Drawing multiple univariate normal distribution

Question

Does anyone know how to draw multiple Gaussian distributions on a single plot using Python? Ive got some normal distributed data with different means and standard deviations that i need to plot. Thnx a lot I could draw only one. Please be simple with me, ive literally just started using Python

Answer 1

Let's suppose you have 3 different combinations of mean mu and standard deviaton sigma. You can choose as many as you like, but for example purposes I used 3.

from matplotlib import pyplot as mp
import numpy as np

def gaussian(x, mu, sig):
    return 1./(np.sqrt(2*np.pi)*sigma)*np.exp(-0.5 * (1./sigma*(x - mu))**2)

for mu, sig in [(0.5, 0.1), (1.0, 0.2), (1.5, 0.3)]: #(mu,sigma)
    mp.plot(gaussian(np.linspace(-8, 8, 100), mu, sig))

mp.show()

Define your mu and sigma in this line, you can add as many combinations as you like:

for mu, sig in [(0.5, 0.1), (1.0, 0.2), (1.5, 0.3)]: #(mu,sigma)

in my case it is

• mu = 0.5, sigma = 0.1
• mu = 1.0, sigma = 0.2
• mu = 1.5, sigma = 0.3

Result:

*EDIT

%matplotlib inline
from matplotlib import pyplot as mp
import numpy as np

def gaussian(x, mu, sig):
    return 1./(np.sqrt(2*np.pi)*sigma)*np.exp(-0.5 * (1./sigma*(x - mu))**2)

for mu, sigma in [(1, 2), (0.5, 1), (0, 0.5)]: #(mu,sigma)
    mp.plot(gaussian(np.linspace(-4, 6, 100, ), mu, sigma))
    mp.xlim(0,110)  #set x-axes limits
    mp.ylim(0,1)  #set y-axes limits

mp.show()

Result: