Recommendation System - Based on User Ratings
Recommendation Based on User Ratings¶
In [1]:
#import all necessary libraries
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline
from sklearn.cross_validation import train_test_split
C:\Users\nwerner\AppData\Local\Continuum\Anaconda2\lib\site-packages\sklearn\cross_validation.py:44: DeprecationWarning: This module was deprecated in version 0.18 in favor of the model_selection module into which all the refactored classes and functions are moved. Also note that the interface of the new CV iterators are different from that of this module. This module will be removed in 0.20. "This module will be removed in 0.20.", DeprecationWarning)
In [2]:
ratings = pd.read_csv('u.data',header=None,sep='\t') #'\t' = separate on the slash and then tab
ratings.head()
Out[2]:
| 0 | 1 | 2 | 3 | |
|---|---|---|---|---|
| 0 | 0 | 50 | 5 | 881250949 |
| 1 | 0 | 172 | 5 | 881250949 |
| 2 | 0 | 133 | 1 | 881250949 |
| 3 | 196 | 242 | 3 | 881250949 |
| 4 | 186 | 302 | 3 | 891717742 |
In [3]:
r_cols = ['user_id','movie_id','rating']
ratings = pd.read_csv('u.data',sep='\t',names=r_cols,usecols=range(3))
print ratings.head()
m_cols=['movie_id','title']
movies = pd.read_csv('u.item',sep='|',names=m_cols,usecols=range(2))
print movies.head()
user_id movie_id rating 0 0 50 5 1 0 172 5 2 0 133 1 3 196 242 3 4 186 302 3 movie_id title 0 1 Toy Story (1995) 1 2 GoldenEye (1995) 2 3 Four Rooms (1995) 3 4 Get Shorty (1995) 4 5 Copycat (1995)
In [7]:
# Merging the dataframes
df = pd.merge(ratings,movies,on='movie_id')
df.head()
#df['movie_id'].unique()
Out[7]:
| user_id | movie_id | rating | title | |
|---|---|---|---|---|
| 0 | 0 | 50 | 5 | Star Wars (1977) |
| 1 | 290 | 50 | 5 | Star Wars (1977) |
| 2 | 79 | 50 | 4 | Star Wars (1977) |
| 3 | 2 | 50 | 5 | Star Wars (1977) |
| 4 | 8 | 50 | 5 | Star Wars (1977) |
In [8]:
userRatings = df.pivot_table(index=['user_id'],columns=['title'],values='rating')
userRatings.head()
Out[8]:
| title | 'Til There Was You (1997) | 1-900 (1994) | 101 Dalmatians (1996) | 12 Angry Men (1957) | 187 (1997) | 2 Days in the Valley (1996) | 20,000 Leagues Under the Sea (1954) | 2001: A Space Odyssey (1968) | 3 Ninjas: High Noon At Mega Mountain (1998) | 39 Steps, The (1935) | ... | Yankee Zulu (1994) | Year of the Horse (1997) | You So Crazy (1994) | Young Frankenstein (1974) | Young Guns (1988) | Young Guns II (1990) | Young Poisoner's Handbook, The (1995) | Zeus and Roxanne (1997) | unknown | � k�ldum klaka (Cold Fever) (1994) |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| user_id | |||||||||||||||||||||
| 0 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| 1 | NaN | NaN | 2.0 | 5.0 | NaN | NaN | 3.0 | 4.0 | NaN | NaN | ... | NaN | NaN | NaN | 5.0 | 3.0 | NaN | NaN | NaN | 4.0 | NaN |
| 2 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 1.0 | NaN | ... | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| 3 | NaN | NaN | NaN | NaN | 2.0 | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| 4 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
5 rows × 1664 columns
In [9]:
corrMatrix = userRatings.corr()
corrMatrix.head()
Out[9]:
| title | 'Til There Was You (1997) | 1-900 (1994) | 101 Dalmatians (1996) | 12 Angry Men (1957) | 187 (1997) | 2 Days in the Valley (1996) | 20,000 Leagues Under the Sea (1954) | 2001: A Space Odyssey (1968) | 3 Ninjas: High Noon At Mega Mountain (1998) | 39 Steps, The (1935) | ... | Yankee Zulu (1994) | Year of the Horse (1997) | You So Crazy (1994) | Young Frankenstein (1974) | Young Guns (1988) | Young Guns II (1990) | Young Poisoner's Handbook, The (1995) | Zeus and Roxanne (1997) | unknown | � k�ldum klaka (Cold Fever) (1994) |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| title | |||||||||||||||||||||
| 'Til There Was You (1997) | 1.0 | NaN | -1.000000 | -0.500000 | -0.500000 | 0.522233 | NaN | -0.426401 | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| 1-900 (1994) | NaN | 1.0 | NaN | NaN | NaN | NaN | NaN | -0.981981 | NaN | NaN | ... | NaN | NaN | NaN | -0.944911 | NaN | NaN | NaN | NaN | NaN | NaN |
| 101 Dalmatians (1996) | -1.0 | NaN | 1.000000 | -0.049890 | 0.269191 | 0.048973 | 0.266928 | -0.043407 | NaN | 0.111111 | ... | NaN | -1.000000 | NaN | 0.158840 | 0.119234 | 0.680414 | 0.000000 | 0.707107 | NaN | NaN |
| 12 Angry Men (1957) | -0.5 | NaN | -0.049890 | 1.000000 | 0.666667 | 0.256625 | 0.274772 | 0.178848 | NaN | 0.457176 | ... | NaN | NaN | NaN | 0.096546 | 0.068944 | -0.361961 | 0.144338 | 1.000000 | 1.0 | NaN |
| 187 (1997) | -0.5 | NaN | 0.269191 | 0.666667 | 1.000000 | 0.596644 | NaN | -0.554700 | NaN | 1.000000 | ... | NaN | 0.866025 | NaN | 0.455233 | -0.500000 | 0.500000 | 0.475327 | NaN | NaN | NaN |
5 rows × 1664 columns
In [10]:
userRatings[['12 Angry Men (1957)',"'Til There Was You (1997)"]].corr()
Out[10]:
| title | 12 Angry Men (1957) | 'Til There Was You (1997) |
|---|---|---|
| title | ||
| 12 Angry Men (1957) | 1.0 | -0.5 |
| 'Til There Was You (1997) | -0.5 | 1.0 |
In [12]:
corrMatrix = userRatings.corr(method='pearson',min_periods=100) #pearson correlation used for continuous variables
corrMatrix.head(10)
Out[12]:
| title | 'Til There Was You (1997) | 1-900 (1994) | 101 Dalmatians (1996) | 12 Angry Men (1957) | 187 (1997) | 2 Days in the Valley (1996) | 20,000 Leagues Under the Sea (1954) | 2001: A Space Odyssey (1968) | 3 Ninjas: High Noon At Mega Mountain (1998) | 39 Steps, The (1935) | ... | Yankee Zulu (1994) | Year of the Horse (1997) | You So Crazy (1994) | Young Frankenstein (1974) | Young Guns (1988) | Young Guns II (1990) | Young Poisoner's Handbook, The (1995) | Zeus and Roxanne (1997) | unknown | � k�ldum klaka (Cold Fever) (1994) |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| title | |||||||||||||||||||||
| 'Til There Was You (1997) | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| 1-900 (1994) | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| 101 Dalmatians (1996) | NaN | NaN | 1.0 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| 12 Angry Men (1957) | NaN | NaN | NaN | 1.0 | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| 187 (1997) | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| 2 Days in the Valley (1996) | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| 20,000 Leagues Under the Sea (1954) | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| 2001: A Space Odyssey (1968) | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 1.0 | NaN | NaN | ... | NaN | NaN | NaN | -0.001307 | NaN | NaN | NaN | NaN | NaN | NaN |
| 3 Ninjas: High Noon At Mega Mountain (1998) | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| 39 Steps, The (1935) | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
10 rows × 1664 columns
In [14]:
userRatings.loc[0] #1st user
Out[14]:
title
'Til There Was You (1997) NaN
1-900 (1994) NaN
101 Dalmatians (1996) NaN
12 Angry Men (1957) NaN
187 (1997) NaN
2 Days in the Valley (1996) NaN
20,000 Leagues Under the Sea (1954) NaN
2001: A Space Odyssey (1968) NaN
3 Ninjas: High Noon At Mega Mountain (1998) NaN
39 Steps, The (1935) NaN
8 1/2 (1963) NaN
8 Heads in a Duffel Bag (1997) NaN
8 Seconds (1994) NaN
A Chef in Love (1996) NaN
Above the Rim (1994) NaN
Absolute Power (1997) NaN
Abyss, The (1989) NaN
Ace Ventura: Pet Detective (1994) NaN
Ace Ventura: When Nature Calls (1995) NaN
Across the Sea of Time (1995) NaN
Addams Family Values (1993) NaN
Addicted to Love (1997) NaN
Addiction, The (1995) NaN
Adventures of Pinocchio, The (1996) NaN
Adventures of Priscilla, Queen of the Desert, The (1994) NaN
Adventures of Robin Hood, The (1938) NaN
Affair to Remember, An (1957) NaN
African Queen, The (1951) NaN
Afterglow (1997) NaN
Age of Innocence, The (1993) NaN
..
Window to Paris (1994) NaN
Wings of Courage (1995) NaN
Wings of Desire (1987) NaN
Wings of the Dove, The (1997) NaN
Winnie the Pooh and the Blustery Day (1968) NaN
Winter Guest, The (1997) NaN
Wishmaster (1997) NaN
With Honors (1994) NaN
Withnail and I (1987) NaN
Witness (1985) NaN
Wizard of Oz, The (1939) NaN
Wolf (1994) NaN
Woman in Question, The (1950) NaN
Women, The (1939) NaN
Wonderful, Horrible Life of Leni Riefenstahl, The (1993) NaN
Wonderland (1997) NaN
Wooden Man's Bride, The (Wu Kui) (1994) NaN
World of Apu, The (Apur Sansar) (1959) NaN
Wrong Trousers, The (1993) NaN
Wyatt Earp (1994) NaN
Yankee Zulu (1994) NaN
Year of the Horse (1997) NaN
You So Crazy (1994) NaN
Young Frankenstein (1974) NaN
Young Guns (1988) NaN
Young Guns II (1990) NaN
Young Poisoner's Handbook, The (1995) NaN
Zeus and Roxanne (1997) NaN
unknown NaN
� k�ldum klaka (Cold Fever) (1994) NaN
Name: 0, Length: 1664, dtype: float64In [15]:
myRatings = userRatings.loc[0].dropna()
myRatings
Out[15]:
title Empire Strikes Back, The (1980) 5.0 Gone with the Wind (1939) 1.0 Star Wars (1977) 5.0 Name: 0, dtype: float64
In [16]:
myRatings.index
Out[16]:
Index([u'Empire Strikes Back, The (1980)', u'Gone with the Wind (1939)',
u'Star Wars (1977)'],
dtype='object', name=u'title')In [21]:
myRatings.values
Out[21]:
array([ 5., 1., 5.])
In [22]:
simCandidates = pd.Series()
for i in range(0,len(myRatings.index)):
print "Adding sims for "+ myRatings.index[i] +'...'
# Retrieve similar movies to this one that I rated
sims = corrMatrix[myRatings.index[i]].dropna()
print sims
# Now scale its similarity by how well I rated this movie
sims = sims.map(lambda x: x*myRatings[i])
# Add the score to the list of similarity candidates
simCandidates = simCandidates.append(sims)
# Glance at our results so far:
print simCandidates.head(20)
Adding sims for Empire Strikes Back, The (1980)...
title
2001: A Space Odyssey (1968) 0.141598
Abyss, The (1989) 0.277867
African Queen, The (1951) 0.231657
Air Force One (1997) 0.165620
Aladdin (1992) 0.311063
Alien (1979) 0.201669
Aliens (1986) 0.292577
Amadeus (1984) 0.149328
American President, The (1995) 0.213057
Annie Hall (1977) -0.002235
Apocalypse Now (1979) 0.084026
Apollo 13 (1995) 0.196901
Babe (1995) 0.109333
Back to the Future (1985) 0.345285
Batman (1989) 0.300169
Batman Forever (1995) 0.112007
Batman Returns (1992) 0.133523
Beauty and the Beast (1991) 0.157386
Ben-Hur (1959) 0.210589
Birdcage, The (1996) 0.092188
Birds, The (1963) 0.067393
Blade Runner (1982) 0.193791
Blues Brothers, The (1980) 0.219766
Boot, Das (1981) 0.164315
Bram Stoker's Dracula (1992) 0.142719
Braveheart (1995) 0.257074
Brazil (1985) -0.089110
Bridge on the River Kwai, The (1957) 0.356743
Broken Arrow (1996) 0.193709
Butch Cassidy and the Sundance Kid (1969) 0.244651
...
Star Trek: Generations (1994) 0.302635
Star Trek: The Motion Picture (1979) 0.180343
Star Trek: The Wrath of Khan (1982) 0.311410
Star Wars (1977) 0.748353
Stargate (1994) 0.100042
Sting, The (1973) 0.274387
Taxi Driver (1976) 0.115306
Terminator 2: Judgment Day (1991) 0.333532
Terminator, The (1984) 0.280766
This Is Spinal Tap (1984) -0.046499
Time to Kill, A (1996) 0.019384
Tin Cup (1996) 0.205358
Titanic (1997) 0.184539
To Kill a Mockingbird (1962) 0.097268
Top Gun (1986) 0.162103
Toy Story (1995) 0.232355
Trainspotting (1996) 0.051306
True Lies (1994) 0.246698
Truth About Cats & Dogs, The (1996) 0.095777
Twelve Monkeys (1995) 0.115975
Twister (1996) -0.010236
Under Siege (1992) 0.139255
Unforgiven (1992) 0.144706
Usual Suspects, The (1995) 0.208092
Vertigo (1958) 0.140744
When Harry Met Sally... (1989) 0.154222
While You Were Sleeping (1995) 0.266557
Willy Wonka and the Chocolate Factory (1971) 0.191770
Wizard of Oz, The (1939) 0.287675
Young Frankenstein (1974) 0.185887
Name: Empire Strikes Back, The (1980), Length: 197, dtype: float64
Adding sims for Gone with the Wind (1939)...
title
2001: A Space Odyssey (1968) 0.004890
Alien (1979) -0.057730
Aliens (1986) 0.056156
Amadeus (1984) 0.323631
Apollo 13 (1995) 0.030318
Back to the Future (1985) 0.257319
Blade Runner (1982) 0.048333
Blues Brothers, The (1980) 0.124627
Braveheart (1995) 0.121169
Casablanca (1942) 0.291137
Dances with Wolves (1990) 0.140462
Dead Poets Society (1989) 0.139189
E.T. the Extra-Terrestrial (1982) 0.361463
Empire Strikes Back, The (1980) 0.135687
Fargo (1996) 0.124841
Field of Dreams (1989) 0.153802
Fish Called Wanda, A (1988) -0.006385
Forrest Gump (1994) 0.095262
Fugitive, The (1993) -0.017365
Godfather, The (1972) 0.065994
Gone with the Wind (1939) 1.000000
Graduate, The (1967) 0.326215
Groundhog Day (1993) 0.079423
Independence Day (ID4) (1996) 0.180982
Indiana Jones and the Last Crusade (1989) 0.171311
It's a Wonderful Life (1946) 0.305688
Jaws (1975) 0.133886
Jurassic Park (1993) 0.138319
Lion King, The (1994) 0.185623
M*A*S*H (1970) 0.313956
Mary Poppins (1964) 0.244310
Monty Python and the Holy Grail (1974) 0.180938
One Flew Over the Cuckoo's Nest (1975) 0.072976
Princess Bride, The (1987) -0.012742
Psycho (1960) 0.193419
Pulp Fiction (1994) 0.034826
Raiders of the Lost Ark (1981) 0.145818
Raising Arizona (1987) -0.160481
Return of the Jedi (1983) 0.209247
Schindler's List (1993) 0.344765
Silence of the Lambs, The (1991) 0.032078
Sound of Music, The (1965) 0.244235
Star Wars (1977) 0.129207
Sting, The (1973) 0.120216
Terminator 2: Judgment Day (1991) 0.133215
Terminator, The (1984) 0.066005
Toy Story (1995) 0.199741
When Harry Met Sally... (1989) 0.197863
Willy Wonka and the Chocolate Factory (1971) 0.053934
Wizard of Oz, The (1939) 0.430219
Name: Gone with the Wind (1939), dtype: float64
Adding sims for Star Wars (1977)...
title
12 Angry Men (1957) 0.184289
2001: A Space Odyssey (1968) 0.230884
Absolute Power (1997) 0.085440
Abyss, The (1989) 0.203709
African Queen, The (1951) 0.230540
Air Force One (1997) 0.113164
Aladdin (1992) 0.191621
Alien (1979) 0.248991
Aliens (1986) 0.254444
Amadeus (1984) 0.190280
American President, The (1995) 0.113189
Annie Hall (1977) -0.100120
Apocalypse Now (1979) 0.028576
Apollo 13 (1995) 0.222006
Army of Darkness (1993) 0.103842
Austin Powers: International Man of Mystery (1997) 0.377433
Babe (1995) 0.184512
Back to the Future (1985) 0.274839
Batman (1989) 0.289344
Batman Forever (1995) 0.113667
Batman Returns (1992) 0.059691
Beauty and the Beast (1991) 0.106199
Beavis and Butt-head Do America (1996) 0.132943
Ben-Hur (1959) 0.043553
Big Night (1996) 0.152359
Birdcage, The (1996) 0.060544
Birds, The (1963) 0.083739
Blade Runner (1982) 0.196715
Blues Brothers, The (1980) 0.192560
Bonnie and Clyde (1967) 0.084781
...
Swingers (1996) 0.289310
Taxi Driver (1976) 0.029863
Terminator 2: Judgment Day (1991) 0.207599
Terminator, The (1984) 0.262255
That Thing You Do! (1996) 0.190198
This Is Spinal Tap (1984) -0.080796
Time to Kill, A (1996) -0.042790
Tin Cup (1996) 0.117280
Titanic (1997) 0.081928
To Kill a Mockingbird (1962) 0.129012
Tomorrow Never Dies (1997) 0.255210
Top Gun (1986) 0.174815
Toy Story (1995) 0.180020
Trainspotting (1996) 0.021504
True Lies (1994) 0.198306
Truth About Cats & Dogs, The (1996) 0.145821
Twelve Monkeys (1995) 0.155530
Twister (1996) 0.038232
Under Siege (1992) 0.026704
Unforgiven (1992) 0.055059
Usual Suspects, The (1995) 0.211075
Vertigo (1958) 0.080635
Volcano (1997) 0.045947
What's Eating Gilbert Grape (1993) -0.060495
When Harry Met Sally... (1989) 0.119849
While You Were Sleeping (1995) 0.156119
Willy Wonka and the Chocolate Factory (1971) 0.221902
Wizard of Oz, The (1939) 0.266335
Wrong Trousers, The (1993) 0.216204
Young Frankenstein (1974) 0.192589
Name: Star Wars (1977), Length: 268, dtype: float64
2001: A Space Odyssey (1968) 0.707991
Abyss, The (1989) 1.389334
African Queen, The (1951) 1.158286
Air Force One (1997) 0.828101
Aladdin (1992) 1.555313
Alien (1979) 1.008343
Aliens (1986) 1.462883
Amadeus (1984) 0.746641
American President, The (1995) 1.065284
Annie Hall (1977) -0.011175
Apocalypse Now (1979) 0.420130
Apollo 13 (1995) 0.984504
Babe (1995) 0.546663
Back to the Future (1985) 1.726427
Batman (1989) 1.500844
Batman Forever (1995) 0.560036
Batman Returns (1992) 0.667613
Beauty and the Beast (1991) 0.786928
Ben-Hur (1959) 1.052943
Birdcage, The (1996) 0.460942
dtype: float64
In [23]:
print 'sorting...'
simCandidates.sort_values(inplace=True,ascending=False)
print simCandidates.head(20)
sorting... Empire Strikes Back, The (1980) 5.000000 Star Wars (1977) 5.000000 Empire Strikes Back, The (1980) 3.741763 Star Wars (1977) 3.741763 Return of the Jedi (1983) 3.606146 Return of the Jedi (1983) 3.362779 Raiders of the Lost Ark (1981) 2.693297 Raiders of the Lost Ark (1981) 2.680586 Austin Powers: International Man of Mystery (1997) 1.887164 Sting, The (1973) 1.837692 Bridge on the River Kwai, The (1957) 1.783717 Indiana Jones and the Last Crusade (1989) 1.750535 Cinderella (1950) 1.749598 Back to the Future (1985) 1.726427 Terminator 2: Judgment Day (1991) 1.667662 Frighteners, The (1996) 1.663647 Field of Dreams (1989) 1.642076 Chasing Amy (1997) 1.633938 L.A. Confidential (1997) 1.595323 Dumbo (1941) 1.588281 dtype: float64
In [24]:
simCandidates.index
Out[24]:
Index([u'Empire Strikes Back, The (1980)', u'Star Wars (1977)',
u'Empire Strikes Back, The (1980)', u'Star Wars (1977)',
u'Return of the Jedi (1983)', u'Return of the Jedi (1983)',
u'Raiders of the Lost Ark (1981)', u'Raiders of the Lost Ark (1981)',
u'Austin Powers: International Man of Mystery (1997)',
u'Sting, The (1973)',
...
u'Courage Under Fire (1996)', u'What's Eating Gilbert Grape (1993)',
u'Murder at 1600 (1997)', u'This Is Spinal Tap (1984)',
u'Brazil (1985)', u'Real Genius (1985)', u'Annie Hall (1977)',
u'Remains of the Day, The (1993)', u'Piano, The (1993)',
u'First Wives Club, The (1996)'],
dtype='object', length=515)In [25]:
simCandidates = simCandidates.groupby(simCandidates.index).sum()
simCandidates
Out[25]:
12 Angry Men (1957) 0.921447
2001: A Space Odyssey (1968) 1.867302
Absolute Power (1997) 0.427199
Abyss, The (1989) 2.407877
African Queen, The (1951) 2.310987
Air Force One (1997) 1.393921
Aladdin (1992) 2.513417
Alien (1979) 2.195566
Aliens (1986) 2.791258
Amadeus (1984) 2.021675
American President, The (1995) 1.631229
Annie Hall (1977) -0.511775
Apocalypse Now (1979) 0.563009
Apollo 13 (1995) 2.124853
Army of Darkness (1993) 0.519211
Austin Powers: International Man of Mystery (1997) 1.887164
Babe (1995) 1.469222
Back to the Future (1985) 3.357941
Batman (1989) 2.947566
Batman Forever (1995) 1.128369
Batman Returns (1992) 0.966069
Beauty and the Beast (1991) 1.317924
Beavis and Butt-head Do America (1996) 0.664713
Ben-Hur (1959) 1.270708
Big Night (1996) 0.761795
Birdcage, The (1996) 0.763660
Birds, The (1963) 0.755656
Blade Runner (1982) 2.000863
Blues Brothers, The (1980) 2.186257
Bonnie and Clyde (1967) 0.423907
...
Swingers (1996) 1.446551
Taxi Driver (1976) 0.725845
Terminator 2: Judgment Day (1991) 2.838871
Terminator, The (1984) 2.781109
That Thing You Do! (1996) 0.950990
This Is Spinal Tap (1984) -0.636474
Time to Kill, A (1996) -0.117032
Tin Cup (1996) 1.613187
Titanic (1997) 1.332340
To Kill a Mockingbird (1962) 1.131400
Tomorrow Never Dies (1997) 1.276052
Top Gun (1986) 1.684591
Toy Story (1995) 2.261614
Trainspotting (1996) 0.364047
True Lies (1994) 2.225018
Truth About Cats & Dogs, The (1996) 1.207991
Twelve Monkeys (1995) 1.357525
Twister (1996) 0.139979
Under Siege (1992) 0.829797
Unforgiven (1992) 0.998825
Usual Suspects, The (1995) 2.095832
Vertigo (1958) 1.106896
Volcano (1997) 0.229737
What's Eating Gilbert Grape (1993) -0.302473
When Harry Met Sally... (1989) 1.568219
While You Were Sleeping (1995) 2.113377
Willy Wonka and the Chocolate Factory (1971) 2.122292
Wizard of Oz, The (1939) 3.200268
Wrong Trousers, The (1993) 1.081020
Young Frankenstein (1974) 1.892380
Length: 268, dtype: float64In [26]:
simCandidates.sort_values(inplace=True,ascending=False)
simCandidates.head(10)
Out[26]:
Empire Strikes Back, The (1980) 8.877450 Star Wars (1977) 8.870971 Return of the Jedi (1983) 7.178172 Raiders of the Lost Ark (1981) 5.519700 Indiana Jones and the Last Crusade (1989) 3.488028 Bridge on the River Kwai, The (1957) 3.366616 Back to the Future (1985) 3.357941 Sting, The (1973) 3.329843 Cinderella (1950) 3.245412 Field of Dreams (1989) 3.222311 dtype: float64
In [27]:
# Dropping films the user has previously seen
filteredSims = simCandidates.drop(myRatings.index)
filteredSims.head(10)
Out[27]:
Return of the Jedi (1983) 7.178172 Raiders of the Lost Ark (1981) 5.519700 Indiana Jones and the Last Crusade (1989) 3.488028 Bridge on the River Kwai, The (1957) 3.366616 Back to the Future (1985) 3.357941 Sting, The (1973) 3.329843 Cinderella (1950) 3.245412 Field of Dreams (1989) 3.222311 Wizard of Oz, The (1939) 3.200268 Dumbo (1941) 2.981645 dtype: float64
In [ ]: