From observing the graph data above: fractal_dimension_mean, smoothness_mean, symmetry_mean, texture_mean, texture_worst, smoothness_worst, compactness_worst, 'symmetry_worst', 'fractal_dimension_worst' and all of the SE features are not very useful in predicting the type of cancer. These columns will be dropped.

From the graphs, we can see that radius_mean, perimeter_mean, area_mean, concavity_mean and concave_points_mean are useful in predicting cancer type due to the distinct grouping between malignant and benign cancer types in these features.

We can also see that radius worst, area_worst, perimeter_worst,'concavity_worst', 'concave_points_worst' are also quite useful.