Pandas apply+map comparison

Pandas apply+map comparison

import numpy as np
import pandas as pd
import timeit
import geohash

samples = 1000
precision = 22
points = np.random.rand(samples, 2)
data = pd.DataFrame(points, columns=['lat', 'lng'])
data.lat += 13
data.lng += 52

data2 = data.copy()

def test1():
    data['test'] = data.apply(lambda x: geohash.encode(x['lat'], x['lng'], precision=precision), axis=1)

def test3():
    data['_tmp1'] = zip(data.lat, data.lng)
    data['test'] = data._tmp1.map(lambda x: geohash.encode(x[0], x[1], precision=precision))
    #data.drop('_tmp1', 1)
    del data['_tmp1']

def test4():
    data['_tmp1'] = zip(data.lat, data.lng)
    data['test'] = data._tmp1.apply(lambda x: geohash.encode(x[0], x[1], precision=precision))
    del data['_tmp1']

def test2():
    for index, row in data2.iterrows():
        geohash.encode(row['lat'], row['lng'], precision=precision)

iterations = 10
print timeit.timeit('test1()', setup="from __main__ import test1", number=iterations) / iterations * 1000
print timeit.timeit('test2()', setup="from __main__ import test2", number=iterations) / iterations * 1000
print timeit.timeit('test3()', setup="from __main__ import test3", number=iterations) / iterations * 1000
print timeit.timeit('test4()', setup="from __main__ import test4", number=iterations) / iterations * 1000