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Browse files- README.md +9 -16
- assets/css/custom.css +1 -1
- custom_components.py +2 -7
- requirements.in +1 -1
- requirements.txt +4 -11
README.md
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@@ -13,14 +13,11 @@ short_description: Vizro - Visual vocabulary
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### Welcome to our visual vocabulary dashboard! 🎨
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This dashboard serves as a comprehensive guide for selecting and creating various types of charts. It helps you decide
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when to use each chart type, and offers sample Python code using [Plotly](https://plotly.com/python/), and
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instructions for embedding these charts into a [Vizro](https://github.com/mckinsey/vizro) dashboard.
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The charts in this dashboard are designed to make it easy for anyone to create beautiful and sophisticated visuals.
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Our goal is to help you understand best practices in data visualization, ensure your charts effectively communicate
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your message, and streamline the creation of high-quality, interactive visualizations.
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Created by:
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Inspired by:
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- [The FT Visual Vocabulary](https://github.com/Financial-Times/chart-doctor/blob/main/visual-vocabulary/README.md):
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[Alan Smith](https://github.com/alansmithy), [Chris Campbell](https://github.com/digitalcampbell), Ian Bott,
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Liz Faunce, Graham Parrish, Billy Ehrenberg, Paul McCallum, [Martin Stabe](https://github.com/martinstabe).
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- [The Graphic Continuum](https://www.informationisbeautifulawards.com/showcase/611-the-graphic-continuum):
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Jon Swabish and Severino Ribecca
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Credits and sources:
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Contributions are welcome! To contribute a chart, follow the steps below:
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1. Check that a `svg` file named after the chart type is contained in the [assets](https://github.com/mckinsey/vizro/tree/main/vizro-core/examples/visual-vocabulary/assets/images/charts) folder. If not, [raise an issue](https://github.com/mckinsey/vizro/issues) in the repository.
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5. Update this `README.md` with the new chart type, its status, category, and API links.
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## How to run the example locally
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1. Run the example with the command `hatch run example visual-vocabulary`.
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### Welcome to our visual vocabulary dashboard! 🎨
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This dashboard serves as a comprehensive guide for selecting and creating various types of charts. It helps you decide when to use each chart type, and offers sample Python code using [Plotly](https://plotly.com/python/), and instructions for embedding these charts into a [Vizro](https://github.com/mckinsey/vizro) dashboard.
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The charts in this dashboard are designed to make it easy for anyone to create beautiful and sophisticated visuals.
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Our goal is to help you understand best practices in data visualization, ensure your charts effectively communicate your message, and streamline the creation of high-quality, interactive visualizations.
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Created by:
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Inspired by:
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- [The FT Visual Vocabulary](https://github.com/Financial-Times/chart-doctor/blob/main/visual-vocabulary/README.md): [Alan Smith](https://github.com/alansmithy), [Chris Campbell](https://github.com/digitalcampbell), Ian Bott, Liz Faunce, Graham Parrish, Billy Ehrenberg, Paul McCallum, [Martin Stabe](https://github.com/martinstabe).
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- [The Graphic Continuum](https://www.informationisbeautifulawards.com/showcase/611-the-graphic-continuum): Jon Swabish and Severino Ribecca
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Credits and sources:
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Contributions are welcome! To contribute a chart, follow the steps below:
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1. Check that a `svg` file named after the chart type is contained in the [assets](https://github.com/mckinsey/vizro/tree/main/vizro-core/examples/visual-vocabulary/assets/images/charts) folder. If not, [raise an issue](https://github.com/mckinsey/vizro/issues) in the repository.
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1. Add a `.py` file containing a code example of the chart type in the `pages/examples` folder, for instance, `area.py`. Take a look at existing examples.
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1. Create a new page for the chart type and add it to the relevant category `.py` file such as `correlation.py`, `deviation.py`, `distribution.py`, etc. Ensure you add the page to the list of `pages` at the end of the `.py` file.
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1. Remove the `IncompletePage(..)` entry for that chart type in `chart_groups.py`.
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1. Update this `README.md` with the new chart type, its status, category, and API links.
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## How to run the example locally
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1. Run the example with the command `hatch run example visual-vocabulary`.
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1. You should now be able to access the app locally via http://127.0.0.1:8051/.
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assets/css/custom.css
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@@ -94,7 +94,7 @@ img[src*="#chart-icon"] {
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background: var(--text-primary);
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border-top-left-radius: 8px;
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bottom: 0;
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color: var(--text-primary-inverted);
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display: flex;
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font-size: 0.8rem;
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font-weight: 500;
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background: var(--text-primary);
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border-top-left-radius: 8px;
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bottom: 0;
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color: var(--text-primary-inverted) !important;
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display: flex;
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font-size: 0.8rem;
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font-weight: 500;
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custom_components.py
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"""Contains custom components used inside the dashboard."""
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from typing import Literal
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import dash_bootstrap_components as dbc
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import vizro.models as vm
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from dash import dcc, html
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try:
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from pydantic.v1 import Field
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except ImportError: # pragma: no cov
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from pydantic import Field
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from urllib.parse import quote
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class CodeClipboard(vm.VizroBaseModel):
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"""Contains custom components used inside the dashboard."""
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from typing import Literal
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from urllib.parse import quote
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import dash_bootstrap_components as dbc
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import vizro.models as vm
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from dash import dcc, html
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from pydantic import Field
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class CodeClipboard(vm.VizroBaseModel):
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requirements.in
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autoflake==2.3.1
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black==24.4.2
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isort==5.13.2
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plotly==
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vizro==0.1.28
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gunicorn
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autoflake==2.3.1
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black==24.4.2
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isort==5.13.2
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plotly==6.0.0
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vizro==0.1.28
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gunicorn
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requirements.txt
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@@ -50,9 +50,7 @@ gunicorn==23.0.0
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idna==3.10
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# via requests
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importlib-metadata==8.5.0
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# via
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# dash
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# flask
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isort==5.13.2
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# via -r requirements.in
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itsdangerous==2.2.0
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# werkzeug
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mypy-extensions==1.0.0
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# via black
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nest-asyncio==1.6.0
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# via dash
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numpy==2.0.2
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# via black
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platformdirs==4.2.2
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# via black
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plotly==
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# via
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# -r requirements.in
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# dash
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# via
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# python-dateutil
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# retrying
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tenacity==9.0.0
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# via plotly
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tomli==2.1.0
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# via
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# autoflake
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# black
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typing-extensions==4.12.2
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# via
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# black
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# dash
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# pydantic
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# pydantic-core
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idna==3.10
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# via requests
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importlib-metadata==8.5.0
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# via dash
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isort==5.13.2
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# via -r requirements.in
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itsdangerous==2.2.0
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# werkzeug
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mypy-extensions==1.0.0
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# via black
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narwhals==1.25.0
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# via plotly
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nest-asyncio==1.6.0
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# via dash
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numpy==2.0.2
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# via black
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platformdirs==4.2.2
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# via black
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plotly==6.0.0
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# via
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# -r requirements.in
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# dash
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# via
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# python-dateutil
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# retrying
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typing-extensions==4.12.2
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# via
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# dash
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# pydantic
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# pydantic-core
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