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Showing content from https://github.com/pandas-dev/pandas/issues/10081 below:

speed up certain string operations · Issue #10081 · pandas-dev/pandas · GitHub

from SO

on big enough strings this might be quite useful for a number of string ops.

import pandas as pd
import random
import numpy as np
from StringIO import StringIO

def make_ip():
    return '.'.join(str(random.randint(0, 255)) for n in range(4))

df = pd.DataFrame({'ip': [make_ip() for i in range(20000)]})

%timeit df[['ip0', 'ip1', 'ip2', 'ip3']] = df.ip.str.split('.', return_type='frame')
#1 loops, best of 3: 3.06 s per loop

%timeit df[['ip0', 'ip1', 'ip2', 'ip3']] = df['ip'].apply(lambda x: pd.Series(x.split('.')))
#1 loops, best of 3: 3.1 s per loop

%timeit df[['ip0', 'ip1', 'ip2', 'ip3']] = \
    pd.read_table(StringIO(df['ip'].to_csv(None,index=None)),sep='.')
#10 loops, best of 3: 46.4 ms per loop

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