Voting patterns similarities
The politicians and Political parties follow a set of principles and characteristics. They always follow these things during voting on legislations and bills. you can use T-distributed Stochastic Neighbor Embedding (t-SNE), machine learning algorithm for visualization developed by Laurens van der Maaten and Geoffrey Hinton. This method helps us to visualize the clusters and similarities of the observations.

Like-minded MP's and political parties with similar principles cluster together(neighbors). 

The t-SNE 1algorithm comprises two main stages. First, t-SNE constructs a probability distribution over pairs of high-dimensional objects in such a way that similar objects have a high probability of being picked, whilst dissimilar points have an extremely small probability of being picked. Second, t-SNE defines a similar probability distribution over the points in the low-dimensional map, and it minimizes the Kullback–Leibler divergence between the two distributions with respect to the locations of the points in the map. Note that whilst the original algorithm uses the Euclidean distance between objects as the base of its similarity metric, this should be changed as appropriate.