Order Categorical Data in a Stacked Bar Plot with Ggplot2

Order categorical data in a stacked bar plot with ggplot2

I see that you have an order column in your data frame which I gather is your order. Hence you can simply do.

p0 = qplot(factor(kclust), fill = reorder(hhDomMil, order), position = 'fill', 
       data = df1)

Here are the elements of this code that take care of your questions

1. How do I plot such a ordered plot? reorder
2. How do I set up x so that each bar is "on" one number? factor(kclust)
3. How do I seperate the bars?
4. How do I print all kclust numbers in x? factor(kclust)

I remember from a previous question of yours that the hhDomMil corresponded to different groups, and I suspect your ordering follows the grouping. In that case, you might want to use that information to choose a color palette that makes it simpler to follow the graph. Here is one way to do it.

mycols = c(brewer.pal(3, 'Oranges'), brewer.pal(3, 'Greens'), 
           brewer.pal(2, 'Blues'), brewer.pal(2, 'PuRd'))

p0 + scale_fill_manual(values = mycols)

ggplot2 order categorical stacked bars by proportions of y-axis

Use the group aesthetic to control the order of the stacked bar.

s <- "Sequence Abundance Category
CAGTG 0.8 A
CAGTG 0.2 B
CAGTG 0.6 C
CAGTG 0.3 D
CAGTG 0.1 E
GGGAC 0.1 A
GGGAC 0.1 B
GGGAC 0.3 C
GGGAC 0.6 D
GGGAC 0.1 E
CTTGA 0.1 A
CTTGA 0.7 B
CTTGA 0.1 C
CTTGA 0.1 D
CTTGA 0.8 E"  
d <- read.delim(textConnection(s), header=T, sep=" ")

# Add the "group" aesthetic to control the order of the stacked bars
g = ggplot(d,aes(x=Category, y=Abundance, fill=Sequence, group=Abundance)) + 
    geom_bar(position = "fill",stat = "identity")
g

Order the stacked barplot by proportion or percent in R

Add the proportion c by group like this, when generating p:

... %>%
  group_by(Name) %>% 
  mutate(prop_c = sum(value[variable=="c"], na.rm=T)/sum(value, na.rm=T))

Then plot, using reorder:

ggplot() +
  geom_col(data= p,aes(x = reorder(Name,prop_c, decreasing=T),y = value,fill = variable),position = "fill") + 
  geom_text(data = long_totals, aes(y = 100,x = Name,label = Total),size = 7,position = position_fill(vjust = 1.02)) +
  scale_y_continuous(labels = scales::percent_format())

sort columns with categorical variables by numerical varables in stacked barplot

The issue here is that all your percentages for a given category (name) in fact add up to 100%. So sorting by percentage, which is normally achieved via aes(x = reorder(name, percentage), y = percentage), won’t work here.

Instead, you probably want to order by the percentage of the data that has class = 1 (or class = -1). Doing this requires some trickery: Use ifelse to select the percentage for the rows where class == 1. For all other rows, select the value 0:

ggplot(df, aes(x = reorder(name, ifelse(class == 1, percentage, 0)), y = percentage, fill = factor(class))) +
  geom_bar(stat = "identity") +
  scale_fill_discrete(name = "Class") +
  xlab('Names')

You might want to execute just the reorder instruction to see what’s going on:

reorder(df$name, ifelse(df$class == 1, df$percentage, 0))
# [1] A A B B C C D D
# attr(,"scores")
#      A      B      C      D
# 44.055 48.720 47.020 46.630
# Levels: A D C B

As you can see, your names got reordered based on the mean percentage for each category (by default, reorder uses the mean; see its manual page for more details). But the “mean” we calculated was between each name’s percentage for class = 1, and the value 0 (for class ≠ 1).

Order Stacked Bar Graph by sum / total of all subgroups

The general (non ggplot-specific) answer is to use reorder() to reset the factor levels in a categorical column, based on some function of the other columns.

## Examine the default factor order
levels(samp.data$fullname)

## Reorder fullname based on the the sum of the other columns
samp.data$fullname <- reorder(samp.data$fullname, rowSums(samp.data[-1]))

## Examine the new factor order
levels(samp.data$fullname)
attributes(samp.data$fullname)

Then just replot, using code from the original question

md <- melt(samp.data, id=(c("fullname")))
temp.plot<-ggplot(data=md, aes(x=fullname, y=value, fill=variable) ) + 
               geom_bar()+ 
               theme(axis.text.x=theme_text(angle=90)) + 
               labs(title = "Score Distribtion")
## ggsave(temp.plot,filename="test.png")

how to change the stacked bar chart using ggplot2 (percentage, sort) in R

library(tidyverse)

data(tips, package='reshape2')

tips %>% 
  #Calculating percentage by sex outside ggplot2
  count(sex,day) %>% 
  group_by(sex) %>% 
  mutate(p = 100*n/sum(n)) %>% 
  ungroup() %>%
  #Removing Friday 
  filter(day != "Fri") %>% 
  #Ordering sex by Saturday percentage
  mutate(
    sex = fct_reorder2(
    .f = sex,
    .x = p,
    .y = day,
    .fun = function(x,y) max(x[y == "Sat"])
      )
    ) %>% 
  ggplot(aes(x = sex, y = p)) +
  geom_col(aes(fill=day))

How to include a bar for total in a stacked bar chart for categorical variable in R

You could achieve your desired result by adding a second geom_bar where you map a constant (e.g. the string Total) on x and setting the order of categoreis via scale_x_discrete:

library(ggplot2)

ggplot(df, aes(x=City, fill=Type), reorder(Type)) + 
  geom_bar(position="fill", alpha=0.75) +
  geom_bar(aes(x = "Total"), position="fill", alpha=0.75) +
  scale_fill_brewer(palette = "Paired") + 
  scale_x_discrete(limits = c("Total", unique(df$City))) +
  coord_flip()

Order Bars in ggplot2 bar graph

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. You can also specify the level order within the call to factor as above, and other ways are possible as well.

theTable$Position <- factor(theTable$Position, levels = c(...))

GGPLOT2: Stacked bar plot for two discrete variable columns

Your problem here is that you haven't fixed your tibble from Wide to Long.

FixedData <- sampleData %>%
  pivot_longer(cols = c("var_1", "var_2"), names_prefix = "var_", 
               names_to = "Variable Number", values_to = "ValueName")

Once you do this, the problem becomes much easier to solve. You only need to change a few things, most notably the y, fill, and position variables to make it work.

p2 <- ggplot(FixedData, aes(x = grp, y = ValueName, fill = `Variable Number`)) +
  geom_bar(stat="identity", position = "stack")+
  coord_flip()+ theme_bw()

p2

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