/python-collections-budget

In this project we’ll process spending data into different types of Python collections. Then we’ll use those collections to graph our spending categories and budget outcomes.

Primary LanguagePython

Setup

  1. Install python

    Install python3 per your OS instructions.

  2. Setup a virtual environment with venv

    Create the venv: python -m venv venv

    Activate the venv: source venv/bin/activate

  3. Install requirements

    Run the following command to install the project’s required libraries:

    python -m pip install -r requirements.txt

Module 1

Count Purchases by Category

Verify module:

To run tests run: pytest -k "module1" -s
To run the file: python -m budget.UsingCounter

  1. Import the Expense Module

    Last month’s spending data is in data/spending_data.csv, which is a spreadsheet with 3 columns for - Location, Category, and amount. For example, the first row contains: Alaska Air,Travel,-$115.75. We want to analyze our spending habits in a few different ways. In this module, we are going to read in this file and display the categories with the most purchases in a graph.

    To read in the data, we’ll use the classes in the file named Expense.py. There are 2 classes -- Expense (which has a vendor, category, and amount) and Expenses (which has a list of type Expense and a sum of the amounts). Expenses also has a method read_expenses() which we’ll use to read the .csv file.

    To start, open the file named FrequentExpenses.py in the budget directory, and add import Expense to the top of the file.

  2. Read in the Spending Data

    Create a variable named expenses and set it equal to calling the Expenses() constructor. Then call the read_expenses() method on expenses and pass in the name of the file data/spending_data.csv.

  3. Create a List of the Spending Categories

    Create an empty list called spendingCategories. Then, create a for loop that iterates each Expense in the expenses. Inside the loop, we want to append() expense.category to spendingCategories.

  4. Count Categories with a Counter Collection

    In order to use the Counter Collection, import collections at the top of the file. Then after the for loop, create a new variable called spendingCounter and set equal to passing spendingCategories to the collections.Counter() constructor.

    If you printed the Counter with print(spendingCategories), you would see the following output: Counter({'Eating Out': 8, 'Subscriptions': 6, 'Groceries': 5, 'Auto and Gas': 5, 'Charity': 2, 'Gear and Clothing': 2, 'Phone': 2, 'Travel': 1, 'Classes': 1, 'Freelance': 1, 'Stuff': 1, 'Mortgage': 1, 'Paycheck': 1, 'Home Improvements': 1, 'Parking': 1, 'Utilities': 1})

    You can see it shows the category as the key and the number of times it was used as the value. With ‘Eating Out` as the most common expense which was done 8 times.

  5. Get the Top 5 Categories

    We can get only the top 5 most common categories by calling the most_common() method on spendingCounter and passing in the value 5. Set the result equal to a variable called top5.

  6. Convert the Dictionary to 2 Lists

    If you’ve used the zip() function before it combines 2 iterables (for example, combines two lists into a list of tuples). We can also use zip(*dictionary_variable) to separate the keys and values of a dictionary into separate lists. Since we want to have 2 separate lists for the categories and their counts for the bar graph, let’s call zip(*top5) and set the result equal to two variables - categories, count.

  7. Plot the Top 5 Most Common Categories

    Add import matplotlib.pyplot as plt to the top of the file. Then at the end of the file, call fig,ax=plt.subplots() to initialize fig as the Figure, or top level container for our graph. And ax as the Axes, which contains the actual figure elements.

  8. Create the bar chart

    Next, call ax.bar() with the categories and count lists as parameters. To add a title, call ax.set_title() and pass in the string '# of Purchases by Category'.

  9. Display the graph

    Finally, to display the graph, call plt.show().

    The resulting graph should be displayed:

Module 2

Create the BudgetList class to Display Overage Expenses

Verify module:

To run tests run: pytest -k "module2" -s
To run the file: python -m budget.BudgetList

  1. Create the BudgetList class

    In the budget directory, open the BudgetList.py file. Inside that file, create a class called BudgetList with only pass inside the class for now.

  2. Create the constructor

    Replace pass with a constructor that has two parameters - self, budget. Then initialize the following class variables:

    • self.budget to the passed-in budget
    • self.sum_expenses to 0
    • self.expenses to an empty list
    • self.sum_overages to 0
    • self.overages to an empty list

  3. Define the append method

    Define an append method that has two parameters - self and item. Put pass inside the method for now.

  4. Add items to expenses that are under budget

Replace pass with an if statement that checks if self.sum_expenses plus the passed-in item is less than self.budget. Inside the if block, call append() on self.expenses and pass in item. Also inside the if block, add item to self.sum_expenses.

  1. Add items to overages that are over budget

After the if block, add an else block that calls append() on self.overages and passes in item. Also, increase self.sum_overages by item.

  1. Define the len method

    Define a method called __len__ that takes in self as a parameter. Inside the method, return the sum of the length of self.expenses and the length of self.overages.

  2. Define the main function

    After the BudgetList class, define a main() function. Inside of main(), create a myBudgetList variable and assign it to calling the BudgetList constructor with a budget argument of 1200.

  3. Import the Expense module

    Before we can use the Expense class to read in spending data, import Expense at the top of BudgetList.py

  4. Read in the spending data file

    Next, create a variable named expenses and set it equal to calling the Expense.Expenses() constructor. On the next line, call the read_expenses() method on expenses and pass in the name of the file data/spending_data.csv. For this to work, we also need to import Expense at the top of the file.

  5. Add the expenses to the BudgetList

    After reading the expenses, create a for loop that has an iterator called expense and loops through expenses.list. Inside the for loop, call append(), with expense.amount as an argument, on myBudgetList.

  6. Print the Length of myBudgetList

    Call print() to print out the string 'The count of all expenses: ' concatenated with the length of myBudgList inside the print() call. Hint: Call the len() function with myBudgetList as an argument, then wrap that in a call to str() to convert to a string.

  7. Tell Python to run the main function

    After the main function, create an if statement that checks if __name__ is equal to "__main__". If so, call main().

    Now we can test that append() and len() are working for our BudgetList. Run python BudgetList.py and the output should be "The count of all expenses: 37".

Module 3

Finish Making BudgetList an Iterable

Verify module:

To run tests run: pytest -k "module3" -s
To run the file: python -m budget.BudgetList

  1. Create iter()

    Next, we want to create an iterator for BudgetList by implementing iter() and next() to iterate the expenses list first and then continue iterating the overages list. Once those are implemented and you can get an iterator from BudgetList, it will be an iterable. Inside the BudgetList class, at the bottom, define an iter method that has self as a parameter. Put pass inside the body of the method for now.

  2. Finish iter()

    Inside __iter__(), remove pass and replace it with setting self.iter_e to calling the iter() constructor with self.expenses as an argument. On the next line, set self.iter_o to calling the iter() constructor with self.overages as an argument. Finally to finish the method, return self.

  3. Create next()

    After the iter method, define the method next() with self as a parameter. Put pass inside the body of the method for now.

  4. Finish next()

    Inside __next__(), remove pass and replace it with a try: block. Inside the try: block, return a call to __next__() on self.iter__e. On the next line add an except block, StopIteration as stop as the exception. Inside the except block, return a call to __next__() on self.iter__o.

  5. Test the iterable

    We can now test that BudgetList works as an iterable by using it in a for loop. In main(), after the print statement, create a for loop that has an iterator called entry and loops through myBudgetList. Inside the for loop, call print() with entry as an argument.

    If we run python BudgetList.py, the output should be "The count of all expenses: 37" followed by each of the 37 amounts.

  6. Import Matplotlib

    Now we want to show a bar graph comparing the expenses, overages, and budget totals. First, we need to add import matplotlib.pyplot as plt to the top of the file after import Expense.

  7. Create the figure and axes

    Then at the end of main(), call fig,ax=plt.subplots() to initialize fig as the Figure, or top level container for our graph. And ax as the Axes, which contains the actual figure elements.

  8. Create the list of labels

    Create a variable called labels and set it equal to a list with the following values: 'Expenses', 'Overages', 'Budget'.

  9. Create the list of values

    Create a variable called values and set it equal to a list with the following properties from myBudgetList: sum_expenses, sum_overages, and budget.

  10. Create the bar graph

    Next, call ax.bar() with the labels and values lists as parameters.

  11. Set the title

    To add a title, call ax.set_title() and pass in the string 'Your total expenses vs. total budget'.

  12. Show the figure

    Finally, to display the graph, call plt.show().