I have results from a survey. I am trying to create a graphic displaying the relationship of two variables: "Q1" and "Q9.1". "Q1" is the independent and "Q9.1" is the depende开发者_如何学编程nt. Both variables have responses from like scale questions: -2,-1,0,1,2. A typical plot places the answers on top of each other - not very interesting or informative. I was thinking that hexbin would be the way to go. The data is in lpp. I have not been able to use "Q1" and "Q9.1" for x and y. However:
> is.numeric("Q1")
[1] FALSE
q1.num <- as.numeric("Q1")
Warning message:
NAs introduced by coercion
The values for Q1 are (hundreds of instances of): -2,-1,0,1,2
How can I make a hexbin graph with this data? Is there another graph I should consider?
Error messages so far:
Warning messages:
1: In xy.coords(x, y, xl, yl) : NAs introduced by coercion
2: In xy.coords(x, y, xl, yl) : NAs introduced by coercion
3: In min(x) : no non-missing arguments to min; returning Inf
4: In max(x) : no non-missing arguments to max; returning -Inf
5: In min(x) : no non-missing arguments to min; returning Inf
6: In max(x) : no non-missing arguments to max; returning -Inf
How about taking a slightly different approach? How about thinking of your responses as factors rather than numbers? You could use something like this, then, to get a potentially useful representation of your data:
# Simulate data for testing purposes q1 = sample(c(-2,-1,0,1,2),100,replace=TRUE) q9 = sample(c(-2,-1,0,1,2),100,replace=TRUE) dat = data.frame(q1=factor(q1),q9=factor(q9)) library(ggplot2) # generate stacked barchart ggplot(dat,aes(q1,fill=q9)) + geom_bar()
You may want to switch q1 and q9 above, depending on the view of the data that you want.
Perhaps ggplot2's stat_binhex could sort that one for you?
Also, I find scale_alpha useful for dealing with overplotting.
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