Gaussian

import numpy as np
import matplotlib.pyplot as plt
import math
 
#first some random data
data = np.linspace(-10, 10, 1000)
 
#https://en.wikipedia.org/wiki/Gaussian_filter
def gaussian1d(data, sigma=1):
    gaussian_curve = []
    for row in range(len(data)):
        gaussian_curve.append((1/(math.sqrt(2*math.pi)*sigma)*math.pow(math.e,(-1)*((data[row]**2 )/(2*sigma**2)))))
    return gaussian_curve    
 
sigmas = [0.5,1.0,1.5,2.0,2.5]
 
X = range(len(data))
for sigma in sigmas:
    plt.plot(X, gaussian1d(data, sigma), label='sigma='+str(sigma))
 
plt.legend()