In [50]:

    

users = {"Angelica": {"Blues Traveler": 3.5, "Broken Bells": 2.0,
                      "Norah Jones": 4.5, "Phoenix": 5.0, 
                      "Slightly Stoopid": 1.5,
                      "The Strokes": 2.5, "Vampire Weekend": 2.0},
        "Bill": {"Blues Traveler": 2.0, "Broken Bells": 3.5,
                 "Deadmau5": 4.0, "Phoenix": 2.0,
                 "Slightly Stoopid": 3.5, "Vampire Weekend": 3.0},
        "Chan": {"Blues Traveler": 5.0, "Broken Bells": 1.0,
                "Deadmau5": 1.0, "Norah Jones": 3.0,
                "Phoenix": 5, "Slightly Stoopid": 1.0},
        "Dan": {"Blues Traveler": 3.0, "Broken Bells": 4.0,
                "Deadmau5": 4.5, "Phoenix": 3.0,
                "Slightly Stoopid": 4.5, "The Strokes": 4.0,
                "Vampire Weekend": 2.0},
        "Hailey": {"Broken Bells": 4.0, "Deadmau5": 1.0,
                    "Norah Jones": 4.0, "The Strokes": 4.0,
                    "Vampire Weekend": 1.0},
                    "Jordyn": {"Broken Bells": 4.5, "Deadmau5": 4.0, "Norah Jones": 5.0,
                    "Phoenix": 5.0, "Slightly Stoopid": 4.5,
                    "The Strokes": 4.0, "Vampire Weekend": 4.0},
        "Sam": {"Blues Traveler": 5.0, "Broken Bells": 2.0,
                "Norah Jones": 3.0, "Phoenix": 5.0,
                "Slightly Stoopid": 4.0, "The Strokes": 5.0},
        "Veronica": {"Blues Traveler": 3.0, "Norah Jones": 5.0,
                    "Phoenix": 4.0, "Slightly Stoopid": 2.5,
                    "The Strokes": 3.0}}


    

In [51]:

    

rating1 = users["Angelica"]


    

In [52]:

    

rating2 = users["Bill"]


    

In [53]:

    

def manhattan(rating1, rating2):
    distance = 0
    for key in rating1:
        if key in rating2:
            #print key
            distance += abs(rating1[key] - rating2[key])
    return distance


    

In [54]:

    

manhattan(rating1, rating2)


    

    
Out[54]:





9.0

In [66]:

    

def computeNearestNeighbor(username, users):
    distances = []
    for user in users:
        if user != username:
            distance = manhattan(users[username], users[user])
            distances.append((distance, user))
    distances.sort()
    return distances


    

In [67]:

    

computeNearestNeighbor("Angelica", users)


    

    
Out[67]:





[(3.5, 'Veronica'),
 (4.5, 'Chan'),
 (5.0, 'Hailey'),
 (8.0, 'Sam'),
 (9.0, 'Bill'),
 (9.0, 'Dan'),
 (9.5, 'Jordyn')]

In [68]:

    

computeNearestNeighbor("Hailey", users)


    

    
Out[68]:





[(2.0, 'Veronica'),
 (4.0, 'Chan'),
 (4.0, 'Sam'),
 (4.5, 'Dan'),
 (5.0, 'Angelica'),
 (5.5, 'Bill'),
 (7.5, 'Jordyn')]

In [102]:

    

def recommend(username, nearestFunc):
    nearest = nearestFunc(username, users)[0][1]
    recommends = []
    for artist in users[nearest]:
        if not artist in users[username]:
            recommends.append((artist, users[nearest][artist]))
    return sorted(recommends, key = lambda x: x[1], reverse = True)
    #return sorted(recommends, lambda x, y: cmp(x[1], y[1]), reverse = True)


    

In [103]:

    

recommend("Hailey", computeNearestNeighbor)


    

    
Out[103]:





[('Phoenix', 4.0), ('Blues Traveler', 3.0), ('Slightly Stoopid', 2.5)]

In [90]:

    

recommend("Dan")


    

    
Out[90]:





[('Norah Jones', 5.0)]

In [114]:

    

def minkowski(rating1, rating2, r):
    distance = 0
    for artist in rating1:
        if artist in rating2:
            distance += pow(abs(rating1[artist] - rating2[artist]), r)
    return pow(distance, 1/r)


    

In [115]:

    

minkowski(rating1, rating2, 1)


    

    
Out[115]:





9.0

In [116]:

    

minkowski(rating1, rating2, 2)


    

    
Out[116]:





1.0

In [120]:

    

def euclidean(rating1, rating2):
    return minkowski(rating1, rating2, 2)


    

In [121]:

    

euclidean(rating1, rating2)


    

    
Out[121]:





1.0

In [ ]: