EECS 298: Social Consequences of Computing

Lab 5

Task

For this lab, you will work with a dataset of product sales at a clothing store to report the average price of each product over different time periods. You will receive an introduction to the Tuple data structure and learn about *args and **kwargs. Finally, you will learn how to handle dates in Python.

lab5.py

First download the dataset you will use for this lab, sales.csv:

wget https://raw.githubusercontent.com/eecs298/eecs298.github.io/main/files/sales.csv

Next, create a file named lab5.py in the same folder as sales.csv. In this file, first import csv and datetime using the following code. The from keyword is used to import a specific function from a package, both named datetime in this case.

import csv
from datetime import datetime

There are three types of products in sales.csv: "t-shirt", "jeans", and "sweaters" and each line in the csv represents a sale of one of the products and the corresponding date and price of the purchase. When you read in the data, you will create a dictionary where each key is one of the products and the value is a list of purchases associated with that product. The purchases will be stored as tuples in the format of (date, price) where date is a string in the format of YYYY-MM-DD and price is a float.

You will implement one function get_average_price(start_date: str, end_date: str, product_list: list[tuple]) that you will use to calculate the average price for a list of products in the __main__ branch.

Submit lab5.py to Gradescope when you’re done.

Tips

Tuples

tuples are a powerful datatype akin to a more efficient list, with the difference being that tuples are immutable and hashable. Since tuples are hashable, they, unlike lists, can be used as keys to a dictionary. Read more about tuples here.

To create a Tuple:

my_tuple = (123, "ABC")
my_tuple_2 = ("Hello", "World", 298, True)
my_tuple[0] # 123
# Tuples are immutable, so you cannot change its values or
# add values once created, e.g. my_tuple[0] = 456 does not work

*args and **kwargs

The *args and **kwargs operators can be used to unpack lists and dicts, respectively, and are typically used to define functions with variable length inputs and pass values into functions. See the examples below.

# Using *args and **kwargs to define variable length input functions
def variable_length_args_function(*args):
for arg in args: # args is a list of values
# Do stuff with args
def variable_length_kwargs_function(**kwargs):
for key,value in kwargs.items(): # kwargs is a dictionary of key/values
# Do stuff with key,values
# Using *args and **kwargs to pass values into functions of a defined length
def my_func(input1: str, input2: int, input3: bool):
print(input1, input2, input3)
message = ["EECS",298,True]
my_func(*message) # prints out: EECS 298 True
message = {"input1": "EECS", "input2":298, "input3":True}
my_func(**message) # prints out: EECS 298 True

datetime.strptime Function

datetime is a package that has functions related to handling dates in python. The datetime.strptime(date_string, format) function takes as input a date given as a string and the format of the date (e.g., YYYY-MM-DD and you can find all the format codes here) and outputs the date as a datetime object such that you can make meaningful comparisons to other datetime objects.

from datetime import datetime
date1_string = "2023-12-01"
date2_string = "2024-01-15"
date3_string = "2024-02-16"
date1 = datetime.strptime(date1_string, format="%Y-%m-%d")
date2 = datetime.strptime(date2_string, format="%Y-%m-%d")
date3 = datetime.strptime(date3_string, format="%Y-%m-%d")
print(date1 <= date2) # True
print(date3 - date2) # datetime.timedelta(days=32)