def occurences(selection):
    if selection == 'Motorbike':
           return np.random.choice([1, 2], p = [0.9, 0.1])
    elif selection == 'Car':
           return np.random.choice([2, 3, 4], p = [0.35, 0.6, 0.05])
    elif selection == 'Bus':
           return np.random.choice([3, 4, 5], p = [0.05, 0.9, 0.05])

def readings(vehicle_type):
    repetition = occurences(vehicle_type)
    vehicle_type_list = repetition*[vehicle_type]
    if vehicle_type == 'Motorbike':
        readings_list = list(np.random.normal(0.5, 0.2, repetition))
    elif vehicle_type == 'Car':
        readings_list = list(np.random.normal(5.5, 0.3, repetition))
    elif vehicle_type == 'Bus':
        readings_list = list(np.random.normal(3.5, 0.4, repetition))
    sample = pd.DataFrame({'vehicle_type':vehicle_type_list,
                         'amp_reading':readings_list})
    return sample

for count in range(1,301):
    choice = np.random.choice(['Motorbike','Car','Bus'], p=[0.333,0.333,0.334])
    if choice == 'Motorbike':
        new_df = new_df.append(readings(choice))
    elif choice == 'Car':
        new_df = new_df.append(readings(choice))
    elif choice == 'Bus':
        new_df = new_df.append(readings(choice))