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In this lab, you'll harness the power of Google Colab, Python, and the versatile Pandas library to embark on a journey of data exploration. By delving into your dataset, you'll gain a profound understanding of its nuances, uncover hidden patterns, and extract valuable insights. This hands-on experience will empower you to unlock the full potential of your data, enabling informed decision-making and informed solutions through the art of data analysis and manipulation.
Welcome to Lab 1, where you'll work with three diverse datasets filled with valuable information waiting to be explored. Your mission is to dive deep into these datasets, uncovering their contents, structures, and the insights they hold. By developing a comprehensive understanding of the data they contain, you'll set the stage for meaningful analysis and well-informed decision-making, enhancing your data-driven journey.
📊 Dataset Information:
| No | Name | Dataset |
|---|---|---|
| 1. | Chipotle Sales |  |
| 2. | Occupation | |
| 3. | Open Food Facts | |
🖥️ Exercise Instructions: You will need to complete this exercise using Google Colab. There are four provided templates for this exercise:
| Lab | Dataset | Instruction |
|---|---|---|
| 1a. | Chipotle Sales |  |
| 1b. | Occupation | |
| 1c. | Open Food Facts | |
| 1d. | Chipotle Sales | |
🚀 Form project teams comprising a minimum of three and a maximum of four students. Teamwork is essential for this assignment. Please complete the Google Sheets page with your group information here. Please update your group information:
| No | Group | File |
|---|---|---|
| 0. | Sample |  |
| 1. | pergolakan🙀 | |
| 2. | Bunnies | |
| 4. | NewATG | |
| 5. | MA1 KTDI | |
| 6. | HANY | |
| 7. | KhuChin | |
| 8. | 3H | |
| 9. | ByteNav | |
| 10. | DEADPOOLv2 | |
| 11. | SEK KITO | |
| 12. | SYN | |
| 13. | 21ProMax | |
🚫 Uphold the highest standards of academic integrity. Any candidate suspected of cheating in the assignment will face disciplinary action, which may include suspension or expulsion from the University. Moreover, any materials or devices found to be in violation of examination rules and regulations will be confiscated.
📝 Prepare a comprehensive document that outlines the step-by-step process for creating the case study. This document should include details about the formulas used. Additionally, you must submit a Google Sheets file containing the results of the case study's execution.
The deadline for submission is 2 November, 2023, at 3:30 PM. Late submissions will not be accepted and will be disregarded.
You must place your file in the submission folder. Within the lab/submission folder, create a folder called your group. Name the default file as readme.md. You can refer to the documentation template here. Suggested folder structure for this project:
lab/your_group/
└── 📁 lab1/
├── 📄 readme.md
├── 📄 ans_lab1a.ipynb
├── 📄 ans_lab1b.ipynb
├── 📄 ans_lab1c.ipynb
└── 📄 ans_lab1d.ipynbPlease create an Issue for any improvements, suggestions or errors in the content.
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