Dashboards in Python for Beginners and Everyone Else using Dash
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I love sharing and visualizing data as much as analyzing it, so I was enthusiastic about a project at work that gave me an excuse to finally learn Dash. Dash is a framework for Python written on top of Flask, Plotly.js, and React.js, and it abstracts away the complexities of each of those technologies into easy to apply components. Anyone who has a little Python and HTML experience will feel like Dash empowers them to create customized and interactive web-based dashboards without breaking a sweat. To quote the documentation’s Introduction,
“ Dash is simple enough that you can bind a user interface around your Python code in an afternoon.”
If you want to build something cool without being bogged down by the nuts and bolts under the hood, this is the guide for you. If you’re new to Dash, read on friend!
If you’re already familiar with Dash and want to see the final layout, scroll to the bottom or find the code on my GitHub.
Bookmark my other Dash Tutorials for advanced concepts, more examples, and tips and tricks not found in documentation!
3 Advanced Examples for Dash Beginners
Live Updates and Streaming Data into a Dashboard
Responsive Mobile Dashboards with Bootstrap CSS Components
Creating a Data Table using Data from Reddit
Exporting Data from a Dashboard
How to Setup User Authentication for Dash Apps using Python and Flask
Dashboards Made Simple
After wrapping my head around the core concepts, creating a simple dashboard felt like a “plug and play” experience. Dash can utilize Bootstrap CSS too, which makes styling and page-layout even easier to piece together.
Although I like Dash so far, it uses a lot of dictionaries and lists making it easy to lose your place. Once you get the hang of the patterns, it doesn’t feel bad. It can feel…
