In [1]:

    

import glob


    

In [2]:

    

print glob.glob('*.csv')


    

    




['inflammation-08.csv', 'inflammation-05.csv', 'inflammation-03.csv', 'small-02.csv', 'inflammation-09.csv', 'inflammation-06.csv', 'inflammation-01.csv', 'inflammation-02.csv', 'small-03.csv', 'inflammation-11.csv', 'inflammation-12.csv', 'inflammation-10.csv', 'inflammation-04.csv', 'small-01.csv', 'inflammation-07.csv']

In [5]:

    

datafiles = glob.glob('*.csv')
datafiles.sort()
print datafiles[:3]
for filename in datafiles[:3]:
    print filename


    

    




['inflammation-01.csv', 'inflammation-02.csv', 'inflammation-03.csv']
inflammation-01.csv
inflammation-02.csv
inflammation-03.csv

In [6]:

    

import numpy
import matplotlib.pyplot


    

    




Vendor:  Continuum Analytics, Inc.
Package: mkl
Message: trial mode expires in 29 days

In [9]:

    

%matplotlib inline


    

In [10]:

    

datafiles = glob.glob('*.csv')
datafiles.sort()
print datafiles[:3]
for filename in datafiles[:3]:
    print filename

    data = numpy.loadtxt(fname=filename, delimiter=',')

    fig = matplotlib.pyplot.figure(figsize=(10.0, 3.0))

    axes1 = fig.add_subplot(1, 3, 1)
    axes2 = fig.add_subplot(1, 3, 2)
    axes3 = fig.add_subplot(1, 3, 3)

    axes1.set_ylabel('average')
    axes1.plot(data.mean(axis=0))

    axes2.set_ylabel('max')
    axes2.plot(data.max(axis=0))

    axes3.set_ylabel('min')
    axes3.plot(data.min(axis=0))

    fig.tight_layout()
    matplotlib.pyplot.show(fig)


    

    




['inflammation-01.csv', 'inflammation-02.csv', 'inflammation-03.csv']
inflammation-01.csv






    













    




inflammation-02.csv






    













    




inflammation-03.csv






    

In [ ]: