Initial data exploration often begins with an iterative approach involving reading data from files, writing small bits of code to process the data in some way, plotting data to visualize patterns and inter-variable relationships, and sharing ideas with colleagues. The combination of the Python programming language, the data analysis package pandas, and Jupyter (formerly IPython) notebooks, an interactive environment for development and sharing, provides a powerful and easy-to-use toolset for data exploration. Several members of the NSIDC software development team will introduce the use of pandas and Jupyter notebooks by analyzing real-world examples from NSIDC’s snow and ice data collections. Participants will learn how to use Jupyter notebooks, pandas for data analysis, and interactive visualization tools such as matplotlib
Michael Brandt, Paul Madden and Matt Savoie are software engineers at the National Snow and Ice Data Center (NSIDC). Michael works on a variety of software products in Ruby and JavaScript, and has taken a particular interest in the processing and visualization of data using Python. Paul enjoys working in the confluence of old-school and cutting-edge software technologies in support of science. Matt is a fluent translator between scientist and software and specializes in the processing and visualization of remotely sensed sea ice data.
