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  1. Dash is the original low-code framework for rapidly building data apps in Python.

    • Part 1. Layout

      The Dash `layout` describes what your app will look like and...

    • Dash Core Components

      Dash ships with supercharged components for interactive user...

    • API Reference

      API Reference - Dash Documentation & User Guide | Plotly

    • WBR

      WBR - Dash Documentation & User Guide | Plotly

    • Clustergram

      Clustergram - Dash Documentation & User Guide | Plotly

    • Track

      Track - Dash Documentation & User Guide | Plotly

    • Basefont

      Basefont - Dash Documentation & User Guide | Plotly

  2. A Dash tutorial that shows you how to create a Dash app in 20 minutes.

  3. pypi.org › project › dashdash · PyPI

    May 3, 2024 · Dash is a popular and trusted Python framework for creating interactive web apps with Plotly.js, React and Flask. Learn how to build dashboards, dash apps, and scale up with Dash Enterprise for ML Ops, low-code, and enterprise AI features.

  4. Learn how to use Dash, a Python framework for building interactive data apps, with various examples from different domains and use cases. Find apps for AI, machine learning, geospatial, sports, bioinformatics, and more.

  5. Learn how to use Dash, an open-source framework for building data visualization interfaces in Python, R, Julia, or F#. Follow along with a step-by-step example of creating a dashboard using avocado data and deploying it on PythonAnywhere.

    • dash python1
    • dash python2
    • dash python3
    • dash python4
  6. Learn how to build dashboards in Python using Dash, a web framework based on Flask, Plotly.js, React and React Js. Follow the steps to create interactive graphs, layouts and components with Dash.

  7. import pandas as pd. app = Dash(__name__) # assume you have a "long-form" data frame. # see <a href="https://plotly.com/python/px-arguments/">https://plotly.com/python/px-arguments/</a> for more options. df = pd.DataFrame({ "Fruit": ["Apples", "Oranges", "Bananas", "Apples", "Oranges", "Bananas"], "Amount": [4, 1, 2, 2, 4, 5],