Data Visualization

Glue – Multi-Dimensional Linked-Data Exploration

Glue is an open source Python library to explore relationships within and between related datasets.

Glue is designed with “data-hacking” workflows in mind, and can be used in different ways.

Glue is a multi-disciplinary tool. It’s used on astronomy data of star forming-clouds, medical data including brain scans, and many other kinds of data.

Key Features

  • Interactive, linked statistical graphics of multiple files.
  • Create scatter plots, histograms and images (2D and 3D) of their data. Glue is focused on the brushing and linking paradigm, where selections in any graph propagate to all others.
  • Uses the logical links that exist between different data sets to overlay visualizations of different data, and to propagate selections across data sets.
  • Support for many file formats including common image formats (jpg, tiff, png), ascii tables, astronomical image and table formats (fits, vot, ipac), and HDF5. Custom data loaders can also be easily added. Glue provides a simple mechanism for creating custom visualizations using matplotlib.
  • Highly scriptable and extendable.
  • Built on top of its standard scientific libraries (i.e., NumPy, Matplotlib, SciPy).
  • Monitor the data files you’ve loaded for changes, and to auto-refresh plots when needed.
  • Easily integrate your own Python code for data input, cleaning, and analysis.
  • Customize many aspects of your Glue environment. Glue lets you create custom data loader functions, custom link functions, and more.

Glue relies on several libraries to parse different file formats:

  • Astropy for FITS images and tables, a variety of ascii table formats, and VO tables.
  • scikit-image to read popular image formats like .jpeg and .tiff.
  • h5py to read HDF5 files.

Glue has the following dependencies:

  • Python 2.7, or 3.3 and higher;
  • Numpy 1.9 or later;
  • Matplotlib 2.0 or later;
  • Pandas 0.14 or later;
  • Astropy 1.0 or higher;
  • setuptools 1.0 or later;
  • Either PyQt5 or PySide2;
  • QtPy 1.2 or higher – this is an abstraction layer for the Python Qt packages;
  • IPython 4.0 or higher;
  • ipykernel;
  • qtconsole;
  • dill 0.2 or later (which improves session saving);
  • h5py 2.4 or later, for reading HDF5 files;
  • xlrd 1.0 or later, for reading Excel files;
  • mpl-scatter-density, for making scatter density maps of many points;
  • bottleneck, for fast NaN-friendly computations.

Website: glueviz.org
Support: Documentation, GitHub Code Repository, Mailing List
Developer: Glue developers
License: BSD License

Glue

Glue is written in Python. Learn Python with our recommended free books and free tutorials.


Related Software

Python Visualization Packages
matplotlibPython 2D plotting library which produces publication quality figures
DiagramsDraw the cloud system architecture in Python code
BokehElegant, concise construction of versatile graphics
DashPython framework for building analytical web applications
seabornPython visualization library based on matplotlib
PlotlyInteractive, browser-based graphing library for Python
VisPyVisualize massive datasets in real time
Vega-AltairDeclarative Visualization in Python
plotnineGrammar of graphics for Python
PyQtGraphPython graphics and GUI library built on PyQt4 / PySide and numpy
bqplotInteractive Plotting Framework for the Jupyter Notebook
VaexFast visualization of big data
PyVista3D plotting and mesh analysis
foliumVisualize data in a Leaflet map
HoloViewsMake Data Analysis and Visualization Seamless
DatashaderGenerates aggregate arrays and representations of them as images
ytMulti-code Toolkit for Analyzing and Visualizing Volumetric Data
GlumpyIntuitive interface between NumPy and modern OpenGL
GeoViewsExplore and visualize geographical, meteorological, and oceanographic datasets
PygalDynamic SVG charting library
GlueMulti-dimensional linked-data exploration

Read our verdict in the software roundup.


Best Free and Open Source Software Explore our comprehensive directory of recommended free and open source software. Our carefully curated collection spans every major software category.

This directory is part of our ongoing series of informative articles for Linux enthusiasts. It features hundreds of detailed reviews, along with open source alternatives to proprietary solutions from major corporations such as Google, Microsoft, Apple, Adobe, IBM, Cisco, Oracle, and Autodesk.

You’ll also find interesting projects to try, hardware coverage, free programming books and tutorials, and much more.

Discovered a useful open source Linux program that we haven’t covered yet? Let us know by completing this form.
Subscribe
Notify of
guest
0 Comments
Oldest
Newest Most Voted