This is the effort to introduce to use Dash with Python to build dashboard for business intelligence purpose. Please also visit my Medium Post to introduce using Plotly Dash to build a dashboard.
Dash is an open source Python library to create a web-based visualiztion application provided by Plotly. This package is great for building dashboard, markdown reports and any kinds of data visualization. This package is built on top of pure Plotly and Flask allow you to build a dashboard using pure Plotly library and host the dashboard via Flask. The ideal use of this library could be building a dashboard using Dash and host it on AWS (Or other cloud computers) and allow views to read it via a link.
It is free. BI tools like Tableau or Microsoft Power BI are great but they are costly to operate. Dash is a good alternative tool to provide similar quality and experience with no cost.
Dash runs in Python. You may use Pandas and any Python library to manipulate your data frame before render the visualization with Dash.
The quality of the visualization in Dash or Plotly is very high that is comparable with Tableau charts because Dash renders d3 visualization.
Plotly is one of the great open source visualization package in the Python library. Many Python developers use Plotly for data visualization. As a product of Plotly, Dash allows developers to integrate their Plotly visualization on the Dash dashboard. Dash is a tool to make building dashboard using Plotly graph easier.
Dash runs web server in Flask. No need to set up in Flask, easy to host the web server in AWS. You don't need to be a web programmer to build the dashboard.
Although the dashboard is viewed in a web broswer, it is a high level tool that the developers are only required to write in Python and have some understanding of html. It means no Javascript or d3 is needed to be written to produce the same product but you may leverage the interactive elements available in d3. Dash is very customizable that you may custom the dashboard using the html layout which eliminates the contraint of pure Plotly's customizability.
Dash relies on Plotly plots, it is a good idea to understand how Plotly works first. Here are the tutorial and examples for plotting in Plotly:
Fundamentals
Bar Charts
Line Charts
Scatter Plot/Bubble Chart
Box Plots
Pie/Donut Charts
Histogram
Treemaps
Heatmaps
Candlestick Charts
Funnel Chart
Choropleth Graphs
Sunburst Charts
Parallel Categories Diagram
Sankey Diagram
Dendrograms (Decision Tree) (Coming Soon...)
Or click the link here to the Plotly Example folder for the selected list of the visualizations can be made with Plotly.
This repositories contains examples from the official Dash site and myself. There are 3 parts for the tutorial with different levels of functionality.
Part 1 - Basics of Using Dash
Part 2 - Dash Callbacks
Part 3 - Interactive Visualization
Dashboard Example - Gaming Console Market Share in 2018
This section contains the quick-start note for dockerizing Plotly and Dash for your solution. You may find the direction and tips to create Docker Image with Plotly and Dash in the Dockerize Dash folder.
Alternatively, you may read the instructions in this Medium Post: Dockerizing Plotly/Dash
You may find the template framework for Plotly when you want to quickly plot something with Plotly. You may find the scripts in the Template Framework folder.
Official Website of Dash: Dash User Guide
Medium Post: Brief Introduction of Dash by Plotly