Due on Oct 22, 2025, end of day
This assignment uses data from the Nata Supermarkets: Customer Analytics case. The dataset contains information about supermarket customers — including their demographics, spending habits across product categories, and how long they’ve been customers.
You will use Pandas to explore, clean, and summarize the data. We will focus on using Python and Pandas operations and some quick visualizations to extract meaningful insights.
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Read the case description (provided separately in the course outline). It introduces Nata Supermarkets’ business context and explains what each variable in the dataset represents.
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Open the Colab Notebook The notebook contains several guided questions (e.g., data inspection, cleaning, transformation, and summary).
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Answer each question directly in the notebook
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Use code cells for your Python code.
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Use short text cells (Markdown) to answer questions.
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Make sure to include your name and student number and save your colab notebook to Github.
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By completing this assignment to:
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Practice core Pandas operations.
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Learn how to inspect and transform real-world datasets.
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Develop skills to interpret numerical summaries into business insights.
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The customer dataset, download from Harvard Business Publishing
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assignment_notebook_1.ipynb— your Colab notebook with questions -
README.md — this instruction file
Submit to GitHub Classroom before the due date. Make sure all code cells run correctly and outputs are visible.