Dash
Dash primarily supports Plotly objects. It is, however, possible to use other plotting libraries with Dash. Dash prides itself as a language-agnostic framework that supports range of programming languages. According to the documentation, Dash provides support for Python, R, F# and Julia programming languages.
Other plotting libraries that can be used with Dash via different conversion mechanisms are Altair, Matplotlib, ggplot, etc.
The following types of maps and map components can be implemented in Dash: Choropleth Maps, Mapbox Choropleth Maps, Bubble Maps, Mapbox Density Heatmap, Hexbin MapBox, Mapbox Map Layers and more.
The typical file structure for a successful build and development of a Dash app is:
|── data/ .csv
│ ├── processed/
│ └── raw/
├── src/ app.py/app.R
├── doc/ .md
├── Procfile
├── Dockerfile
├── docker-compose.yml
├── requirements.txt
├── README.md
├── CODE_OF_CONDUCT.md
├── CONTRIBUTING.md
└── LICENSE.mdDash prides itself as a language-agnostic framework that supports range of programming languages. According to the documentation, Dash provides support for Python, R, F# and Julia programming languages.
In Python, Dash primarily supports Plotly objects. It is, however, possible to use other plotting libraries with Dash via different conversion mechanisms such as Seaborn/Matplotlib, Altair/Vega-Lite and Bokeh. Similarly, in R, aside from the Plotly library, Dash also supports some common graphing packages such as ggplot. However, the level of interaction and robustness of those graphs are maximized when they are plotted using Plotly.
to_html() method to include charts in iframes. This is essentially nesting a HTML page within a page.mpl_to_plotly() function in plotly.tools library that will return a plotly figure(which can then be returned to Graph’s figure attribute) from matplotlib figure.ggplotly() by Plotly, you can convert your ggplot2 figures into interactive ones powered by plotly.js, ready for embedding into Dash applications.According to here, the following types of maps and map components can be implemented in Dash:
While Plotly is the primary map plotting library for Dash, other plotting libraries can as well be used. Other popular libraries such as Altair, ggplot, Folium are the other popular options that can be used in Dash via conversion mechanisms.
For a successful build and deployment of the app on Heroku, the following files are must-haves: * app.py or app.R file * Dockerfile * Docker-compose.yml * Procfile * requirements.txt
The typical file structure is:
project/
├── data/ .csv
│ ├── processed/
│ └── raw/
├── src/ app.py/app.R
├── doc/ .md
├── Procfile
├── Dockerfile
├── docker-compose.yml
├── requirements.txt
├── README.md
├── CODE_OF_CONDUCT.md
├── CONTRIBUTING.md
└── LICENSE.mdAnother popular alternative is to put the app.py or app.R file in the root folder of the project.