How to draw a map of a cluster analysis results I have performed k-mean clustering on a demographic data set. Now I wish to show the results on a (geographical) map, i.e. I want to show the clusters that I got after the analysis in a map. Can someone recommend me a platform (any free software or any online sources) where I can draw such a map? 
PS - If this is the wrong stackexchange site to ask this question then please direct me to the correct one. Thank you!
 A: A nice and popular method of viusalizing cluster analysis are dendrogramms. You can image it as a sort of tree like structure, that represents the linkage between clusters. It is defined by a metric (e.g. eucledian) and a clustering algorithm (e.g. ward).
Another way would to plot the data and colorize the points accoriding to their clustering. You could also colorize the backround in a similar way.
A good and free online resource would be "The R Programming Language". There are plenty tutorials to be found.
I'll try to give an short introduction, which i took from statmethods.net
Prepate Data
# Prepare Data
mydata <- na.omit(mydata) # listwise deletion of missing
mydata <- scale(mydata) # standardize variables

Cluster and Visualize
You can use a  Dendrogramm to visualize a hierarchical clustering result like so:
# Ward Hierarchical Clustering
d <- dist(mydata, method = "euclidean") # distance matrix
fit <- hclust(d, method="ward") 
plot(fit) # display dendogram
groups <- cutree(fit, k=5) # cut tree into 5 clusters
# draw dendogram with red borders around the 5 clusters 
rect.hclust(fit, k=5, border="red")

which will produce this image 
K-means
R provides also k-means clustering. The resulting clustering can also be shown like so:
# K-Means Clustering with 5 clusters
fit <- kmeans(mydata, 5)

# Cluster Plot against 1st 2 principal components

# vary parameters for most readable graph
library(cluster) 
clusplot(mydata, fit$cluster, color=TRUE, shade=TRUE, 
    labels=2, lines=0)

# Centroid Plot against 1st 2 discriminant functions
library(fpc)
plotcluster(mydata, fit$cluster)

Which will produce this figure:

