Operands Could not be Broadcast with Shapes (19,)(0,)

I have googled and read something similar to the problem I have but I do not seem to know how to fix the error I got from this particular code:

import operator
def getNeighbors(movieID, K):
    distances = []
    for movie in movieDict:
        if (movie != movieID):
            dist = ComputeDistance(movieDict[movieID], movieDict[movie])
            distances.append((movie, dist))
    distances.sort(key=operator.itemgetter(1))
    neighbors = []
    for x in range(K):
        neighbors.append(distance[x][0])
    return neighbors

K = 10
avgRating = 0
neighbors = getNeighbors(1, K)

**ValueError:** operands could not be broadcast together with shapes (19,)(0,)

The full code:

import numpy as np
import pandas as pd
r_cols = ['user_id', 'movie_id', 'rating']
ratings = pd.read_csv('C:/Users/dell/Downloads/DataScience/DataScience-Python3/ml-100k/u.data', sep='\t', engine='python', names=r_cols, usecols=range(3))  # please enter your file path here. The file is u.data
print(ratings.head())   
movieProperties = ratings.groupby('movie_id').agg({'rating': [np.size, np.mean]})
print(movieProperties.head())

movieNumRatings = pd.DataFrame(movieProperties['rating']['size'])
movieNormalizedNumRatings = movieNumRatings.apply(lambda x: (x - np.min(x)) / (np.max(x) - np.min(x)))
print(movieNormalizedNumRatings.head())

movieDict = {}
with open('C:/Users/dell/Downloads/DataScience/DataScience-Python3/ml-100k/u.item') as f:     # The file is u.item
    temp = ''
    for line in f:
        fields = line.rstrip('\n').split('|')
        movieID = int(fields[0])
        name = fields[1]
        genres = fields[5:25]
        genres = map(int, genres)
        movieDict[movieID] = (name, genres, movieNormalizedNumRatings.loc[movieID].get('size'), movieProperties.loc[movieID].rating.get('mean'))

print(movieDict[1])

from scipy import spatial
def ComputeDistance(a, b):
    genresA = np.array(list(a[1]))
    genresB = np.array(list(b[1]))
    genreDistance = spatial.distance.cosine(genresA, genresB)
    popularityA = np.array(a[2])
    popularityB = np.array(b[2])
    popularityDistance = abs(popularityA - popularityB)
    return genreDistance + popularityDistance  

print(ComputeDistance(movieDict[2], movieDict[4])) 

import operator

def getNeighbors(movieID, K):
    distances = []
    for movie in movieDict:
        if (movie != movieID):
            dist = ComputeDistance(movieDict[movieID], movieDict[movie])
            distances.append((movie, dist))
    distances.sort(key=operator.itemgetter(1))
    neighbors = []
    for x in range(K):
        neighbors.append(distance[x][0])
    return neighbors

K = 10
avgRating = 0

neighbors = getNeighbors(1, K)
```