggplot(theTable, aes(x=reorder(Position,Position, function(x)-length(x)))) + geom_bar()
scale_x_discrete (limits = ...) to specify the order of bars.
positions <- c("Goalkeeper", "Defense", "Striker") p <- ggplot(theTable, aes(x = Position)) + scale_x_discrete(limits = positions)
I think the already provided solutions are overly verbose. A more concise way to do a frequency sorted barplot with ggplot is
ggplot(theTable, aes(x=reorder(Position, -table(Position)[Position]))) + geom_bar()
It's similar to what Alex Brown suggested, but a bit shorter and works without an anynymous function definition.
I think my old solution was good at the time, but nowadays I'd rather use
forcats::fct_infreq which is sorting factor levels by frequency:
require(forcats) ggplot(theTable, aes(fct_infreq(Position))) + geom_bar()
A simple dplyr based reordering of factors can solve this problem:
library(dplyr) #reorder the table and reset the factor to that ordering theTable %>% group_by(Position) %>% # calculate the counts summarize(counts = n()) %>% arrange(-counts) %>% # sort by counts mutate(Position = factor(Position, Position)) %>% # reset factor ggplot(aes(x=Position, y=counts)) + # plot geom_bar(stat="identity") # plot histogram
I agree with zach that counting within dplyr is the best solution. I've found this to be the shortest version:
dplyr::count(theTable, Position) %>% arrange(-n) %>% mutate(Position = factor(Position, Position)) %>% ggplot(aes(x=Position, y=n)) + geom_bar(stat="identity")
This will also be significantly faster than reordering the factor levels beforehand since the count is done in dplyr not in ggplot or using
reorder() in Alex Brown's answer, we could also use
forcats::fct_reorder(). It will basically sort the factors specified in the 1st arg, according to the values in the 2nd arg after applying a specified function (default = median, which is what we use here as just have one value per factor level).
It is a shame that in the OP's question, the order required is also alphabetical as that is the default sort order when you create factors, so will hide what this function is actually doing. To make it more clear, I'll replace "Goalkeeper" with "Zoalkeeper".
library(tidyverse) library(forcats) theTable <- data.frame( Name = c('James', 'Frank', 'Jean', 'Steve', 'John', 'Tim'), Position = c('Zoalkeeper', 'Zoalkeeper', 'Defense', 'Defense', 'Defense', 'Striker')) theTable %>% count(Position) %>% mutate(Position = fct_reorder(Position, n, .desc = TRUE)) %>% ggplot(aes(x = Position, y = n)) + geom_bar(stat = 'identity')
In addition to forcats::fct_infreq, mentioned by @HolgerBrandl, there is forcats::fct_rev, which reverses the factor order.
theTable <- data.frame( Position= c("Zoalkeeper", "Zoalkeeper", "Defense", "Defense", "Defense", "Striker"), Name=c("James", "Frank","Jean", "Steve","John", "Tim")) p1 <- ggplot(theTable, aes(x = Position)) + geom_bar() p2 <- ggplot(theTable, aes(x = fct_infreq(Position))) + geom_bar() p3 <- ggplot(theTable, aes(x = fct_rev(fct_infreq(Position)))) + geom_bar() gridExtra::grid.arrange(p1, p2, p3, nrow=3)
If the chart columns come from a numeric variable as in the dataframe below, you can use a simpler solution:
ggplot(df, aes(x = reorder(Colors, -Qty, sum), y = Qty)) + geom_bar(stat = "identity")
The minus sign before the sort variable (-Qty) controls the sort direction (ascending/descending)
Here's some data for testing:
df <- data.frame(Colors = c("Green","Yellow","Blue","Red","Yellow","Blue"), Qty = c(7,4,5,1,3,6) ) **Sample data:** Colors Qty 1 Green 7 2 Yellow 4 3 Blue 5 4 Red 1 5 Yellow 3 6 Blue 6
When I found this thread, that was the answer I was looking for. Hope it's useful for others.