How many features can we input for a SVM to classify?
There is no restriction on the number of features. 

The syntax is exactly the same. For your tutorial, rather than 

X = iris.data[:, :2]


That takes only $2$ columns, just change it to a bigger number if those columsn area in your dataframe. It is a common practice that the last column is the $y$ values of which case just to remove that column, just use $-1$.

For some online tutorials, sometimes we use $2$ features for the convenience of visualization only. 

However, note that we do not want to use too many features as we want to build a model can be generalized. A simple model that works is better than a complicated model.