In [9]:

    

import numpy as np
import pandas as pd


dti = pd.DatetimeIndex(start='2001/01/01', end='2002/02/01', freq='D')
s = pd.Series(np.random.rand(len(dti)), dti)


    

In [12]:

    

%pylab inline
s.plot()


    

    




Populating the interactive namespace from numpy and matplotlib






    
Out[12]:





<matplotlib.axes._subplots.AxesSubplot at 0x7f37eb7e8c50>






    

In [20]:

    

import tempfile

tf = tempfile.NamedTemporaryFile(prefix="test_",suffix=".csv")

f_list = map(lambda f: tempfile.NamedTemporaryFile(prefix="test_",suffix=".csv").name , range(10) )
print(f_list)


    

    




['/tmp/test_aSW96r.csv', '/tmp/test_0XeU7Z.csv', '/tmp/test_ATBhUY.csv', '/tmp/test_R1U_0s.csv', '/tmp/test__n4Jpi.csv', '/tmp/test_4LeiQI.csv', '/tmp/test_GRZWy8.csv', '/tmp/test_UILTfc.csv', '/tmp/test_k0hg7Z.csv', '/tmp/test_Iih9UH.csv']

In [32]:

    

print("{:.2%}".format(0.394304))

print("{:.2%}".format(1.0*9/len(f_list)))


print(":.2{st}".format(st=100.0*9/len(f_list)))


    

    




39.43%
90.00%
:.290.0

In [ ]:

    

suffix = datetime.datetime.now().strftime("%y%m%d_%H%M%S")