[FIXED] Parallelize dummy data generation in pandas

Issue

I would like to generate a dummy dataset composed of a fake first name and a last name for 40 milion records using multiple processor n cores.

Below is a single task loop that generates a first name and a last name and appends them to a list:

import pandas as pd
from faker import Faker

def fake_data_generation(records):
    fake = Faker(['en_US','en_GB'])
    
    person = []
    
    for i in range(records):
        first_name = fake.first_name()
        last_name = fake.last_name()
        person.append({"First_Name": first_name,
                       "Last_Name": last_name}
                     )
    return person

Output:

for i in range(5):
    df = pd.DataFrame(fake_data_generation(i))

>>> df
  First_Name Last_Name
0      Colin   Stewart
1    Barbara      Rios
2     Victor     Green
3  Stephanie     Booth

Solution

Maybe you can use providers directly:

import pandas as pd
import numpy as np
from faker.providers.person.en_US import Provider as us
from faker.providers.person.en_GB import Provider as gb

first_names = list(set(us.first_names).union(gb.first_names))
last_names = list(set(us.last_names).union(gb.last_names))

N = 40_000_000
df = pd.DataFrame({'First_Name': np.random.choice(first_names, N),
                   'Last_Name': np.random.choice(last_names, N)})

Output:

>>> df
         First_Name Last_Name
0             Kayla      Tran
1              Gary     Bates
2             Daisy   Leblanc
3           Tiffany     Ahmed
4            Kellie       May
...             ...       ...
39999995   Kristine   Collier
39999996      Joyce     Mccoy
39999997       Paul   Padilla
39999998      Tonya     Bevan
39999999      Julie    Bright

[40000000 rows x 2 columns]

Answered By - Corralien