Solved – How to plot a fan (Polar) Dendrogram in R

data visualizationdendrogramr

I'm referring to something like this:

alt text

suggested dataset for showing a solutions:

data(mtcars)
plot(hclust(dist(mtcars)))

Best Answer

In phylogenetics, this is a fan phylogram, so you can convert this to phylo and use ape:

library(ape)
library(cluster) 
data(mtcars)
plot(as.phylo(hclust(dist(mtcars))),type="fan")

Result:
alt text

Related Solutions

Cluster Analysis in R – Why Are There Reversals on the Dendrogram?

This is unavoidable consequence of the data and the clustering method. Centroid and median agglomerations can produce such "reversals" with some data. Because, in principle, distance between cluster centres can diminish on a later step of agglomeration.

Most practical way out is to ignore the fact that the reversal occured and to align the "sunk" senior (later) cross-bars with the highest cross-bar which is junior (earlier) to it. Like I show below.

One more notion. In your place, I'd refrain from using geometric methods (centroid, median, Ward) - suitable for euclidean distance - with nonmetric Gower coefficient.

enter image description here

Solved – How to plot 20 years of daily data in time series

The problem with your data is not that it is extremely detailed: you have no values at weekends, that's why it is plotted with gaps. There are two ways to deal with it:

Either try to guess approximate values in weekends with some smoothing methods (smooth.spline, loess, etc.). Code of simple interpolation is below. But in this case you will introduce something "unnatural" and artificial to the data. That's why I prefer second option.

currentDate <- min(as.Date(oracle$Date))
dates <- c(currentDate)
openValues <- c(oracle$Open[5045])
i <- 5044
while (i > 0) {
  currentDate <- currentDate + 1;
  dates <- c(dates, currentDate)
  if (currentDate == as.Date(oracle$Date[i])) {
        # just copy value and move
        openValues <- c(openValues, oracle$Open[i])
        i <- i-1
      } else {
        # interpolate value
        openValues <- c(openValues, mean(oracle$Open[i:i-1]))
  }
}
plot(dates, openValues, type="l")

You can go from daily basis to a weekly basis, just averaging (for example) five sequential points that belog to one week (in this case you are "killing" some information). Just a quick example of how to do that would be

openValues = c(mean(oracle$Open[1:5]));
dates = c(as.Date(oracle$Date[1]));
for (i in seq(6,5045,5)) {
  openValues = c(openValues, mean(oracle$Open[i:i+5]));
      dates = c(dates, as.Date(oracle$Date[i]));
}
plot(dates, openValues, type="l")

Hope it will help.

Best Answer

Related Solutions

Cluster Analysis in R – Why Are There Reversals on the Dendrogram?

Solved – How to plot 20 years of daily data in time series

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