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. Thanks

rggplot2r-faq answered 7 years ago Prasad Chalasani #1

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 `Position`

column.)

Then your `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.

answered 7 years ago Gavin Simpson #2

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. There are multiple ways of doing this 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(...))
```

answered 6 years ago Alex Brown #3

@GavinSimpson: `reorder`

is a powerful and effective solution for this:

```
ggplot(theTable,
aes(x=reorder(Position,Position,
function(x)-length(x)))) +
geom_bar()
```

answered 4 years ago QIBIN LI #4

Using `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)
```

answered 4 years ago Holger Brandl #5

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.

**Update**

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()
```

answered 2 years ago zach #6

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
```

answered 2 years ago Alexandru Papiu #7

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 `table`

.

answered 2 years ago user2739472 #8

Like `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')
```

answered 4 months ago Robert McDonald #9

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)
```