Plotting k-means output - python
If the dim of your data is more than 2, you may want to transform your data with PCA, t-SNE or Custom linear projections.

t-SNE is recommended for clustering result.

For example:

from sklearn.manifold import TSNE
tsne = TSNE(n_components=2, random_state=0)
data = tsne.fit_transform(data)


This may lose some information, but useful for visualization.