On Tue, Nov 2, 2010 at 10:58 PM, Santosh Srinivas
<santosh.srini...@gmail.com> wrote:
> Thanks Gabor. I used melt to transform the data and plot using balloonplot.
>
> tData <- structure(list(A = c(0.2, 0.13, 0.05, 0.1, 0.02, 0.18, 0.09, 0.06,
> 0.13), B = c(0.15, 0.06, 0.09, 0.02, 0.03, 0.12, 0.01, 0.15, 0.06), C
> = c(-0.1, 0, -0.07, -0.06, -0.05, -0.05, -0.06, -0.08, -0.07), D =
> c(-0.15, -0.05, -0.1, -0.03, -0.13, -0.04, -0.1, -0.04, -0.15), E =
> c(-0.17, -0.16, -0.08, -0.07, -0.09, -0.14, -0.1, -0.05, 0)), .Names =
> c("A", "B", "C", "D", "E"), class = "data.frame", row.names = c(NA,
> -9L))
>
> tData$Period <- rownames(tData)
>
> tData.m <- melt(tData)
>
> # need to find a way to adjust the color for -ve values
> balloonplot(tData.m$Period,tData.m$variable,abs(tData.m$value))
>
You can also try fixing up this where TS is dput object:
mat <- as.matrix(TS)
plot(col(TS) ~ row(TS), cex = 5 * (mat - min(mat)) / diff(range(mat)),
col = 1 + (mat > 0))
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