-
Notifications
You must be signed in to change notification settings - Fork 1
/
popular_movies.py
71 lines (45 loc) · 2.25 KB
/
popular_movies.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
import numpy as np
import pandas as pd
#POPULAR MOVIES
d = {'movie_id': [98], 'movie_title': ['Silence of the Lambs'] }
df = pd.DataFrame(d)
df.to_csv('ml-100k/popular.data',mode='a' ,sep='\t',index=False, header=False)
d = {'movie_id': [64], 'movie_title':['Shawshank Redemption'] }
df = pd.DataFrame(d)
df.to_csv('ml-100k/popular.data',mode='a' ,sep='\t',index=False, header=False)
d = {'movie_id': [127], 'movie_title':['Godfather'] }
df = pd.DataFrame(d)
df.to_csv('ml-100k/popular.data',mode='a' ,sep='\t',index=False, header=False)
d = {'movie_id': [56], 'movie_title':['Pulp Fiction'] }
df = pd.DataFrame(d)
df.to_csv('ml-100k/popular.data',mode='a' ,sep='\t',index=False, header=False)
d = {'movie_id': [69], 'movie_title':['Forrest Gump'] }
df = pd.DataFrame(d)
df.to_csv('ml-100k/popular.data',mode='a' ,sep='\t',index=False, header=False)
d = {'movie_id': [318], 'movie_title':['The Shinder\'s List'] }
df = pd.DataFrame(d)
df.to_csv('ml-100k/popular.data',mode='a' ,sep='\t',index=False, header=False)
d = {'movie_id': [204], 'movie_title': ['Back to The Future']}
df = pd.DataFrame(d)
df.to_csv('ml-100k/popular.data',mode='a' ,sep='\t',index=False, header=False)
d = {'movie_id': [11], 'movie_title':['Se7en'] }
df = pd.DataFrame(d)
df.to_csv('ml-100k/popular.data',mode='a' ,sep='\t',index=False, header=False)
d = {'movie_id': [22], 'movie_title':['Braveheart'] }
df = pd.DataFrame(d)
df.to_csv('ml-100k/popular.data',mode='a' ,sep='\t',index=False, header=False)
d = {'movie_id': [144], 'movie_title':['Die Hard'] }
df = pd.DataFrame(d)
df.to_csv('ml-100k/popular.data',mode='a' ,sep='\t',index=False, header=False)
d = {'movie_id': [71], 'movie_title':['The Lion King'] }
df = pd.DataFrame(d)
df.to_csv('ml-100k/popular.data',mode='a' ,sep='\t',index=False, header=False)
d = {'movie_id': [200], 'movie_title':['The Shining'] }
df = pd.DataFrame(d)
df.to_csv('ml-100k/popular.data',mode='a' ,sep='\t',index=False, header=False)
d = {'movie_id': [178], 'movie_title':['12 Angry Men'] }
df = pd.DataFrame(d)
df.to_csv('ml-100k/popular.data',mode='a' ,sep='\t',index=False, header=False)
d = {'movie_id': [177], 'movie_title':['The Good, The Bad and the Ugly'] }
df = pd.DataFrame(d)
df.to_csv('ml-100k/popular.data',mode='a' ,sep='\t',index=False, header=False)