Data visualization is a powerful tool for understanding complex datasets and conveying information to both technical and non-technical audiences. In this repository, you will find:
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Matplotlib Visualizations: Matplotlib is a versatile library for creating static, animated, and interactive visualizations. Explore a range of chart types, including line plots, bar charts, scatter plots, histograms, and more.
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Seaborn Visualizations: Seaborn is built on top of Matplotlib and offers a high-level interface for creating aesthetically pleasing statistical visualizations. Discover how to create informative pair plots, heatmaps, distribution plots, and more.
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Sample Datasets: We've included sample datasets that you can use to recreate the visualizations and practice your data visualization skills.
To get started with the visualizations in this repository:
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Clone the repository to your local machine using
git clone. -
Explore the Jupyter notebooks to see code examples and explanations for each visualization.
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Modify and adapt the code to your own datasets and analysis needs.
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Experiment with customizations, colors, and styles to create your own unique visualizations.
This project requires the following Python libraries:
- Matplotlib
- Seaborn
- Jupyter Notebook
You can install these dependencies using pip or conda:
pip install matplotlib seaborn