@article{AikenAikenCotton2018,
  author    = {Aiken, John M. and Aiken, Chastity and Cotton, Fabrice},
  title     = {A python library for teaching computation to seismology students},
  series = {Seismological research letters},
  volume    = {89},
  journal   = {Seismological research letters},
  number    = {3},
  publisher = {Seismological Society of America},
  address   = {Albany},
  issn      = {0895-0695},
  doi       = {10.1785/0220170246},
  pages     = {1165 -- 1171},
  year      = {2018},
  abstract  = {Python is at the forefront of scientific computation for seismologists and therefore should be introduced to students interested in becoming seismologists. On its own, Python is open source and well designed with extensive libraries. However, Python code can also be executed, visualized, and communicated to others with "Jupyter Notebooks". Thus, Jupyter Notebooks are ideal for teaching students Python and scientific computation. In this article, we designed an openly available Python library and collection of Jupyter Notebooks based on defined scientific computation learning goals for seismology students. The Notebooks cover topics from an introduction to Python to organizing data, earthquake catalog statistics, linear regression, and making maps. Our Python library and collection of Jupyter Notebooks are meant to be used as course materials for an upper-division data analysis course in an Earth Science Department, and the materials were tested in a Probabilistic Seismic Hazard course. However, seismologists or anyone else who is interested in Python for data analysis and map making can use these materials.},
  language  = {en}
}