n1 completed

Author: Valkryn

days/04-06-collections/challenge.py

@@ -17,12 +17,13 @@ def get_movies_by_director(data=movie_csv):
         for line in csv.DictReader(file):
             try:
                 director = line['director_name']
-                title = line['movie_title']
-                year = line['year']
+                title = line['movie_title'].replace('\xa0', '')
+                year = line['title_year']
                 score = line['imdb_score']
             except ValueError:
                 continue
             m = Movie(title=title, year=year, score=score)
+            print(m)
             directors[director].append(m)
 
 

days/07-09-data-structures/code/cars.py

@@ -0,0 +1,7 @@
+cars = {
+    'Ford': ['Falcon', 'Focus', 'Festiva', 'Fairlane'],
+    'Holden': ['Commodore', 'Captiva', 'Barina', 'Trailblazer'],
+    'Nissan': ['Maxima', 'Pulsar', '350Z', 'Navara'],
+    'Honda': ['Civic', 'Accord', 'Odyssey', 'Jazz'],
+    'Jeep': ['Grand Cherokee', 'Cherokee', 'Trailhawk', 'Trackhawk']
+}

days/07-09-data-structures/code/n1.py

@@ -0,0 +1,47 @@
+from cars import cars
+from collections import defaultdict
+
+
+def main():
+    print(get_all_jeeps(cars))
+    print(first_car(cars))
+    print(name_contains_str(cars))
+    sort_cars(cars)
+
+
+def get_all_jeeps(file):
+    jeeps = file['Jeep']
+    return jeeps
+
+
+def first_car(file):
+    f_cars = []
+    for manufacturer, car in file.items():
+        f_cars.append(car[0])
+    return f_cars
+
+
+def name_contains_str(file):
+    selected_cars = []
+    for cars in file.values():
+        for car in cars:
+            if 'Trail' in car:
+                selected_cars.append(car)
+    return selected_cars
+
+
+def sort_cars(file):
+    new_dict = defaultdict(list)
+    for maker, s_cars in file.items():
+        new_dict[maker] = sorted(s_cars)
+    print(new_dict)
+
+
+if __name__ == '__main__':
+    main()
+
+# challenges
+# Get all Jeeps
+# Get the first car of every manufacturer.
+# Get all vehicles containing the string Trail in their names (should work for other grep too)
+# Sort the models (values) alphabetically