Feature Importance Scores Python
Not all the algorithms provide you feature_importance, some of them give you coeff(weights W1..W7) values.
So according to me, the way you are extracting feature_importance is correct. 


  However, this approach has the problem that out of n attributes, I
  will only get feature importance score for (n - 1) attributes as the
  nth attribute is the target variable.


Model gets trained based upon the features and target value. So you will get the feature_importance only for features and not for the target. 

Using statistical approach you can also analyse the relationship between the various features and the target value.

As a side note:


Make sure you normalized the whole features on the same scale for
better and faster training.