- Dash allows us to create fully interactive data analytic web applications and interfaces, using pure Python, without having to worry about HTML, CSS, or JavaScript.
Dash = Flask + Plotly + React
- Dash uses Flask for the backend. For producing charts and data visualization, it uses Plotly. React is used for handling all components, and actually a dash app is rendered as a single-page React app.
- Various data visualizations to dashboards
- Interactive web applications without needing to know HTML, CSS, or JavaScript.
- Highly customizable and flexible (Change the layout, style, and interactivity of your dashboard)
- Easy to share
- The following are the main modules that we will mostly be using:
- Dash: This is the main module, which provides the backbone of any app, through the Dash object.
- Dash Core Components: A module that provides a set of interactive components that can be manipulated by users. For example, dropdowns, radio buttons, checklists, and many more components are included in this module.
- Dash HTML Components: This module provides all the available HTML tags as Python classes. It simply converts Python to HTML tags.
- For example, you can call
html.Div('My Dashboard') in Python, and it will be converted to <div>My Dashboard</div> and render as such in a browser.
- Dash is available in a public repository called PyPI (Python Package Index)
- The tool can be installed from the command line using the Python Management System, pip.
- For Windows users, from the command line, running as an administrator, simply issue the following two commands:
- For Mac users, from a terminal, simply issue the following two commands: