Project Description & Submission Guidelines

Project Overview

This project is an individual project and involves cleaning a dataset and creating visualizations using Python. You will select a dataset from Kaggle.com or another reputable source, download it, and use it as the foundation for your project.

The primary objective of this assignment is to enhance your skills in data cleaning and visualization using Python. Through this process, you will gain hands-on experience in handling real-world datasets, identifying and resolving data inconsistencies, and effectively presenting insights through visualizations.

Minimum Requirements for Submission

To successfully complete this project, you must submit the following:

1. Project Summary Document (13 paragraphs)
   • Provide a clear and concise summary of your data selection, cleaning process, and visualization techniques.
   • Start by mentioning the name and description of the dataset you chose.
   • Highlight challenges encountered (e.g., missing values, data inconsistencies) and explain how you resolved them.
   • Summarize the visualization techniques used and how they contribute to understanding the data.
2. Google Colab Notebook
   • Submit a link to your Google Colab notebook, ensuring that it is accessible.
   • Include clear and detailed comments (# comments) within your code to explain your thought process and methodologies.
3. CSV Files
   • Upload all CSV files that are used within your code.
   • Ensure that the original dataset (as downloaded) and any cleaned versions are included.
4. Project Explanation Video (57 minutes)
   • Record a 57 minute video explaining your project.
   • Walk through your dataset, data cleaning process, key challenges, and visualizations.
   • Provide a brief code walkthrough, highlighting important parts of your notebook.

Presentation Requirements

• No in-class presentation is required for this project.

Submission Instructions

1. Organize your project files in a single folder labeled as:
   MIS315_YourLastName_YourFirstName_Project1
2. Include all necessary components:
   • Google Colab Notebook (with comments)
   • CSV files (original & processed data)
   • Project Summary Document
   • Visualization Images (if applicable)
   • 57 minute project explanation video
3. Compress the folder into a ZIP file.
4. Upload the zipped folder to Canvas under the designated project submission section.

IMPORTANT NOTE:

• Ensure your folder is named correctly before compressing it.
• Submissions that do not follow the correct naming format will NOT be graded.

This project is an opportunity to demonstrate your ability to clean, analyze, and visualize data effectively using Python. Be sure to follow all submission guidelines carefully to receive full credit.

1,000 Points Possible

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