k-means

data = np.random.randn(100, 2)
def kmeans(data, k):
    # randomly initialize k centroids
    # initialize cluster assigments
    # loop until no centroid changes
    # calculate distances of all data points to each centroid
    # move the centroids to their new cluster's center of mass
    # reassign the data points to clusters
    pass