Sklearn SVM - how to get a list of the wrong predictions?
The following method works for all kinds of classification problem.

Use list comprehension to find all indices of wrong prediction:

indices = [i for i in range(len(y_test)) if y_test[i] != y_pred[i]]


wrong predictions will then be:

wrong_predictions = test_dataframe.iloc[indices,:]


You can also make indices a new column of wrong_predictions, it would be convenient to compare :)