# How many features can we input for a SVM to classify?

I am new to SVM classifiers. I read on the internet that SVM are binary classifiers and also many SVMs, as described in research papers, only take 2 features as the input.

My question is, does it have to be 2 input features? Can we use more than 2? If so, how do we write this code in python?

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.