R中多列的箱线图

Question

all,

Pretty new to R so I'm having some trouble trying to figure this out. This is a sample of the data I'm working with...

ID	Cross_specific	Cross_pop	seed_count
1	interspecific	NA	#
2	intraspecific	intrapopulation	#
3	intraspecific	interpopulation	#

What I want to do is create a boxplot that separates the seed count by intraspecific/intrapopulation, intraspecific/interpopulation, and interspecific - so three separate boxplots. I'm pretty sure I'll have to get the boxplot to read across two different columns, which I think I've figured out.

The problem is it separates the boxplot into five categories: "interspecific" and "intraspecific" from the "Cross_specific" column as well as "NA", "intrapopulation", and "interpopulation" from the "Cross_pop_ column.

Is there a way to take the "intra" and "inter" categories (leaving the "NA" out) from the "Cross_pop" column and only the "interspecific" category from the "Cross_specific" column?

This is the line I used

boxplot(seed_count_avg~cross_pop+cross_specific="interspecific",data=data,main="Seed Count",xlab="Cross Type",ylab="Seed Count")

Unfortunately, I got an error ( Error: unexpected '=' in "boxplot(seed_count_avg~cross_pop+cross_specific=" , in case you're wondering).

I also used this code

boxplot(seed_count_avg~cross_pop+cross_specific,data=data,main="Seed Count",xlab="Cross Type",ylab="Seed Count")

Which created boxplots, but with empty spaces.

Thank you in advance!

Answer 1

This might be close to what you are trying to do. First we need reproducible data:

set.seed(42)
Cross_specific <- sample(c("interspecific", "intraspecific"), 100, replace=TRUE)
Cross_pop <- sample(c("intrapopulation", "interpopulation"), 100, replace=TRUE)
Cross_pop[Cross_specific=="interspecific"] <- ""
seed_count <- sample(1000, 100)
data <- data.frame(Cross_specific, Cross_pop, seed_count)

Whenever Cross_specific=="interspecific" we set the value of Cross_pop to "", not NA because this is not missing data. Now the boxplot:

boxplot(seed_count~Cross_specific+Cross_pop, data=data2, main="Seed Count", 
     xlab="Cross Type", ylab="Seed Count", drop=TRUE, cex.axis=.9)

Which produces the following plot: