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Docs/introduce why vizro (#73)
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12 changes: 7 additions & 5 deletions README.md
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Expand Up @@ -55,26 +55,28 @@ Vizro is a toolkit for creating modular data visualization applications

<p align="left">
<font size="+1">
Rapidly self-serve the assembly of customised dashboards in minutes - without the need for advanced coding or design experience - to create flexible and scalable, Python enabled data visualization applications
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
</font>
</p>

<p align="center">
<img src="https://raw.githubusercontent.com/mckinsey/vizro/main/.github/images/code_dashboard.png" width="1300"/>
</p>

Use a few lines of simple configuration to create complex dashboards, which are automatically assembled utilising libraries such as [**Plotly**](https://github.com/plotly/plotly.py) and [**Dash**](https://github.com/plotly/dash), with inbuilt coding and design best practices
Use a few lines of simple configuration to create complex dashboards, which are automatically assembled utilizing libraries such as [**Plotly**](https://github.com/plotly/plotly.py) and [**Dash**](https://github.com/plotly/dash), with inbuilt coding and design best practices

Define high level categories within the configuration, including:

- **components:** create charts, tables, input/output interfaces, and more
- **controls**: create filters, parameter inputs, and custom action controllers
- **pages, layouts and navigation**: create multiple pages, with customisable layouts and flexible navigation across them
- **actions and interactions**: create interactions between charts, and use pre-defined or customised actions (such as exporting)
- **pages, layouts and navigation**: create multiple pages, with customizable layouts and flexible navigation across them
- **actions and interactions**: create interactions between charts, and use pre-defined or customized actions (such as exporting)

Configuration can be written in multiple formats including **Pydantic models**, **JSON**, **YAML** or **Python dictionaries** for added flexibility of implementation

Optional high-code extensions allow almost infinite customisation in a modular way, combining the best of low-code and high-code - for flexible and scalable, Python enabled data visualization applications
Optional high-code extensions allow 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

(Visit the ["Why Vizro"](https://vizro.readthedocs.io/en/latest/pages/explanation/why_vizro/) section to see a more detailed explanation of Vizro use cases)

<br/>

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12 changes: 7 additions & 5 deletions vizro-core/README.md
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Expand Up @@ -55,26 +55,28 @@ Vizro is a toolkit for creating modular data visualization applications

<p align="left">
<font size="+1">
Rapidly self-serve the assembly of customised dashboards in minutes - without the need for advanced coding or design experience - to create flexible and scalable, Python enabled data visualization applications
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
</font>
</p>

<p align="center">
<img src="https://raw.githubusercontent.com/mckinsey/vizro/main/.github/images/code_dashboard.png" width="1300"/>
</p>

Use a few lines of simple configuration to create complex dashboards, which are automatically assembled utilising libraries such as [**Plotly**](https://github.com/plotly/plotly.py) and [**Dash**](https://github.com/plotly/dash), with inbuilt coding and design best practices
Use a few lines of simple configuration to create complex dashboards, which are automatically assembled utilizing libraries such as [**Plotly**](https://github.com/plotly/plotly.py) and [**Dash**](https://github.com/plotly/dash), with inbuilt coding and design best practices

Define high level categories within the configuration, including:

- **components:** create charts, tables, input/output interfaces, and more
- **controls**: create filters, parameter inputs, and custom action controllers
- **pages, layouts and navigation**: create multiple pages, with customisable layouts and flexible navigation across them
- **actions and interactions**: create interactions between charts, and use pre-defined or customised actions (such as exporting)
- **pages, layouts and navigation**: create multiple pages, with customizable layouts and flexible navigation across them
- **actions and interactions**: create interactions between charts, and use pre-defined or customized actions (such as exporting)

Configuration can be written in multiple formats including **Pydantic models**, **JSON**, **YAML** or **Python dictionaries** for added flexibility of implementation

Optional high-code extensions allow almost infinite customisation in a modular way, combining the best of low-code and high-code - for flexible and scalable, Python enabled data visualization applications
Optional high-code extensions allow 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

(Visit the ["Why Vizro"](https://vizro.readthedocs.io/en/latest/pages/explanation/why_vizro/) section to see a more detailed explanation of Vizro use cases)

<br/>

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### Added

- Add a "why Vizro" section to the docs ([#73](https://github.com/mckinsey/vizro/pull/73))

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15 changes: 14 additions & 1 deletion vizro-core/docs/index.md
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# Vizro

Vizro is a toolkit for creating modular data visualization applications
Vizro is a toolkit for creating modular data visualization applications.


<div class="card-section-wrapper" style="display: block;">
<div class="responsive-grid">

<a class="card-wrapper" href="pages/tutorials/first_dashboard/">
<div class="card">
<div class="card-content">
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</div>
</a>

<a class="card-wrapper" href="pages/explanation/why_vizro/">
<div class="card">
<div class="card-content">
<h5>Explanation</h5>
<p>
Our explanation section contains background information and the answer to "why" questions.
</p>
</div>
</div>
</a>

<a class="card-wrapper" href="pages/development/contributing/">
<div class="card">
<div class="card-content">
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4 changes: 2 additions & 2 deletions vizro-core/docs/pages/development/authors.md
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Expand Up @@ -14,8 +14,8 @@

## Previous team members and code contributors

[Jo Stichbury](https://github.com/stichbury)
[Juan Luis Cano Rodríguez](https://github.com/astrojuanlu)
[Jo Stichbury](https://github.com/stichbury),
[Juan Luis Cano Rodríguez](https://github.com/astrojuanlu),
[Denis Lebedev](https://github.com/DenisLebedevMcK),
[Qiuyi Chen](https://github.com/Qiuyi-Chen),
[Elena Fridman](https://github.com/EllenWie),
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14 changes: 14 additions & 0 deletions vizro-core/docs/pages/explanation/why_vizro.md
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# Why Vizro

In the context of comparison with other visualization packages or business intelligence tools, Vizro combines benefits of the speed and user-friendliness of low-code visual analytics tools with the flexibility and power of high-code tools - whilst providing inbuilt visual design, application architecture and coding standardization which also facilitates scaling and reusability.

The simple and largely declarative configuration language follows a “grammar of dashboards” which makes the creation of complex dashboards more intuitive. This leverages modular components, empowering users to rapidly self-serve the assembly of customized dashboards with inbuilt visual styling in minutes, and reduces the amount of “glue code” required, whilst still retaining the ability to enhance functionality almost infinitely through customization and extensions, with standardization increasing the consistency across outputs.

<figure markdown>
![Image title](https://raw.githubusercontent.com/mckinsey/vizro/main/.github/images/code_dashboard.png)
<figcaption>Example of how Vizro's configuration language translates into an app</figcaption>
</figure>

Using configuration rather than a GUI to define the output facilitates collaboration during the creation process, and increases reusability and scalability in a Python setting.

The largely tech-agnostic configuration driven assembly enables utilizing a range of tools, and an inbuilt validation layer provides meaningful feedback to users about configuration choices, thereby increasing flexibility and ease of use.
3 changes: 2 additions & 1 deletion vizro-core/mkdocs.yml
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Expand Up @@ -31,12 +31,13 @@ nav:
- Extensions:
- Custom Charts: pages/user_guides/custom_charts.md
- Custom Components: pages/user_guides/custom_components.md

- API reference:
- Vizro: pages/API_reference/vizro.md
- Models: pages/API_reference/models.md
- Data Manager: pages/API_reference/manager.md
- Actions: pages/API_reference/actions.md
- Explanation:
- Why Vizro: pages/explanation/why_vizro.md
- Contribute:
- Contributing: pages/development/contributing.md
- Authors: pages/development/authors.md
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