In [1]:

    

%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd


    

In [2]:

    

plt.style.use('ggplot')


    

In [3]:

    

print(plt.style.available)


    

    




[u'seaborn-darkgrid', u'seaborn-notebook', u'classic', u'seaborn-ticks', u'grayscale', u'bmh', u'seaborn-talk', u'dark_background', u'ggplot', u'fivethirtyeight', u'seaborn-colorblind', u'seaborn-deep', u'seaborn-whitegrid', u'seaborn-bright', u'seaborn-poster', u'seaborn-muted', u'seaborn-paper', u'seaborn-white', u'seaborn-pastel', u'seaborn-dark', u'seaborn-dark-palette']

In [4]:

    

# dataset from https://github.com/sidooms/MovieTweetings
cols = ['user id', 'movie id', 'rate', 'ts']
ratings = pd.read_csv('dataset/ratings.dat.txt', sep='::', 
                      index_col=False, names=cols, encoding='utf8')


    

    




/Users/kris/anaconda/lib/python2.7/site-packages/ipykernel/__main__.py:3: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.
  app.launch_new_instance()

In [5]:

    

ratings[:5]


    

    
Out[5]:






  

    

      

      
user id
      
movie id
      
rate
      
ts
    
  
  

    

      
0
      
1
      
68646
      
10
      
1381620027
    
    

      
1
      
1
      
113277
      
10
      
1379466669
    
    

      
2
      
2
      
422720
      
8
      
1412178746
    
    

      
3
      
2
      
454876
      
8
      
1394818630
    
    

      
4
      
2
      
790636
      
7
      
1389963947
    
  

In [6]:

    

ratings['rate'].value_counts()


    

    
Out[6]:





8     144125
7     133613
9      84679
6      77757
10     69018
5      42972
4      19212
3      10377
1       7138
2       6164
0        141
Name: rate, dtype: int64

In [7]:

    

ratings['rate'].value_counts().sort_index().plot(kind='bar')
plt.title('movie ratings')
plt.ylabel('counts')
plt.xlabel('rate')


    

    
Out[7]:





<matplotlib.text.Text at 0x11e08f090>






    

In [8]:

    

movies = pd.read_csv('dataset/movies.dat.txt', sep='::', 
                     index_col=False, names=['movie id', 'name', 'genre'], 
                     encoding='utf8')
movies[:5]


    

    




/Users/kris/anaconda/lib/python2.7/site-packages/ipykernel/__main__.py:3: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.
  app.launch_new_instance()






    
Out[8]:






  

    

      

      
movie id
      
name
      
genre
    
  
  

    

      
0
      
8
      
Edison Kinetoscopic Record of a Sneeze (1894)
      
Documentary|Short
    
    

      
1
      
10
      
La sortie des usines Lumière (1895)
      
Documentary|Short
    
    

      
2
      
12
      
The Arrival of a Train (1896)
      
Documentary|Short
    
    

      
3
      
25
      
The Oxford and Cambridge University Boat Race ...
      
NaN
    
    

      
4
      
91
      
Le manoir du diable (1896)
      
Short|Horror
    
  

In [9]:

    

drama = movies[movies['genre'] =='Crime|Drama']
drama[:5]


    

    
Out[9]:






  

    

      

      
movie id
      
name
      
genre
    
  
  

    

      
15
      
2844
      
Fantômas - À l'ombre de la guillotine (1913)
      
Crime|Drama
    
    

      
215
      
20859
      
Escape! (1930)
      
Crime|Drama
    
    

      
229
      
21406
      
Sono yo no tsuma (1930)
      
Crime|Drama
    
    

      
261
      
22286
      
The Public Enemy (1931)
      
Crime|Drama
    
    

      
264
      
22403
      
Smart Money (1931)
      
Crime|Drama
    
  

In [10]:

    

dramaIds = drama['movie id']
criterion = ratings['movie id'].map(lambda x: (dramaIds==x).any())
dramaRates = ratings[criterion]
dramaRates[:5]


    

    
Out[10]:






  

    

      

      
user id
      
movie id
      
rate
      
ts
    
  
  

    

      
0
      
1
      
68646
      
10
      
1381620027
    
    

      
50
      
15
      
68646
      
10
      
1486459236
    
    

      
51
      
15
      
71562
      
10
      
1486459311
    
    

      
52
      
15
      
99674
      
9
      
1486459399
    
    

      
104
      
27
      
111161
      
10
      
1405022004
    
  

In [11]:

    

dramaRates['rate'].value_counts().sort_index().plot(kind='bar')
plt.title('drama rating')
plt.xlabel('rate')
plt.ylabel('count')


    

    
Out[11]:





<matplotlib.text.Text at 0x11e024790>






    

In [14]:

    

ratings.shape, movies.shape


    

    
Out[14]:





((595196, 4), (27565, 3))

In [ ]: