Interactive data science

Interactive data science environments provide a way to rapidly explore data, develop work flows, share code and visualise results. A variety of Data Science environments are available, Jupyter is a popular choice in the scientific community. It provides a well supported open-source cross-language solution for data analysis and visualisation.

Through the Oznome, DAMBusters and EUDM projects we have developed a high level of expertise in building customised Jupyter environments and consulting to introduce interactive data science solutions in new contexts and projects. We have extended Jupyter using both standard compositions of IPython Widgets and through more advanced approaches to produce customised Jupyter Environments.

Examples of our work include:

customized widgets for Pandas Data Frame Filtering
Custom widgets for environmental data APIs
Interactive Maps using IPyLeaflet
provenance tracking.

A variety of Jupyter Notebooks are publically available at https://github.com/oznome/jupyter-examples