Implementing sklearn.linear_model.SGDClassifier using python
I think that this is the same issue as in this question.

The shape of $X$ must be (n_samples, n_features) as explained in the
SVC.fit docstring. A 1-d array is interpreted as a single sample (for
convenience when doing predictions on single samples). Reshape your $X$
to (n_samples, 1).

That means you should use numpy.reshape to reshape the $X$ column. If the data frame has n rows, you should use
X_new = X.reshape(n, 1)

Then use the fit method with $X_{new}$. Note: you probably don't need to do this if you use two or more $X$ columns for your model fitting.