How to calculate the cumulative distribution function in python without using scipy

Question

How can I calculate the cumulative distribution function of a normal distribution in python without using scipy?

I'm specifically referring to this function:

from scipy.stats import norm
norm.cdf(1.96)

I have a Django app running on Heroku and getting scipy up and running on Heroku is quite a pain. Since I only need this one function from scipy, I'm hoping I can use an alternative. I'm already using numpy and pandas, but I can't find the function in there. Are there any alternative packages I can use or even implement it myself?

See mathworld.wolfram.com/NormalDistributionFunction.html for approximations. — Bill Bell
– Bill Bell, Commented Apr 2, 2018 at 18:46
Possible duplicate of How to calculate cumulative normal distribution in Python — ClimateUnboxed
– ClimateUnboxed, Commented Aug 15, 2019 at 10:10

Jared Wilber · Accepted Answer · 2018-04-02 18:52:04Z

9

Just use math.erf:

import math

def normal_cdf(x):
    "cdf for standard normal"
    q = math.erf(x / math.sqrt(2.0))
    return (1.0 + q) / 2.0

Edit to show comparison with scipy:

scipy.stats.norm.cdf(1.96)
# 0.9750021048517795

normal_cdf(1.96)
# 0.9750021048517796

answered Apr 2, 2018 at 18:52

Jared Wilber

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ClimateUnboxed · Accepted Answer · 2019-08-15 10:13:04Z

3

This question seems to be a duplicate of How to calculate cumulative normal distribution in Python where there are many alternatives to scipy listed.

I wanted to highlight the answer of Xavier Guihot https://stackoverflow.com/users/9297144/xavier-guihot which shows that from python3.8 the normal is now a built in:

from statistics import NormalDist

NormalDist(mu=0, sigma=1).cdf(1.96)
# 0.9750021048517796

answered Aug 15, 2019 at 10:13

ClimateUnboxed

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