Single scalar from vector

I am aware that this question is very general, but I found this question and it made me curious. What are the sensible ways that you can think of to derive a single scalar value from a vector? Of course this procedure will vary a lot according to your data and your purpose and will result in an information loss, but what are the alternatives? For now, this is what I have (from linked question and mine):

• Length. Compute the Euclidean norm for each vector.
• Max. Take the maximum value of the vector.
• Central tendency. Mean, median, mode etc.
• Measures of distribution shape. Skewness and Kurtosis.
• Dispersion. Variance, standard deviation, IQR, range, entropy, etc.
• Dimensionality reduction. Perform some kind of dimensionality reduction (e.g. PCA, t-SNE, Isomap, etc.) to the vector set and keep the value of the first component.
• Distance from centroid. For every vector, compute the distance from the centroid and use this scalar as an index of the eccentricity of the vector.