cancer keys()dict_keys(['feature_names''data''descr''target''target_names']datasets that are included in scikit-learn are usually stored as bunch objectswhich contain some information about the dataset as well as the actual data all you need to know about bunch objects is that they behave like dictionarieswith the added benefit that you can access values using dot (as in bunch key instead of bunch['key']the dataset consists of data pointswith features eachin[ ]print("shape of cancer data{}format(cancer data shape)out[ ]shape of cancer data( of these data points are labeled as malignant and as benignin[ ]print("sample counts per class:\ {}format{nv for nv in zip(cancer target_namesnp bincount(cancer target))})out[ ]sample counts per class{'benign' 'malignant' to get description of the semantic meaning of each featurewe can have look at the feature_names attributein[ ]print("feature names:\ {}format(cancer feature_names)out[ ]feature names['mean radius'mean texture'mean perimeter'mean area'mean smoothness'mean compactness'mean concavity'mean concave points'mean symmetry'mean fractal dimension'radius error'texture error'perimeter error'area error'smoothness error'compactness error'concavity error'concave points error'symmetry error'fractal dimension error'worst radius'worst texture'worst perimeter'worst area'worst smoothness'worst compactness'worst concavity'worst concave points'worst symmetry'worst fractal dimension'supervised machine learning algorithms