I just looked at the PCA in scikit-learn, but I didn't find a way to evaluate the quality of representation for variables and individuals like I usually do using the squared cosine. The squared cosine between the vector and the projection of the individual or the variable on the axis is used to determine the quality of the representation. For instance with the FactoMineR package in R to get those results for the variables you can simply do : res.pca$var$cos2Where res.pca are the results of your PCA.So how would I do something similar with scikit-learn ? 
How to evaluate the quality of representation for variables and individuals of a PCA in scikit-learn?
scikit learn;pca