what does "~0" mean in the R model matrix

Question

I am trying to understand model matrix in R (model.matrix), to convert categorical variables to dummy variables and came across the following code

# Option 2: use model.matrix() to convert all categorical variables in the data frame into a set of dummy variables. We must then turn the resulting data matrix back into 
# a data frame for further work.
xtotal <- model.matrix(~ 0 + REMODEL, data = df)
xtotal <- as.data.frame(xtotal)

Can someone please help me understand what "~0" here mean ? And what the code is trying to do ?

Answer 1

+ 0 means that the model will not have an intercept, i.e., a column of 1s. In the presence of a factor variable, when an intercept is present, one of the levels will be removed in order to ensure that the model matrix is full rank, which is required in ordinary least squares regression. When the intercept is absent, all levels of the factor can remain.

So, this code is a way to convert a factor to a matrix where dummy variables for all the levels are present. Omitting + 0 would replace one of the dummies with a column of 1s, which may not be useful for your purpose.