Why is decision tree give only two nodes




While trying to run decision tree on some data I ran into an unexpected result:

I am getting only two nodes in which the data has been split.
What is the reason for this??And how do I rectify this problem,is it because there are large number of missing values in the data??
Also I am not being able to plot whatever is there:

> library(rattle)
> fancyRpartPlot(model.rpart)
Error in loadNamespace(name) : there is no package called ‘rpart.plot’

Is this because of the fact that there is only one level of data?
Can someone please help me with these issues??


@data_hacks-If you are getting only two nodes
the deciding factor can be only one, there are only two levels or there is lots of missing value in which other variable helps for predication.

Hope this helps,