Help with calculating the information (Entropy)

and the Info gain with the below equation

Information Content (Entropy): I(P(v1),,P(vk))=i=1P(vi)log2P(vi) Where: k is the number of classes, vk refers to the samples belong to the Class k,P(vk) is the percentage of number of sample vk among all sample A chosen attribute A divides the training set E into subsets E1,,Ev according to their values for A, where A has v distinct values. remainder(A)=i=1vp+npi+niI(pi+nipi,pi+nini) Information Gain (IG) or reduction in entropy from the attribute test: IG(A)=I(p+np,p+nn)remainder(A) Calculate (1) the information and (2) the remainder of information for the following tree with a specific attribute. Your results should be in fractional format rather than decimal format. For example, 2/3, or 6Xlog(3), or 3+log5+log(2/3), where X represents multiplication. (1) the information: (2) the remainder of information