with open('notes.txt', 'w') as f:
    f.write('Data Analytics Zero to Hero\n')
    f.write('Video 5: Working with Files\n')
print('File written.')

with open('notes.txt', 'r') as f:
    contents = f.read()
print(contents)

with open('notes.txt', 'r') as f:
    for line in f:
        print(line.strip())

with open('notes.txt', 'a') as f:
    f.write('Appended line.\n')
with open('notes.txt', 'r') as f:
    print(f.read())

import csv

with open('mtcars.csv', 'r') as f:
    reader = csv.reader(f)
    header = next(reader)
    print(header)

with open('mtcars.csv', 'r') as f:
    reader = csv.reader(f)
    header = next(reader)
    rows = list(reader)
print(len(rows))
print(rows[0])

with open('mtcars.csv', 'r') as f:
    reader = csv.DictReader(f)
    cars = list(reader)
print(cars[0])
print(cars[0]['model'])
print(cars[0]['mpg'])

total_mpg = 0
for car in cars:
    total_mpg = total_mpg + float(car['mpg'])
average_mpg = total_mpg / len(cars)
print(f'Average MPG across all 32 cars: {average_mpg:.2f}')

efficient_cars = [car for car in cars if float(car['mpg']) > 25]
print(len(efficient_cars))

with open('efficient_cars.csv', 'w', newline='') as f:
    writer = csv.DictWriter(f, fieldnames=['model', 'mpg', 'cyl'])
    writer.writeheader()
    for car in efficient_cars:
        writer.writerow({'model': car['model'], 'mpg': car['mpg'], 'cyl': car['cyl']})
print('Saved efficient_cars.csv')

import json

top_3_efficient = sorted(efficient_cars, key=lambda c: float(c['mpg']), reverse=True)[:3]
with open('top_cars.json', 'w') as f:
    json.dump(top_3_efficient, f, indent=2)
print('Saved top_cars.json')

with open('top_cars.json', 'r') as f:
    loaded = json.load(f)
print(loaded)
print(type(loaded))

print(json.dumps({'model': 'Fiat 128', 'mpg': 32.4}))