Week 8: In-Class

Week 8: In-Class#

Demo#

Demo 8.1: Phonebook Merge#

A phonebook is represented as a dictionary where each key corresponds to a contact’s name, and the corresponding value is a list of phone numbers associated with that contact. As an example, consider the two phonebooks given below:

phonebook = {'Liv': ['55511112', '18777890'] ,
              'Mads': ['27274445', '48533336'],
              'Steve': ['45455555', '25455525']}

second_phonebook = {'Anna': ['89577772'] ,
                     'Steve': ['25257755', '25455525'],
                     'Mads': ['48533336', '27274445']}

Given a second phonebook, we want to add its content to the first phonebook, but without creating duplicates. Specifically:

If a name from the second phonebook is not present in the first phonebook, it should be added to the first phonebook along with its associated phone numbers.
If a name from the second phonebook is already present in the first phonebook, then we look at the two lists of phone numbers for that name. Phone numbers that are only present in the second list should be added to the end of the first list in the order they occur in the second list.

Pen & Paper

Make a test for the function you are going to write. Using the two phonebooks above, write down what the expected value of phonebook should be after adding the second phonebook.

Demo

Write a function that takes two dictionaries representing phonebooks as input. The function should not have a return statement, but it should modify the first phonebook by adding the content from the second phonebook.

Coding Practice#

Code 8.2: Inventory Management#

Create a dictionary representing the inventory of a store, where each key of the dictionary is a string naming an item, for instance 'apples', and each value is the quantity of that item in the store.

inventory = {
    "apples": 10,
    "bananas": 5,
    "oranges": 8,
    "kiwis": 7
}

Write a function restock_inventory that takes as input a dictionary with the same structure as inventory and an integer representing how many units to add to each item. The function should increase the quantity of each item in the inventory by the given restock amount and then return the updated dictionary.

The expected output of restock_inventory is shown below:

>>> inventory = {
...     "apples": 10,
...     "bananas": 5,
...     "oranges": 8,
...     "kiwis": 7
... }
>>> restock_inventory(inventory, 3)
{'apples': 13, 'bananas': 8, 'oranges': 11, 'kiwis': 10}
>>> restock_inventory(inventory, 2)
{'apples': 15, 'bananas': 10, 'oranges': 13, 'kiwis': 12}
>>> restock_inventory(inventory, 1)
{'apples': 16, 'bananas': 11, 'oranges': 14, 'kiwis': 13}

Code 8.3: Weather Station#

Create a dictionary which represents a weather station. The dictionary should have 5 keys: "station_name", "is_operational", "city", "country" and "construction_year". You can see in the image below, the value of each key.

Now you should modify the dictionary by adding the key temperature_readings with the value [20.1, 21.3, 19.8, 22.0]. Add also the key wind_speed_readings with the value [5.2, 3.4, 7.1, 15.6].

Write a for-loop that prints all key-value pairs of the dictionary weather_station. Look at your output and confirm that the dictionary has the correct keys and values.

Now write a function get_average_readings which as an input takes a dictionary with the same structure as weather_station. The function should return a tuple with two values: the average of the wind speed readings and the average of the temperature readings. Test the function with the dictionary weather_station and print the results.

Code 8.4: Data Statistics#

Write a function data_statistics which given a list of experiment values and an experiment name returns a dictionary containing the following key-value pairs:

experiment_name: The name of the experiment.
experiment_values: The list of experiment values.
mean_val: The mean of the experiment values.
standard_deviation: The standard deviation of the experiment values.
max_val: The maximum of the experiment values.
min_val: The minimum of the experiment values.

The standard deviation \(\sigma\) of a sequence of values can be found using the formula below:

\[ \sigma=\sqrt{\frac{\sum\left(x_i-\mu\right)^2}{N}} \]

where \(x_{i}\) denotes value \(i\) in the sequence, \(\mu\) is the mean of the sequence and \(N\) is the length of the sequence.

To test your function, you can use the example data given below:

experiment_name = "standard_values"
experiment_values = [1.30, -0.01,  1.35,  0.31,  0.35, -1.61,  1.39,  1.19, -1.07,  0.34]

Problem Solving#

Problem 8.5: Energy Expenditure#

Energy expenditure is a measure of how many calories a body burns throughout a day. Total energy expenditure (TEE) can be calculated as

\[\mathrm{TEE} = \mathrm{BEE} \cdot \mathrm{AF}\]

where AF is the activity factor, and BEE is the basal energy expenditure covering essential functions like breathing, circulation, and digestion.

The BEE for males and females is

\[\mathrm{BEE}_\mathrm{male} = 66 + (13.7 \cdot \text{weight}) + (5.0 \cdot \text{height}) - (6.8 \cdot \text{age})\]

\[\mathrm{BEE}_\mathrm{female} = 655 + (9.6 \cdot \text{weight}) + (1.8 \cdot \text{height}) - (4.7 \cdot \text{age})\]

where weight, height and age are in kilograms, centimeters and years, respectively.

The activity factor AF is classified as:

Sedentary activity: \(\mathrm{AF} = 1.3\)
Moderate activity: \(\mathrm{AF} = 1.5\)
Strenuous activity: \(\mathrm{AF} = 2.0\)

Assume you are given data for three persons in the following form:

person_data = {
    "names": ["Jakob", "Josefine", "Morten"],
    "genders": ["Male", "Female", "Male"], 
    "ages": [25, 30, 37], 
    "weights": [70, 60, 86], 
    "heights": [175, 165, 189],
    "activity_levels": ["moderate", "strenuous", "sedentary"]
}

Here, the items in the first position of each list correspond to the weight, height and age of the first person, and so on.

Write a function calculate_bee_tee which meets the following specifications:


            calculate_bee_tee.py

calculate_bee_tee(person_data, name)

The basal energy expenditure (BEE) and total energy expenditure (TEE).

Parameters:

`person_data`	`dict`	Person data including age, gender, height and weight
`name`	`str`	The name of a person in `person_data`

Returns:

tuple

The BEE and TEE of the person with the corresponding name

The expected output of calculate_bee_tee is shown below:

>>> calculate_bee_tee(person_data, 'Jakob')
(1730.0, 2595.0)
>>> calculate_bee_tee(person_data, 'Josefine')
(1387.0, 2774.0)
>>> calculate_bee_tee(person_data, 'Morten')
(1937.6, 2518.88)

Problem 8.6: Player Scores#

You are in charge of making a leaderboard for DTU’s football club. You have devised a point scoring system to determine the performance of each player. The point scoring system is as follows:

Successful goals are worth 20 points each
Successful passes are worth 2 points each
Unsuccessful goal attempts are worth 5 points each
Unsuccessful pass attempts are worth 1 point each

Each player’s score is the sum of the points accumulated in the four categories.

Assume you are given the following set of player statistics containing number of goals, number of passes, number of goal attempts and number of pass attempts of all the players in the club. The attempts include both the successful and unsuccessful attempts.

player_stats = [
    {"name": "Bob", "goals": 2, "passes": 15, "goal_attempts": 3, "pass_attempts": 17},
    {"name": "Alex", "goals": 1, "passes": 17, "goal_attempts": 2, "pass_attempts": 20},
    {"name": "Molly", "goals": 1, "passes": 28, "goal_attempts": 2, "pass_attempts": 31},
    {"name": "Sophia", "goals": 2, "passes": 21, "goal_attempts": 3, "pass_attempts": 25}
]

Write a function get_highscore which meets the following specifications:


            get_highscore.py

get_highscore(player_stats)

Finds the player with the highest score from a set of player statistics.

Parameters:

player_stats

list

A set of player statistics including player name, number of goals, number of passes, number of goal attempts and number of pass attempts.

Returns:

tuple

The name of the highest scoring player and their player score.

The expected output of get_highscore is shown below:

>>> get_highscore(player_stats)
('Sophia', 91)

`social_network`	`dict`	A social network model.
`person_name`	`str`	The name of a person in `social_network`.