How to properly fit a decision tree to be able to graph it in R?

I'm trying to graph the object resulting from fitting a decision tree model , but I'm running into several problems:

tree_model<- tree(High~ ShelveLoc + Price + Advertising + Income + Age + CompPrice,
                 data = data,na.action = "na.exclude", control = tree.control(nobs = 400, minsize = 1))

After executing the above, it returns the following message:

Warning messages:
1: In tree(High ~ ShelveLoc + Price + Advertising + Income + Age +  :
  NAs introduced by coercion
2: In tree(High ~ ShelveLoc + Price + Advertising + Income + Age +  :
  NAs introduced by coercion

From what I understand of the message, I think that some missing values ​​may be negatively affecting the fit of the model, so I've tried various options in the argument na.action, but the same message always appears. On the other hand, I have reviewed the dataframe and there is no missing value, I have also modified the parameters of tree.controland I still do not get the graph.

Next I try to graph the model:

plot(tree_model)

But the following message appears:

Error in plot.tree(tree_model) : cannot plot singlenode tree

From what I have read, it is usually due to the fact that my data has very little variance and this means that there is only one node in my tree, but since it is a class exercise I know that a tree with several nodes should be generated and it will probably be me is escaping something in the function tree(). After reviewing the PDF available in the CRAN of the package in question, I still don't know what argument to include or modify in the function.

What do I need to modify in my code to get the graph I want?