Welcome to my Makeover Monday Challenge repository! Here, you will find a collection of engaging and insightful visualizations created as a part of my participation in the Makeover Monday Challenge. The Makeover Monday Challenge is a fantastic initiative that provides a platform to explore, analyze, and visualize diverse datasets, ultimately enhancing data visualization skills.
Makeover Monday is a weekly social data project that involves the visualization of datasets. Every week, a new dataset is shared, and participants are encouraged to reimagine and redesign the visual representation of the data. This collaborative effort not only helps participants improve their data visualization skills but also fosters a sense of community among data enthusiasts.
Here is a link to their website: MakeOverMonday
This repository is organized to provide easy navigation and access to the visualizations created during the Makeover Monday Challenge. Here's a brief overview of the repository structure:
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Week_X_Title: This directory contains the visualizations and relevant files for the specific week's challenge. Each week is appropriately labelled for quick reference.
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Images: Explore this directory to view snapshots and high-resolution images of the visualizations. These images capture the essence of the data transformations and insights gained during the Makeover Monday Challenge.
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Data: Find the original datasets as well as an augmented dataset for each challenge in this directory. It's essential to have access to the raw data to understand the context and perform your analyses.
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Scripts: If applicable, this directory may contain any custom scripts or code snippets used during the data visualization process.
Feel free to navigate through the repository and explore the visualizations for each week. If you have Tableau installed, you can download the Tableau workbooks (.twb) and interact with the visualizations directly. The associated images provide a quick preview of the insights derived from the data.
Tableau Public Link: Visualizations
I welcome contributions and feedback from the community. If you have suggestions for improvement, alternative visualizations, or ideas for future challenges, please don't hesitate to create an issue or submit a pull request.
Let's continue transforming raw data into compelling stories!
Happy Exploring, Jazmine
© 2024 Jazmine Ngaji