'Using cosine_similarity function on Python to make Recommender System

I'm trying to make recommendation system by rating's of music type. Contend based recommendation system.


import numpy as np
import pandas as pd
from sklearn.metrics.pairwise import cosine_similarity

a = [[3],[8],[0],[0],[11]]
b = [[1],[1],[0],[0],[1]]]
ap = pd.DataFrame(a, index=['Sonata','Etudes','Waltzes','Nocturnes','Marches'],columns=['ratings'])
bp = pd.DataFrame(b, index=['Sonata','Etudes','Waltzes','Nocturnes','Marches'],columns=['watched movie?'])

and this code's result returns

Input user ratings

Movies Matrix

But if i use cosine_similarity function like ->

from sklearn.metrics.pairwise import cosine_similarity
pd.DataFrame(cosine_similarity(a, b),columns=['A','B','c','d','e'], index=['Sonata','Etudes','Waltzes','Nocturnes','Marches'])

(the reason i added B c d e column is , error says i need 5 columns and 5 indexes.) this code returns

I want only result of cosine_similarity function of A table and B table 's rating but result can only show on 5x5 table and there is only 0 or 1 value.

My expected result was like this ==>>>