3

I have dataframe of genres

df = pd.DataFrame({'genres': [['Drama'], ['Music', 'Drama', 'Romance'],
                               ['Action', 'Adventure', 'Comedy'],
                               ['Thriller', 'Romance', 'Drama'],
                               ['Adventure', 'Family']]
                    })
print(df)
genres = ['Action', 'Adventure', 'Comedy', 'Drama', 'Family', 'Music', 'Romance', 'Thriller']  # list of all genres

data:

                        genres
0                      [Drama]
1      [Music, Drama, Romance]
2  [Action, Adventure, Comedy]
3   [Thriller, Romance, Drama]
4          [Adventure, Family]

i want to have output like:

                        genres  Action  Adventure  Comedy  Drama  Family  \
0                      [Drama]       0          0       0      1       0   
1      [Music, Drama, Romance]       0          0       0      1       0   
2  [Action, Adventure, Comedy]       1          1       1      0       0   
3   [Thriller, Romance, Drama]       0          0       0      1       0   
4          [Adventure, Family]       0          1       0      0       1   

   Music  Romance  Thriller  
0      0        0         0  
1      1        1         0  
2      0        0         0  
3      0        1         1  
4      0        0         0
Improve this question

1 Answer 1

Reset to default
6

Use MultiLabelBinarizer:

from sklearn.preprocessing import MultiLabelBinarizer

mlb = MultiLabelBinarizer()

df1 = pd.DataFrame(mlb.fit_transform(df['genres']),columns=mlb.classes_, index=df.index)
df = df.join(df1)
print (df)
                        genres  Action  Adventure  Comedy  Drama  Family  \
0                      [Drama]       0          0       0      1       0   
1      [Music, Drama, Romance]       0          0       0      1       0   
2  [Action, Adventure, Comedy]       1          1       1      0       0   
3   [Thriller, Romance, Drama]       0          0       0      1       0   
4          [Adventure, Family]       0          1       0      0       1   

   Music  Romance  Thriller  
0      0        0         0  
1      1        1         0  
2      0        0         0  
3      0        1         1  
4      0        0         0

If want filter genres by lists add reindex:

genres = ['Action', 'Adventure', 'Comedy', 'Drama']

df1 = pd.DataFrame(mlb.fit_transform(df['genres']),columns=mlb.classes_, index=df.index)
df = df.join(df1.reindex(columns=genres, fill_value=0))
print (df)
                        genres  Action  Adventure  Comedy  Drama
0                      [Drama]       0          0       0      1
1      [Music, Drama, Romance]       0          0       0      1
2  [Action, Adventure, Comedy]       1          1       1      0
3   [Thriller, Romance, Drama]       0          0       0      1
4          [Adventure, Family]       0          1       0      0
Improve this answer
Sign up to request clarification or add additional context in comments.

1 Comment

all i can say is: perfaction

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service and acknowledge you have read our privacy policy.

Start asking to get answers

Find the answer to your question by asking.

Ask question

Explore related questions

See similar questions with these tags.