Gary White Explains How to Create a Scatterplot Matrix Using Seaborn in Matplotlib

In this article we present the Network Analysis Profiler (NAP v2.0), a web tool to directly compare the topological features of multiple networks simultaneously. NAP is written in R and Shiny and currently offers both 2D and 3D network visualisation, as well as simultaneous visual comparisons of node- and edge-based topological features as bar charts or scatterplot matrix. NAP is fully interactive, and users can easily export and visualise the intersection between any pair of networks using Venn diagrams or a 2D and a 3D multi-layer graph-based visualisation. NAP supports weighted, unweighted, directed, undirected and bipartite graphs.

Download Full-text

iSPLOM: Interactive with Scatterplot Matrix for Exploring Multidimensional Data

Advances in Intelligent Systems and Computing - Knowledge and Systems Engineering ◽

10.1007/978-3-319-02741-8_16 ◽

2014 ◽

pp. 175-186 ◽

Cited By ~ 2

Author(s):

Tran Van Long

Keyword(s):

Multidimensional Data ◽

Scatterplot Matrix

Download Full-text

The Scatterplot Matrix

Statistical Graphics for Visualizing Multivariate Data ◽

10.4135/9781412985970.n5 ◽

2011 ◽

pp. 39-53

Keyword(s):

Scatterplot Matrix

Download Full-text

Scatterplot Matrix Techniques for Large N

Journal of the American Statistical Association ◽

10.2307/2289444 ◽

1987 ◽

Vol 82 (398) ◽

pp. 424 ◽

Cited By ~ 79

Author(s):

D. B. Carr ◽

R. J. Littlefield ◽

W. L. Nicholson ◽

J. S. Littlefield

Keyword(s):

Large N ◽

Scatterplot Matrix

Download Full-text

Feature-Rich, GPU-Assisted Scatterplots for Millions of Call Events

Computers ◽

10.3390/computers8010012 ◽

2019 ◽

Vol 8 (1) ◽

pp. 12

Author(s):

Dylan Rees ◽

Richard Roberts ◽

Roberts Laramee ◽

Paul Brookes ◽

Tony D’Cruze ◽

...

Keyword(s):

Call Center ◽

Data Sets ◽

Contact Center ◽

Working Population ◽

Real World Data ◽

Industry Partner ◽

End Times ◽

Contact Centers ◽

Scatterplot Matrix ◽

Operational Data

The contact center industry represents a large proportion of many country’s economies. For example, 4% of the entire United States and UK’s working population is employed in this sector. As in most modern industries, contact centers generate gigabytes of operational data that require analysis to provide insight and to improve efficiency. Visualization is a valuable approach to data analysis, enabling trends and correlations to be discovered, particularly when using scatterplots. We present a feature-rich application that visualizes large call center data sets using scatterplots that support millions of points. The application features a scatterplot matrix to provide an overview of the call center data attributes, animation of call start and end times, and utilizes both the CPU and GPU acceleration for processing and filtering. We illustrate the use of the Open Computing Language (OpenCL) to utilize a commodity graphics card for the fast filtering of fields with multiple attributes. We demonstrate the use of the application with millions of call events from a month’s worth of real-world data and report domain expert feedback from our industry partner.

Download Full-text