How to Create Geom_Boxplot with Large Amount of Continuous X-Variables

How to create geom_boxplot with large amount of continuous x-variables

Here is a way using the original data you posted on Google - which actually was much more helpful, IMO.

ggplot(df, aes(x=CH, y=value,group=CH))+
  geom_boxplot(notch=FALSE, outlier.shape=NA, fill="red", alpha=0.2)+
  scale_x_log10()

So, as @BenBolker said before he deleted his answer(??), you should leave the x-variable (CH) as numeric, and set group=CH in the call to aes(...).

With your real data there is another problem though. Your CH is more or less logarithmically spaced, so there are about as many points < 1 as there are between 1 - 10, etc. ggplot wants to make the boxes all the same size, so with a linear x-axis the box width is smaller than the line width, and you don't see the boxes at all. Changing the x-axis to a logarithmic scale fixes that, more or less.

How to plot a boxplot with correctly spaced continuous x-axis values and a grouping variable in ggplot2?

In your data, you have a discrete variable, i.e., class. However, you need the data to be grouped by class and x_int. So, we can specify this grouping by using interaction in the group argument for x_int and class. Then, fill with class.

library(tidyverse)

df %>% 
  ggplot(aes(x=x_int, y=y, group = interaction(x_int, class), fill = class)) +
  geom_boxplot()

Output

How to create boxplot with large amount of continuous x-variables and continuous y-variables with R (not ggplot)

You can plot by boxplot() function. From this tutorial :

https://www.r-bloggers.com/box-plot-with-r-tutorial/

r-blogger is good for your start learning R. Good luck.

How to plot a boxplot with correctly spaced continuous x-axis values in ggplot2

df <- data.frame(y=abs(rnorm(8)),
                 x=rep(c(0,100,200,500),times=2)) 

ggplot(df, aes(x, y, group=x)) + 
  geom_boxplot()

This solution relies on two changes. First, to plot boxes positioned on a continuous x axis, we need to provide numeric rather than factor x values. However, this does not work by itself, because without x values being grouped by factor levels, ggplot no longer knows how to group the data into different boxes. So, we also need to provide an additional grouping variable.

Fill and dodge boxplots by group on a continuous x axis

From ?aes_group_order:

By default, the group is set to the interaction of all discrete variables in the
plot.

In your data, you only have one discrete variable, "fill". However, we wish the data to be grouped by both "fill" and "x". Thus, we need to specify the desired grouping using the group argument. And yes, you were correct, interaction is the way to go.

First, a slightly smaller data set (easier to link data to output):

d <- data.frame(x = rep(c(1, 2, 4), each = 8),
                grp = rep(c("a", "b"), each = 4),
                y = sample(24))

Then the plot, where we group data by the different combinations of "x" and "grp" (interaction(x, grp)), and fill the boxes by "grp":

ggplot(d, aes(x = x, y = y, group = interaction(x, grp), fill = grp)) +
  geom_boxplot()

R : Plot a boxplot with a continuous x axis : choose an interval for each box

Consider adding the following discrete variable to your data instead of applying cut_width() in your ggplot commands:

df$Speed_Cat = cut_width(df$Speed, 20)

Then your plot will be constructed via:

ggplot(df, aes(x = Speed_Cat, y = Concentrations)) + 
geom_boxplot() + 
scale_x_discrete(labels=seq(0,100,20))

Just know what you want your cuts to represent! Buckets become [-10,10], (10,30], ...,
but you can always adjust these when you create the variable in your data.

How to Create Boxplots with a Continuous x axis in R?

If I understood correctly:

I turn the rownames into the first column

library(data.table)
setDT(df, keep.rownames = TRUE)[]

Then melt it with reshape2

library(reshape2)
df=melt(df,id.vars=c("rn","age"))

And plot it using ggplot2

library(ggplot2)
ggplot(df,aes(x=age,y=value,group=rn))+geom_boxplot()

ggplot2: arranging multiple boxplots as a time series

Is this what you want?

Code:

p <- ggplot(data = dtm, aes(x = asDate, y = mortes, group=interaction(date, trmt)))
p +  geom_boxplot(aes(fill = factor(dtm$trmt)))

The key is to group by interaction(date, trmt) so that you get all of the boxes, and not cast asDate to a factor, so that ggplot treats it as a date. If you want to add anything more to the x axis, be sure to do it with + scale_x_date().

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