Zipf Distribution
Zipf distritutions are used to sample data based on zipf's law.
Zipf's Law: In a collection the nth common term is 1/n times of the most common term. E.g. 5th common word in english has occurs nearly 1/5th times as of the most used word.
It has two parameters:
a - distribution parameter.
size - The shape of the returned array.
Example
Draw out a sample for zipf distribution with distribution parameter 2 with size 2x3:
from numpy import random
x = random.zipf(a=2, size=(2, 3))
print(x)
Try it Yourself »
Visualization of Zipf Distribution
Sample 1000 points but plotting only ones with value < 10 for more meaningful chart.
Example
from numpy import random
import matplotlib.pyplot as plt
import seaborn as sns
x = random.zipf(a=2, size=1000)
sns.distplot(x[x<10], kde=False)
plt.show()
Result
