Merge pull request #9 from LaunchCodeEducation/a1

Assignment 1: Fintech Fun

content/assignments/_index.md

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 ## What is a Graded Assignment?
-Graded Assignments will count towards your final grade in the course. Each assignment is graded pass-fail. While [Assignment 0]({{% relref "./assignment0/_index.md" %}}) is more of a tutorial to get you used to submitting Google Sheets for grading, you need a passing grade on each assignment to complete the course. Each assignment builds on concepts introduced over multiple lessons, so we would like you to begin reviewing the assignment and working on the different tasks as soon as the assignment becomes available in Canvas.
+Graded Assignments will count towards your final grade in the course. Each assignment is graded pass-fail. While [Assignment 0]({{% relref "./assignment0/_index.md" %}}) is more of a tutorial to get you used to Google Sheets, you have to get a passing grade on each assignment in order for you to complete the course. Each assignment builds on concepts introduced over multiple lessons, so we encourage you to begin reviewing the assignment and working on the different tasks as soon as the assignment becomes available in Canvas.
 
 ## Content Links
 
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content/assignments/assignment1/_index.md

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+pre = "<b>A1: </b>"
+title = "Fintech Fun"
+date = 2023-05-25T12:55:09-05:00
+draft = false
+weight = 2
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+
+## Outline
+
+In this assignment, you are working for a fintech company looking to build a personal finance app to guide the average American consumer. You will be using the EDA and cleaning data skills you acquired with Google Sheets to grow the founders' understanding of various data sources before the app teams put together the underlying logic into the app.
+
+## Content Links
+
+{{% children %}}

content/assignments/assignment1/debt-warmup/_index.md

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+title = "Task 2: Tackling Debt"
+date = 2023-05-25T12:55:09-05:00
+draft = false
+weight = 2
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+
+The company knows that one thing that many Americans need is a way to track paying off credit card debt. They put together a hypothetical user profile and gathered data from a CPA on how this consumer could use two popular debt repayment methods to conquer their credit card debt. The hypothetical customer is named Mia and she has four different credit cards that she needs to pay off.
+
+| Credit Card Name | Starting Statement Balance | Interest Rate | Minimum Monthly Payment |
+|------------------|----------------------------|---------------|-------------------------|
+| Hotel Card | $1,250 | 20% | $50 |
+| Airline Card | $2,000 | 22% | $50 |
+| Bank Card 1 | $1,000 | 15% | $50 |
+| Bank Card 2 | $1,750 | 18% | $50 |
+
+The company wanted to put together a debt repayment plan for Mia under the following assumptions:
+
+1. Because she lives with her parents and they are covering some of her expenses, Mia can dedicate $1,000 out of her $2,500 a month salary to debt repayment.
+1. If any of her debt grows to over $10,000, Mia's parents are going to cover the majority of her expenses so she can put $2,000 a month towards repaying her credit card debt.
+
+This repayment plan for the hypothetical Mia is supposed to help the company put together an effective debt repayment portion of their app. However, they want you to run an EDA and clean the debt repayment plan so they can move forward with the app.
+
+The debt repayment workbook has a spreadsheet for the debt snowball method and the debt avalanche method. The debt snowball involves paying the minimum payment on each credit card and putting the extra of her allocated debt payment towards the debt with the smallest balance. Once that is paid off, she would do the same to the remaining credit card with the smallest balance and so on until she is done paying her debts. The debt avalanche method involves her paying the minimum payment on each credit card and putting the extra towards the credit card with the highest interest rate until that is paid off and then she moves on to the next highest interest rate.
+
+Making sure that you are working on your copy of the debt repayment workbook, perform an EDA and clean the data, answering the questions in the final report document.
+
+

content/assignments/assignment1/housing-prices/_index.md

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+title = "Task 3: Housing Prices"
+date = 2023-05-25T12:55:09-05:00
+draft = false
+weight = 3
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+
+In addition to providing info on tackling debt, the company wants to help customers navigate the housing market. The app company wants to provide more information on housing prices to help their customers decide when is the best time to buy. In order to do so, they need you to run an EDA and clean the data for this [dataset](https://www.kaggle.com/datasets/madhurpant/factors-affecting-usa-national-home-prices/data).
+
+Create a new workbook to store this dataset and select THREE out of the seven provided CSVs that you find the most interesting. You only have to perform EDA and clean the data for your chosen factors. Add each factor to a separate spreadsheet in your workbook. As you work, make sure to answer the questions in the final report document for each of your three chosen factors.
+

content/assignments/assignment1/project-intro/_index.md

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+title = "Task 1: The Business Issue"
+date = 2023-05-25T12:55:09-05:00
+draft = false
+weight = 1
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+
+You work for a company that is trying to create the ultimate app for the average American navigating financial issues and financial planning. While the company is led by some brilliant minds, trying to create the ultimate anything can be difficult and they are having a hard time digging through all the numbers to lay down the foundations of what the app should be. They have data related to a variety of different topics, however, due to various regulations on financial advising, they need to ensure that the data is accurate before pushing it out to app users.
+
+With a thousand different topics that can be encompassed within personal finance, the founders of this company want you to focus on performing an exploratory data analysis and cleaning two datasets that they believe the app should be built on. The first dataset is a debt repayment plan a financial advisor put together for a hypothetical app customer and the other one is a collection of historical data for different factors that may impact housing prices in the United States.
+
+To get started, open this [folder](https://drive.google.com/drive/folders/1LKqS5sHRRsqK8GZg5PC1yiaKUrINyjkl?copy) and copy both the spreadsheet and the final report document to your drive. You should fill out your personal copy of the final report document as you work on each dataset. You may also notice that so far, only one dataset is imported into a spreadsheet for you. You will need to create the second workbook by importing the data from Kaggle. Time to get started with your first dataset!
+

content/assignments/assignment1/project-submission/_index.md

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+title = "Task 4: Submitting Your Work"
+date = 2023-05-25T12:55:09-05:00
+draft = false
+weight = 4
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+
+Before you submit your work, make sure that you answered all the questions detailing your results in the report document.
+
+1. Create a folder named "A1 Fintech Fun" and add your name to the folder name. 
+1. Move your three items from this assignment to the folder. You can do so by clicking *File* > *Move* and selecting the folder you just created in the popup.
+1. Once you have your two Google Sheet workbooks and your final report document in the folder, you can share the whole folder by hovering your mouse to the right of the folder name in the list view and clicking the sharing icon. This icon looks like a person with a plus sign on it.
+1. Under the Access permissions, allow for people to comment and copy the link.
+1. Return the assignment page in Canvas and paste the link in the submission box.