Fitting Probability Distributions to Data with SciPy (Python)

UPDATE: I realized the method I used in this video, called fit() is only included for CONTINUOUS distributions (normal, gamma, exponential, etc) in SciPy. If you're trying to fit a DISCRETE distribution (Poisson, geometric, binomial, etc), I made a new video explaining how to do that:

UPDATE 2: After I made this video, SciPy 1.9 was released, which includes a new method that makes it easy to fit distributions to data, and can be used for both continuous and discrete distributions. Here is the link to the documentation for this method:

Hi everyone! This video is about how to use the Python SciPy library to fit a probably distribution to data, using the normal distribution and gamma distribution as examples.

All the code from my videos is available on my Github:

Let me know if you have any questions! Thanks for watching!

[MikeSaintAntoine]

Hi everyone, thanks for watching! Here's the link to the code on my Github in case you want to try it for yourself (also feel free to add me as a friend on Github if you want 🙂) :

[jameskaihatu]

Python newbie here, emerging into the modern world from Fortran...77. I learned a lot. Thanks.

[nnamdiodozi]

Great video Mike. What method do I use to fit to discrete distributions. I looked under the scipy binom object and there is no fit method. Is it possible to compute measure of fit eg least squares, AIC or BIC?

[andrewcameron]

Thank you very much for your helpful video! It was exactly what I was looking for. I just subscribed to your channel. Wishing you the best!

[pastorsoto]

Great video! If you want to test U-shape distribution what test would you choose. I look at the documentation but couldn't find how to do it

[digantchavda]

Thank you so much! Very helpful video!!

[learning_with_irving]

Dude, How are you so smart? Is it because your name is Michael and also a saint?