from pandas import *

import numpy as np
import os

from vbench.api import Benchmark
from pandas.util.testing import rands
import pandas._tseries as lib
import pandas._sandbox as sbx
import time

import psutil

pid = os.getpid()
proc = psutil.Process(pid)

s = Series(np.random.randn(10000))

for _ in xrange(5):
    # print proc.get_memory_info()
    result = rolling_median(s, 1000)

fa98ab3227d0952d4562b7c6c770e271dccd1f1f
<mask token>

<mask token>
for _ in xrange(5):
    result = rolling_median(s, 1000)

<mask token>
pid = os.getpid()
proc = psutil.Process(pid)
s = Series(np.random.randn(10000))
for _ in xrange(5):
    result = rolling_median(s, 1000)

from pandas import *
import numpy as np
import os
from vbench.api import Benchmark
from pandas.util.testing import rands
import pandas._tseries as lib
import pandas._sandbox as sbx
import time
import psutil
pid = os.getpid()
proc = psutil.Process(pid)
s = Series(np.random.randn(10000))
for _ in xrange(5):
    result = rolling_median(s, 1000)

from pandas import *

import numpy as np
import os

from vbench.api import Benchmark
from pandas.util.testing import rands
import pandas._tseries as lib
import pandas._sandbox as sbx
import time

import psutil

pid = os.getpid()
proc = psutil.Process(pid)

s = Series(np.random.randn(10000))

for _ in xrange(5):
    # print proc.get_memory_info()
    result = rolling_median(s, 1000)
