Calculate the Standard Deviation of Fundamental Frequency (MFCC) I'm implementing a gunshot detector following the article "Algorithm for Gunshot Detection Using
Mel-Frequency Cepstrum Coefficients
(MFCC)" (paywall).

In the article, the authors uses 22 features based on MFCC (coeficients normalized between 0.1 and 0.9). One of the features is "Standard deviation of fundamental frequency". I already spent all my day trying to figure out the proper way to do this calculation.

The expected value for a gunshot is near 0.04.
You calculate fundamental frequency of the signal with some pitch extraction algorithm, for example YIN, https://github.com/ronggong/pypYIN. It is a vector of numbers, then you calculate standard deviation of it, that would be a number.

Overall, this feature is not very important for detection. Also, the paper you are trying to reproduce is not quite modern, these days you can get much better results with VGGish and Audioset, something like

https://github.com/luuil/Tensorflow-Audio-Classification

or 

https://github.com/IBM/MAX-Audio-Embedding-Generator