Icke-personaliserade förslag
Bygga rekommendationsmotorer i Python
Robert O'Callaghan
Director of Data
Identifiera par
0 User_223 The Great Gatsby <---| Read by the same user
1 User_223 The Catcher in the Rye <---|
2 User_131 The Lord of the Rings
3 User_965 Little Women <---| Read by the same user
4 User_965 Fifty Shades of Grey <---|
... ...
Permutationer jämfört med kombinationer
| User | book_title |
|---|---|
| User_233 | The Great Gatsby |
| User_233 | The Catcher in the Rye |
Till:
| Book A | Book B | |
|---|---|---|
| 0 | The Great Gatsby | The Catcher in the Rye |
| 1 | The Catcher in the Rye | The Great Gatsby |
Böcker sedda med The Great Gatsby -> The Catcher in the Rye
Böcker sedda med The Catcher in the Rye -> The Great Gatsby
Skapa parningsfunktionen
from itertools import permutations
def create_pairs(x):
return pairs
Skapa parningsfunktionen
from itertools import permutations
def create_pairs(x):
pairs = permutations(x.values, 2)
return pairs
permutations(list, length_of_permutations))Genererar ett iterbart objekt med alla permutationer
Skapa parningsfunktionen
from itertools import permutations
def create_pairs(x):
pairs = list(permutations(x.values, 2))
return pairs
permutations(list, length_of_permutations))Genererar ett iterbart objekt med alla permutationerlist()Konverterar objektet till en användbar lista
Skapa parningsfunktionen
from itertools import permutations
def create_pairs(x):
pairs = pd.DataFrame(list(permutations(x.values, 2)),
columns=['book_a','book_b'])
return pairs
permutations(list, length_of_permutations))Genererar ett iterbart objekt med alla permutationerlist()Konverterar objektet till en användbar listapd.DataFrame()Konverterar listan till en DataFrame med kolumnernabook_aochbook_b
Tillämpa funktionen på data
book_pairs = book_df.groupby('userId')['book_title'].apply(perm_function)
print(book_pairs.head())
book_a book_b
userId
User_223 0 The Great Gatsby The Catcher in the Rye
1 The Catcher in the Rye The Great Gatsby
User_965 0 Little Women 40 Shades of Grey
1 40 Shades of Grey Little Women
User_773 0 The Twilight Saga Harry Potter and the Sorcerer's Stone
...
Städa upp resultaten
book_pairs = book_pairs.reset_index(drop=True)
print(book_pairs.head())
book_a book_b
0 The Great Gatsby The Catcher in the Rye
1 The Catcher in the Rye The Great Gatsby
3 Little Women 40 Shades of Grey
4 40 Shades of Grey Little Women
5 The Twilight Saga Harry Potter and the Sorcerer's Stone
...
Räkna paren
pair_counts = book_pairs.groupby(['book_a', 'book_b']).size()
book_a book_b
The Twilight Saga Fifty Shades of Grey 16
Pride and Prejudice 12
...
pair_counts_df = pair_counts.to_frame(name = 'size').reset_index()
print(pair_counts_df.head())
book_a book_b size
1 The Twilight Saga Fifty Shades of Grey 16
2 The Twilight Saga Pride and Prejudice 12
...
Slå upp rekommendationer
pair_counts_sorted = pair_counts_df.sort_values('size', ascending=False)
pair_counts_sorted[pair_counts_sorted['book_a'] == 'Lord of the Rings']
book_a book_b size
137 Lord of the Rings The Hobbit 12
147 Lord of the Rings Harry Potter and the Sorcerer's Stone 10
143 Lord of the Rings The Colour of Magic 9
...
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Bygga rekommendationsmotorer i Python
