Data analysis and visualization using the Python notebook interface

Date and Time: 
2015 April 17 - PM
FL2-1022 Large Auditorium
Ramalingam Saravanan

Computer models and remote sensing missions often generate datasets that are too large to store and analyze on desktop computers or even on local compute clusters. A traditional approach to exploring such datasets is to run the analysis program on a remote machine and display the output on the desktop computer via X windows. The tunneling option of the secure shell connection can be used to facilitate remote display of graphics generated by analysis software like Matlab, IDL, NCL etc. More recently, purely browser-based visualization tools are becoming more popular for graphical data analysis and visualization. These tools extend beyond desktop and laptop computers to the realm of mobile devices. Javascript toolkits like d3.js support powerful in-browser display options. The IPython Notebook interface combines markup, code, and graphics within a single browser-based document, serving as a replacement for the traditional terminal/editor/graphics window development environment. The notebook supports versatile inline graphics and widgets for remote visualization. This presentation will discuss different alternatives that are currently available for browser-based remote data analysis and discuss their pros and cons in the context of both teaching and research

Speaker Description: 

Saravanan has been a professor in the Department of Atmospheric Sciences at Texas A&M University since 2005. Previously, he worked as a scientist in CGD at NCAR. He received his Ph.D. in Atmospheric and Oceanic Sciences from Princeton University in 1990. His research involves the use of supercomputers for numeric al modeling and data analysis to study past, present, and future climates. He also dabbles in open source software and teaches courses in meteorology, climate, and introductory programming (using Python)

Video recorded: 

Ipython notebook created during the tutorial downloadable from this page (remove the _.txt extension) and visible at

Event Category: