diff --git a/13/kaijuking/directors.py b/13/kaijuking/directors.py
new file mode 100644
index 000000000..09413cb5e
--- /dev/null
+++ b/13/kaijuking/directors.py
@@ -0,0 +1,103 @@
+import csv
+from collections import defaultdict, namedtuple
+from operator import attrgetter
+
+
+MOVIE_DATA = 'movie_metadata.csv'
+NUM_TOP_DIRECTORS = 20
+MIN_MOVIES = 4
+MIN_YEAR = 1960
+
+
+Movie = namedtuple('Movie', 'title year score')
+Director = namedtuple('Director', 'director average_score')
+movie_dd = defaultdict(list)
+
+
+def get_movies_by_director():
+    '''Extracts all movies from csv and stores them in a dictionary
+    where keys are directors, and values is a list of movies (named tuples)'''
+
+    with open(MOVIE_DATA, newline='', encoding="utf8") as csvfile:
+        csv_reader = csv.DictReader(csvfile, delimiter=',')
+
+        for row in csv_reader:
+
+            # Filter out any row whose 'title_year' meets or exceeds the minimum year
+            if row['title_year'] >= str(MIN_YEAR):
+                
+                # Construct the movie defaultdict
+                # key = director_name, value = Movie Tuple(title, year, score)
+                movie_dd[row['director_name']].append(Movie(row['movie_title'], row['title_year'], row['imdb_score']))
+        
+        
+    # Sort the list of namedtuples by score from highlest to lowest
+    for director in movie_dd:
+        movie_dd[director] = sorted(movie_dd[director], key=attrgetter('score'), reverse=True)
+
+    return movie_dd
+
+
+def get_average_scores(directors):
+    '''Filter directors with < MIN_MOVIES and calculate averge score'''
+
+    # Eventually will be a list of tuples like [('director', 'average_score')]
+    avg_scores = []
+
+    # Loop through the directors defaultdict and calculate the director's average movie score
+    for director, movies in directors.items():
+        if len(movies) >= MIN_MOVIES:
+            avg_scores.append((director, _calc_mean(movies)))
+            
+    # Found here: https://pythonguides.com/python-sort-list-of-tuples/
+    # Sort the averages list by the second element ('average_score') going from highest to lowest
+    avg_scores.sort(key=lambda y: y[1], reverse=True)
+
+    # Return only the first 20 items of the sorted list
+    # This shoud equate to the top 20 directors and their movie score averages
+    return avg_scores[0:NUM_TOP_DIRECTORS]
+
+
+def _calc_mean(movies):
+    '''Helper method to calculate mean of list of Movie namedtuples'''
+    total_score = 0
+    for movie in movies:
+        total_score += float(movie.score)
+    
+    # Round the division to return a float to one decimal point (ex: 8.5)
+    avg_score = round(total_score / len(movies), 1)
+    return avg_score
+
+
+def print_directors_and_averages(directors, averages):
+    counter = 1
+
+    # Loop through the list of tuple averages (ex: [('director', 'average_score')])
+    for d1, avg in averages:
+
+        # No need to sort as the averages tuple list is already sorted by average from highest to lowest
+        print('\n')
+        print(f'{counter:02d}. {d1:<52} {avg}')
+        print('-' * 60)
+
+        # Loop through the defaultdict of movies
+        for d2, movies in directors.items():
+
+            # Print the list of movies if the director is found in both
+            # Movies are printed in order as is since movie defaultdict is already sorted by 'score'
+            if d2 == d1:
+                for movie in movies:
+                    print(f'{movie.year}] {movie.title:<50} {movie.score}')
+        counter += 1
+
+
+def main():
+    directors = get_movies_by_director()
+    averages = get_average_scores(directors)
+    print_directors_and_averages(directors, averages)
+
+
+if __name__ == '__main__':
+    main()
+
+    
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