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Apply some pep8 rules to the code. fix #3. #4

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64 changes: 48 additions & 16 deletions ch2/filteringdata.py
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Original file line number Diff line number Diff line change
Expand Up @@ -8,31 +8,58 @@

from math import sqrt

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}
}

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
}
}


def manhattan(rating1, rating2):
"""Computes the Manhattan distance. Both rating1 and rating2 are dictionaries
of the form {'The Strokes': 3.0, 'Slightly Stoopid': 2.5}"""
distance = 0
commonRatings = False
commonRatings = False
for key in rating1:
if key in rating2:
distance += abs(rating1[key] - rating2[key])
commonRatings = True
if commonRatings:
return distance
else:
return -1 #Indicates no ratings in common
return -1 # Indicates no ratings in common


def computeNearestNeighbor(username, users):
Expand All @@ -46,6 +73,7 @@ def computeNearestNeighbor(username, users):
distances.sort()
return distances


def recommend(username, users):
"""Give list of recommendations"""
# first find nearest neighbor
Expand All @@ -56,12 +84,16 @@ def recommend(username, users):
neighborRatings = users[nearest]
userRatings = users[username]
for artist in neighborRatings:
if not artist in userRatings:
if artist not in userRatings:
recommendations.append((artist, neighborRatings[artist]))
# using the fn sorted for variety - sort is more efficient
return sorted(recommendations, key=lambda artistTuple: artistTuple[1], reverse = True)
return sorted(
recommendations,
key=lambda artistTuple: artistTuple[1],
reverse=True
)

# examples - uncomment to run

print( recommend('Hailey', users))
#print( recommend('Chan', users))
print(recommend('Hailey', users))
# print( recommend('Chan', users))
68 changes: 51 additions & 17 deletions ch2/filteringdataPearson.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -8,16 +8,43 @@

from math import sqrt

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}
}

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
}
}


def manhattan(rating1, rating2):
Expand All @@ -32,8 +59,7 @@ def manhattan(rating1, rating2):
if total > 0:
return distance / total
else:
return -1 #Indicates no ratings in common

return -1 # Indicates no ratings in common


def pearson(rating1, rating2):
Expand All @@ -54,12 +80,16 @@ def pearson(rating1, rating2):
sum_x2 += pow(x, 2)
sum_y2 += pow(y, 2)
# now compute denominator
denominator = sqrt(sum_x2 - pow(sum_x, 2) / n) * sqrt(sum_y2 - pow(sum_y, 2) / n)
denominator = (
sqrt(sum_x2 - pow(sum_x, 2) / n) *
sqrt(sum_y2 - pow(sum_y, 2) / n)
)

if denominator == 0:
return 0
else:
return (sum_xy - (sum_x * sum_y) / n) / denominator


def computeNearestNeighbor(username, users):
"""creates a sorted list of users based on their distance to username"""
Expand All @@ -72,6 +102,7 @@ def computeNearestNeighbor(username, users):
distances.sort()
return distances


def recommend(username, users):
"""Give list of recommendations"""
# first find nearest neighbor
Expand All @@ -82,8 +113,11 @@ def recommend(username, users):
neighborRatings = users[nearest]
userRatings = users[username]
for artist in neighborRatings:
if not artist in userRatings:
if artist not in userRatings:
recommendations.append((artist, neighborRatings[artist]))
# using the fn sorted for variety - sort is more efficient
return sorted(recommendations, key=lambda artistTuple: artistTuple[1], reverse = True)

return sorted(
recommendations,
key=lambda artistTuple: artistTuple[1],
reverse=True
)
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