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README.md
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---
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<br/><br/>
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<p align="center">
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<picture>
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<source media="(prefers-color-scheme: dark)" srcset="https://raw.githubusercontent.com/mckinsey/vizro/main/.github/images/Vizro_Github_Banner_Dark_Mode.png">
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<source media="(prefers-color-scheme: light)" srcset="https://raw.githubusercontent.com/mckinsey/vizro/main/.github/images/Vizro_Github_Banner_Light_Mode.png">
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<img alt="Vizro logo" src="https://raw.githubusercontent.com/mckinsey/vizro/main/.github/images/Vizro_Github_Banner_Dark_Mode.png" width="250">
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</picture>
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</p>
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<br/><br/>
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<div align="center" markdown="1">
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[](https://pypi.org/project/vizro/)
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[](https://badge.fury.io/py/vizro)
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[](https://github.com/mckinsey/vizro/blob/main/LICENSE.md)
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[](https://vizro.readthedocs.io/)
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[](https://www.bestpractices.dev/projects/7858)
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</div>
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<div align="center" markdown="1">
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<a href="https://vizro.readthedocs.io/en/stable/" target="_blank">Documentation </a> |
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<a href="https://vizro.readthedocs.io/en/stable/pages/tutorials/first_dashboard/" target="_blank">Get Started </a> |
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<a href="http://vizro.mckinsey.com/" target="_blank">Live Demo </a>
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</div>
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---
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<p align="center">
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<img src="https://raw.githubusercontent.com/mckinsey/vizro/main/.github/images/example_screens.png" width="700"/>
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</p>
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<p align="center">
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<font size="+2">
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<b>
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Visual Intelligence. Beautifully Engineered
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</b>
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</font>
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</p>
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<p align="center">
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<font size="+1">
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Vizro is a toolkit for creating modular data visualization applications
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</font>
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</p>
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<p align="center">
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<img src="https://raw.githubusercontent.com/mckinsey/vizro/main/.github/images/tech_logos.png" width="300"/>
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</p>
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## What is Vizro?
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<p align="left">
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<font size="+1">
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Rapidly self-serve the assembly of customized dashboards in minutes - without the need for advanced coding or design experience - to create flexible and scalable, Python-enabled data visualization applications.
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</font>
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</p>
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<p align="center">
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<img src="https://raw.githubusercontent.com/mckinsey/vizro/main/.github/images/code_dashboard.png" width="1300"/>
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</p>
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Use a few lines of simple configuration to create complex dashboards, which are automatically assembled using libraries such as [**Plotly**](https://github.com/plotly/plotly.py) and [**Dash**](https://github.com/plotly/dash), with inbuilt coding and design best practices.
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Define high-level categories within the configuration, including:
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- **Components:** create charts, tables, input/output interfaces, and more.
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- **Controls**: create filters, parameter inputs, and custom action controllers.
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- **Pages, layouts and navigation**: create multiple pages, with customizable layouts and flexible navigation across them.
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- **Actions and interactions**: create interactions between charts, and use pre-defined or customized actions (such as exporting).
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Configuration can be written in multiple formats including **Pydantic models**, **JSON**, **YAML** or **Python dictionaries** for added flexibility of implementation.
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Optional high-code extensions enable almost infinite customization in a modular way, combining the best of low-code and high-code - for flexible and scalable, Python enabled data visualization applications.
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Visit ["Why should I use Vizro?"](https://vizro.readthedocs.io/en/stable/pages/explanation/faq/#why-should-i-use-vizro) for a more detailed explanation of Vizro use cases.
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