import pandas as pd
import numpy as np
import timeit

from math import log

my_stat = pd.DataFrame({'x': np.random.random(size=10000)})

def with_pd():
    my_stat['y'] = my_stat['x'].map(log)

def with_pd_numexpr():
    my_stat.eval('y = log(x)', engine='numexpr', inplace=True)

def with_np():
    my_stat['y'] = np.log(my_stat['x'])

print(timeit.timeit('with_pd()', setup='from __main__ import with_pd', number = 100)) #0.525s
print(timeit.timeit('with_pd_numexpr()', setup='from __main__ import with_pd_numexpr', number = 100)) #0.305s
print(timeit.timeit('with_np()', setup='from __main__ import with_np', number = 100)) #0.122s