Unable to plot kernel density in MASS package - In min(x) : no non-missing arguments to min; returning Inf

Question

When trying to plot my data I get these error messages:

1: In min(x) : no non-missing arguments to min; returning Inf
2: In max(x) : no non-missing arguments to max; returning -Inf

This reproducible code works:

# some dummy data
library(mvtnorm)
dat <- rmvnorm(10000, mean=c(x=4,y=4), sigma=matrix(c(1,0.5,0.5,1), ncol=2))
dat <- as.data.frame(dat)

# 2d density plot
library(MASS)
kdexy <- kde2d(dat$x,dat$y, n=50)
image(kdexy, col=grey(seq(1,0.2,length=10)))

But using my real data doesn't:

kdexy <- kde2d(temp$V1, temp$V2, n=50)
image(kdexy, col=grey(seq(1,0.2,length=10)))

Yet the structure of the two data sets is the same (the dummy data [dat] and the real data [temp]):

> str(dat$x)
 num [1:80000] 0.669 0.609 -0.633 0.565 0.559 ...
> str(temp$V1)
 num [1:823180] 0 0 0 0 0.0146 ...
> summary(dat$x)
   Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
-4.2270 -0.1902  0.4841  0.4900  1.1600  5.3570 
> summary(temp$V1)
   Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
-1.0000  0.0000  0.0000 -0.0289  0.0000  0.9844 
> range(dat$x)
[1] -4.227400  5.357184
> range(temp$V1)
[1] -1.000000  0.984375
> str(temp$V2)
 num [1:823180] 1 1 15.5 15.5 18.5 ...
> summary(temp$V2)
   Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
   1.00    1.00   18.45   23.55   35.96  116.10 
> range(temp$V2)
[1]   1.0000 116.0829

They are both stored in dataframes and the only difference I'm aware of is the length, and that temp$V1 is bounded at -1 and 1.

The output of kdexy <- kde2d() differs between the two datasets. In the example data, the Z sections is populated with very small numbers; in the real dataset, every point is filled with 'NaN'.

Answer 1

My data are heavily concentrated around 0 (total n=850,000, n==0 ~ 650,000). Using a subset of data, where x<0 (n=150,000), the plots work.