3D plot in R error

Question

I have been trying to plot a 3d plot of my data but I cannot figure out how to overcome some errors. Any help is highly appreciated.

>head(d1) #produced through the melt function as seen below
     Date variable     value
1 2007 Q2    0.890 1.1358560
2 2007 Q3    0.890 1.1560433
3 2007 Q4    0.890 0.3747925
4 2008 Q1    0.890 0.3866533
5 2008 Q2    0.890 0.3872620
6 2008 Q3    0.890 0.3844887

I have successfully managed to plot a heatmap using this:

d1<-melt(mydata,id.vars = "Date")
P1 <- ggplot(data=d1, aes(x=Date, y=variable, fill=value)) + 
  geom_tile() +
  ggtitle("My heatmap") +scale_fill_gradientn(colors=colorRampPalette(c("lightgray","royalblue","seagreen","orange","red","brown"))(500),name="Variable") +
  labs(x = "Quarter",y="Alpha") +
  theme_bw()
ggplotly(P1)
*Don't know how to automatically pick scale for object of type yearqtr. Defaulting to continuous.*

However, I want to create a 3d plot.

open3d()
rgl.surface(x=d1$variable, y=d1$Date, 
            coords=c(1,3,2),z=d1$value, 
            color=colorzjet[ findInterval(d1$value, seq(min(d1$value), max(d1$value), length=100))] )
axes3d()
Error in rgl.surface(x = d1$variable, y = d1$Date, coords = c(1, 3, 2),  : 
'y' length != 'x' rows * 'z' cols


plot_ly(x=d1$Date,y=d1$variable,z=d1$value,type="surface",colors=colors)
Error: `z` must be a numeric matrix
I have tried to use as.matrix(apply(d1,2,as.numeric)), but this returns NAs to the date argument.

Could it be the nature of the Quarterly dates that messes up the graph? (because even the heat map doesn't show the dates as Quarterly. Any tips?

dput(d1) output here: dput(d1) output

Answer 1

The file you uploaded is a CSV file, not dput output. But you can read it and plot it like this:

d1csv <- read.csv("dput_output.csv")
year <- as.numeric(sub(" .*", "", d1csv$Date))
quarter <- as.numeric(sub(".*Q", "", d1csv$Date))

Date <- matrix(year + (quarter - 1)/4, 55)
variable <- matrix(d1csv$variable, 55)
value <- matrix(d1csv$value, 55)

persp3d(Date, variable, value, col = "red")

This gives the following plot: