Abstract

Glue is a Python library to explore relationships within and among related datasets. Its main features include: (a) Linked Statistical Graphics-–With Glue, users can create scatter plots, histograms and images (2D and 3D) of their data; (b) Flexible linking across data––Glue uses the logical links that exist between different data sets to overlay visualizations of different data, and to propagate selections across data sets; and (c) Full scripting capability––Glue is written in Python, and built on top of its standard scientific libraries (i.e., Numpy, Matplotlib, Scipy), where users can easily integrate their own python code for data input, cleaning, and analysis.  In this workshop, I will first demonstrate the basic functionalities of Glue, to visualize and to explore multi-dimensional datasets.  I will then provide examples of data exploration in real research projects, and try to help the participants explore their own data with Glue.