%%file inout.dat
Here is a nice file
with a couple lines of text
it is a haiku

f = open('inout.dat')
print f.read()
f.close()

f = open('inout.dat')
print f.readlines()
f.close()

for line in open('inout.dat'):
    print line.split()

contents = open('inout.dat').read()
out = open('my_output.dat', 'w')
out.write(contents.replace(' ', '_'))
out.close()

!cat my_output.dat

# writelines() is the opposite of readlines()
lines = open('inout.dat').readlines()
out = open('my_output.dat', 'w')
out.writelines(lines)
out.close()

!cat my_output.dat

%pylab inline
import numpy as np
import matplotlib.pyplot as plt

arr = np.arange(10).reshape(2, 5)
np.savetxt('test.out', arr, fmt='%.2e', header="My dataset")
!cat test.out

DataIn = np.loadtxt('test.out')
print DataIn.shape
print DataIn

print DataIn[1,:]

a, b, c, d, x = np.loadtxt('test.out', unpack=True)
print a
print b
print c
print d
print x

a, b = np.loadtxt('test.out',unpack=True, usecols=[0,1])
print a
print b

%%file input.csv
# My csv example data
    0.0,  1.1,  0.1
    2.0,  1.9,  0.2
    4.0,  3.2,  0.1
    6.0,  4.0,  0.3
    8.0,  5.9,  0.3

!cat input.csv

#throws an error because commas are not part of floating point numbers
x, y = np.loadtxt('input.csv',unpack=True, usecols=[0,1,2])

x, y = np.loadtxt('input.csv',unpack=True, delimiter=',', usecols=[0,1])
print x,y

t = np.array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])
v = np.array([0.137,0.456,0.591,0.713,0.859,0.926,1.139,1.327,1.512,1.875])

p = 0.15 + v/10.0

np.savetxt('output.dat', (t,p))

DataOut = np.column_stack((t,p))
np.savetxt('output.dat', DataOut)

!cat output.dat

np.savetxt('output.dat', DataOut, fmt=('%3i', '%4.3f'))

!cat output.dat

myheader ="\nTime and Pressure data\nt (s) p (Pa)\n"
np.savetxt('output.dat', DataOut, fmt=('%3i', '%4.3f'),header=myheader)
!cat output.dat

arr2 = DataIn #copy the array from before
np.save('test.npy', arr2)
# Now we read this back
arr2n = np.load('test.npy')
# Let's see if any element is non-zero in the difference.
# A value of True would be a problem.
print 'Any differences?', np.any(arr2-arr2n)

np.savez('test.npz', arr, arr2)
arrays = np.load('test.npz')
arrays.files

np.savez('test.npz', array1=arr, array2=arr2)
arrays = np.load('test.npz')
arrays.files

print 'First row of first array:', arrays['array1'][0]
# This is an equivalent way to get the same field
print 'First row of first array:', arrays.f.array1[0]