# exponential distribution

# used for describing time till next event e.g failure / success etc.

# It has two parameters.
# scale - inverse of rate (see lam in poisson distribution) defaults to 1.0
# size - The shape of the returned array

# draw out a sample for exponential distribution with 2.0 scale with 2x3 size

from numpy import random

x = random.exponential(scale = 2, size = (2,3))

print(x)

# visualization of exponential distribution

# from numpy import random
import matplotlib.pyplot as plt 
import seaborn as  sns 

sns.distplot(random.exponential(size = 1000), hist = False)
plt.show

# Relationship between Poisson and exponential distribution

# poisson distribution deals with the number of occurences of an event in a time peroid
# whereas exponential distribution deals with the time between these events



