user _ ratings _ matrix=training _ df.pivot (index=' userid ',columns='movieId ',values='rating ' )
users=user _ ratings _ matrix.index.values
print (' creatingcorateddataframe . ' )
withopen (similarities/userscorated.CSV ',' w ' ) as result_file:
打印(用户1、用户2、共享)、文件=result _ file () ) ) ) ) ) ) ) )。
打印(calculatingcoratedbetweenusers . ' )
forU1inTQDM(users,total=Len ) users ) ) :
for u2 in users:
movies _ u1=~NP.isnan (user _ ratings _ matrix.iloc (u1-1 ) ) )
movies _ U2=~NP.isnan (user _ ratings _ matrix.iloc (U2-1 ) ) )
ame _ movies=NP.logical _ and (movies _ u1,movies_u2 ) ) ) ) 652 )
num _ same _ movies=list (same _ movies ).count ) )。
print(f({U1}、{u2}、{num_same_movies} )、file=result_file () ) ) ) ) )。