[Python] How to find the importance of the features for a logistic regression model?

I have a binary prediction model trained by logistic regression algorithm. I want know which features (predictors) are more important for the decision of positive or negative class. I know there is coef_ parameter which comes from the scikit-learn package, but I don't know whether it is enough for the importance. Another thing is how I can evaluate the coef_ values in terms of the importance for negative and positive classes. I also read about standardized regression coefficients and I don't know what it is.

Lets say there are features like size of tumor, weight of tumor, and etc to make a decision for a test case like malignant or not malignant. I want to know which of the features are more important for malignant and not malignant prediction.

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