Welcome to the PreppinData-2023 repository! This repository contains my solutions to the weekly challenges of the Preppin' Data blog. Here, you will find detailed explanations, code snippets, and datasets that demonstrate how to solve the challenges effectively.
The following table presents the 2023 weekly challenges, along with an indication of whether I have successfully completed each one.
| Week | Challenge | Description | Solved |
|---|---|---|---|
| 1 | The Data Source Bank | ℹ️ | ✅ |
| 2 | International Bank Account Numbers | ℹ️ | ✅ |
| 3 | Targets for DSB | ℹ️ | ✅ |
| 4 | New Customers | ℹ️ | ✅ |
| 5 | DSB Ranking | ℹ️ | ✅ |
| 6 | DSB Customer Ratings | ℹ️ | ✅ |
| 7 | Flagging Fraudulent Suspicions | ℹ️ | ✅ |
| 8 | Taking Stock | ℹ️ | |
| 9 | Customer Bank Statements | ℹ️ | |
| 10 | What's my balance on this day? | ℹ️ | |
| 11 | Which customers Are closest? | ℹ️ | |
| 12 | Regulatory Reporting Alignment | ℹ️ | |
| 13 | Rolling stock price trends | ℹ️ | |
| 14 | World Trade Data | ℹ️ | |
| 15 | Easter Dates | ℹ️ | |
| 16 | Easter and Full Moons | ℹ️ | |
| 17 | Population Growth vs Country Size | ℹ️ | |
| 18 | The Nut House Revenue Analysis | ℹ️ | |
| 19 | Tableau Conference Special | ℹ️ | |
| 20 | Dining Hall Debacle | ℹ️ | |
| 21 | Prep School Grades | ℹ️ |
Preppin' Data is a blog and community-driven platform that offers weekly data preparation challenges. These challenges are designed to enhance your data manipulation and analysis skills using Tableau Prep, although these challenges can be solved using tools such as Excel, Alteryx, SQL, and Python. Each week, a new challenge is released, presenting a unique dataset and a set of requirements to accomplish.
In this repository, I will share my solutions to the PreppinData weekly challenges for the year 2023. Each challenge will have its own dedicated folder, containing the following components:
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Solution Files: The solution files will be provided in form of a Python Jupyter Notebook. These files will contain the code and steps to transform the given dataset and meet the specified requirements.
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Input Datasets: The input datasets used in each challenge will be provided in the
data/inputdirectory. -
Output Datasets: The output datasets generated after applying the transformations will be included in the
data/outputdirectory. These datasets will help you verify the correctness of the solution and compare your results with mine.
Contributions are welcome! If you have a different approach or solution to any of the challenges, feel free to reach out to me or to open a pull request with your changes. Additionally, if you notice any issues, errors, or have suggestions for improvements, please submit an issue.
The solutions provided in this repository are my personal interpretations of the PreppinData weekly challenges. They may not be the only correct way to solve the problems, but they aim to demonstrate efficient and effective approaches. I encourage you to experiment, adapt, and customize the solutions to suit your specific requirements.
I would like to express my gratitude to the Preppin' Data team for creating such engaging and educational challenges. Their continuous efforts to improve data preparation skills have been invaluable to the data community.
If you have any questions, feedback, or just want to connect, you can reach me through the following channels:
- GitHub: Josemvg
- LinkedIn: José Manuel Vega Gradit