Ggplot2: Sorting a Plot

ggplot2: sorting a plot

Here are a couple of ways.

The first will order things based on the order seen in the data frame:

x$variable <- factor(x$variable, levels=unique(as.character(x$variable)) )

The second orders the levels based on another variable (value in this case):

x <- transform(x, variable=reorder(variable, -value) ) 

Sort a bar plot based on two conditions in ggplot

Couple of issues in the code -

• name=factor(Groups, levels = Values) gives all NA's. levels should be the value present in the data.
• We don't need $ in ggplot code. Also df$Sites does not have the factor levels that we need. The factor levels are added in the piped data and not in the original data.

library(dplyr)
library(ggplot2)

df %>% 
    arrange(Groups, Values) %>%
    mutate(Sites=factor(Sites, levels = Sites), 
           Groups = factor(Groups)) %>% 
    ggplot(aes(x = Sites, y = Values, fill = Groups)) +
    geom_bar(stat = "identity")+
    scale_fill_manual(values = c ('royalblue1', 'grey2', 'yellow1'))+
    ylab("Values")+
    xlab("")+
    theme(axis.text.x = element_text(angle = 90, hjust = 1))

How to plot a bar plot by ggplot2 and sort bars in non-alphabetical order

We could use fct_relevel from forcats package (it is in tidyverse).

1. Bring your rownames to a column gene with rownames_to_column function from tibble package (it is in tidyverse)

2. Use fct_relevel to set the order as you wish

3. Then use ggplot2 (I used geom_col())

library(tidyverse)

mydata %>% 
  rownames_to_column("gene") %>% 
  pivot_longer(
    cols = -gene
  ) %>% 
  mutate(gene = fct_relevel(gene, 
                            "SHO", "DRG", "ALA", "XPA")) %>% 
  ggplot(aes(x=gene, y=value))+
  geom_col(color="green" , fill="yellowgreen", position="dodge" , width = 0.5)+
  xlab("Genes")+
  ylab("Expression") +
  theme(axis.text.x = element_text(size = 10, angle = 45, hjust = 1), 
        plot.margin = margin(0.5,0.5,0.5,2, "cm"))

Sorting ggplot2 geom_posterior plot

You can reorder by mean:

reorder(name, value, mean)

specifying the vector whose levels will be reordered, a vector whose subset of values determines the order, and a function to apply to subsets (in this case, mean).

library(tidyverse)
library(ggdistribute)

set.seed(123)

value1 <- rnorm(n=100, mean=1, sd=1) %>% as.data.frame()
value2 <- rnorm(n=100, mean=3, sd=1) %>% as.data.frame()
value3 <- rnorm(n=100, mean=1, sd=2) %>% as.data.frame()

value1$name <- "A1"
value2$name <- "A2"
value3$name <- "A3"

value1 <- rbind(value1,value2,value3) 
colnames(value1) <- c("value","name")

ggplot(value1, aes(x = value, y = reorder(name, value, mean)))+
  geom_posterior() +
  xlab("value")  + theme_bw()

Plot

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(...))

Plotting in sorted order using Plotnine

You can do it in two ways

1. Make sure the variable mapped to the x-axis is a categorical and the categories are ordered correctly. Below I use the fact that pd.unique returns values in order of appearance.

corr.sort_values(by='value').reset_index(drop = True)
corr['var2'] = pd.Categorical(corr.var2, categories=pd.unique(corr.var2))
...

2. Plotnine has an internal function reorder (introduced in v0.7.0) which you can use inside an aes() call to change the order of values of one variable based on the values of another variable. See the documentation for reorder at the bottom of the page.

# no need to sort values
p = ggplot(data = corr, mapping = aes(x='reorder(var2, value)', y='value')) +\
...

I have a sorted data frame, but when I plot it the order is gone. [in R]

As mentioned, you have to set factors:

df <- data.frame(word=c("play","win","offer","http","right","internet"),
                 frequency=c(321,355,123,899,564,433),
                 type=c("nonspam","nonspam","spam","spam","spam","spam"))  

your_order <- order(df$frequency)
df$word <- factor(df$word, levels = df$word[your_order])

ggplot(df, aes(x=frequency, y=word)) +
  geom_segment(aes(yend=word), xend=0, color='grey50') +
  geom_point(size=3, aes(color=type)) + 
  scale_color_brewer(palette='Set1', limits=c('Spam', 'non-Spam'), guide=F) +
  theme_bw() +
  theme(panel.grid.major.y = element_blank()) +
  facet_grid(type ~ ., scales='free_y', space='free_y')

With these commands your plot should appear as expected.

ggplot2 sorting X Axis by start date of timeframes

Try this:

library(dplyr)
library(ggplot2)
#Plot
data %>%
  mutate(start=as.Date(start,'%d.%m.%Y'),
         end=as.Date(end,'%d.%m.%Y'),
         name=factor(name,levels = unique(name),ordered = T)) %>%
  mutate(start=as.character(start),
         end=as.character(end)) %>%
  ggplot(aes(x=start, xend=end, y=name, yend=name, color=Team)) +
  geom_segment(size=4) +
  labs(title='Overview', size= 6, x='Tenure', y='Judge') +
  scale_colour_manual(values = c('red', 'black', 'green' , 'grey')) +
  theme(axis.title = element_text(),text = element_text(size=12),
        axis.text.x = element_text(angle=90, hjust=1)) +
  theme(axis.text.y = element_text(lineheight = 2, size = 6))

Output:

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