import numpy

numpy.loadtxt(fname='inflammation-01.csv', delimiter=',')

weight_kg = 55

print weight_kg

print 'weight in pounds:', 2.2 * weight_kg

weight_kg = 57.5
print 'weight in kilograms is now:', weight_kg

weight_lb = 2.2 * weight_kg
print 'weight in kilograms:', weight_kg, 'and in pounds:', weight_lb

weight_kg = 100.0
print 'weight in kilograms is now:', weight_kg, 'and weight in pounds is still:', weight_lb

data = numpy.loadtxt(fname='inflammation-01.csv', delimiter=',')

print data

print type(data)

print data.shape

print 'first value in data:', data[0, 0]

print 'middle value in data:', data[30, 20]

print data[0:4, 0:10]

print data[5:10, 0:10]

small = data[:3, 36:]
print 'small is:'
print small

doubledata = data * 2.0

print 'original:'
print data[:3, 36:]
print 'doubledata:'
print doubledata[:3, 36:]

tripledata = doubledata + data

print 'tripledata:'
print tripledata[:3, 36:]

print data.mean()

print 'maximum inflammation:', data.max()
print 'minimum inflammation:', data.min()
print 'standard deviation:', data.std()

patient_0 = data[0, :] # 0 on the first axis, everything on the second
print 'maximum inflammation for patient 0:', patient_0.max()

print 'maximum inflammation for patient 2:', data[2, :].max()

print data.mean(axis=0)

print data.mean(axis=0).shape

print data.mean(axis=1)

element = 'oxygen'
print 'first three characters:', element[0:3]
print 'last three characters:', element[3:6]

%matplotlib inline

from matplotlib import pyplot
pyplot.imshow(data)
pyplot.show()

ave_inflammation = data.mean(axis=0)
pyplot.plot(ave_inflammation)
pyplot.show()

print 'maximum inflammation per day'
pyplot.plot(data.max(axis=0))
pyplot.show()

print 'minimum inflammation per day'
pyplot.plot(data.min(axis=0))
pyplot.show()

import numpy as np
from matplotlib import pyplot as plt

data = np.loadtxt(fname='inflammation-01.csv', delimiter=',')

plt.figure(figsize=(10.0, 3.0))

plt.subplot(1, 3, 1)
plt.ylabel('average')
plt.plot(data.mean(0))

plt.subplot(1, 3, 2)
plt.ylabel('max')
plt.plot(data.max(0))

plt.subplot(1, 3, 3)
plt.ylabel('min')
plt.plot(data.min(0))

plt.tight_layout()
plt.show()