Python Libraries to Visualize Molecular Crystals
Programming libraries are the backbone of any programming language, and they contain additional classes and calculations for more functionality. In my previous article, Predicting Transparent Devices, I talked about building a transparent conductor prediction and visualization app. Here are the python libraries I used in visualizing molecular crystals.
Sklearn is a fantastic toolkit to begin machine learning. We used the Support vector regression and random forest model.
Pandas is a library to read and write CSV files.
Plotly is a visualization library that features interactive scatter plots and more.
Dash is a product by plotly powered by Flask, a lightweight backend framework, and React a frontend framework. Data scientists use Plotly Dash it for Web development.
The Dash Bootstrap LUX theme is an elegant way to make web components mobile responsive using Cards, buttons and grids.
Dash Bio is a plotly product developed to visualize atoms, molecules and more.
