#!/usr/bin/env python
# coding: utf-8

# ## Python Basics

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1 + 2 * 3 


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2**3


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x = "Machine" + "Learning"
print x


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x.upper()


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x.lower()


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len(x)


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a = 2 + 3
b = a * 4
c = b - 7
L = [a,b,c]
print L


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M = [10, 2, "a", 3.5]
N = L + M
print N


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len(N)


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N[2]


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N[:3]


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N[3:]


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N[3:6]


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# This is what a comment looks like 
fruits = ['apples','oranges','pears','bananas']
for fruit in fruits:
    print fruit + ' for sale'

fruitPrices = {'apples': 2.00, 'oranges': 1.50, 'pears': 1.75}
for fruit, price in fruitPrices.items():
    if price < 2.00:
        print '%s cost %f a pound' % (fruit, price)
    else:
        print fruit + ' are too expensive!'


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# Example of python's list comprehension construction:

nums = [1,2,3,4,5,6]
plusOneNums = [x+1 for x in nums]
print "plusOneNums =", plusOneNums
oddNums = [x for x in nums if x % 2 == 1]
print "oddNums = ", oddNums
oddNumsPlusOne = [x+1 for x in nums if x % 2 ==1]
print "oddNumsPlusOn = ", oddNumsPlusOne


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# Dictionaries

studentIds = {'knuth': 42.0, 'turing': 56.0, 'nash': 92.0 }
studentIds['turing']


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studentIds['ada'] = 97.0
studentIds


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del studentIds['knuth']
studentIds


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studentIds['knuth'] = [42.0,'forty-two']
studentIds


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studentIds.keys()


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studentIds.values()


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studentIds.items()


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len(studentIds) 


# ## Numpy

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import numpy as np


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# Creating a 1-d array

A = np.array([1,2,3,4,5])
A


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# Creating a 1-d array from an existing Python list

L = [1, 2, 3, 4, 5, 6]

A = np.array(L)
A


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A / 5


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np.array([1.0,2,3,4,5]) / 5


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M = np.array([2, 3, 4, 5, 6, 7])

P = L * M
P


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P.sum()


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P.mean()


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# Dot product of two vectors

np.dot(L, M)


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# Creating a 2-d array

X = np.array([[1,2,3],[4,5,6],[7,8,9]])
X


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# Transpose a 2-d array

X.T


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# Array slicing

X[1,2]


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X[:,1]


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X[0,:]


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X[1:,1:]


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X[1:,0:2]


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# Using arrays to index into other arrays (e.g., Boolean masks)

A = np.array([1, 2, 3, 4, 5, 6])

A > 3


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A[A > 3]


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sum(A[A > 3])


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Ind = (A > 1) & (A < 6)
print Ind
A[Ind]


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