We want to create a data analysis process that:

  • is adaptable to many projects and domains
  • allows you to produce (and re-produce) analysis efficiently
  • is satisfying to produce and maintain

Key principles

Many of the ideas proposed boil down to some key principles:

  • let the computer do the work
  • fail fast

Learning objectives

By the end of this workshop our objective is that you will be able to:

  • navigate and create a directory in the shell
  • set up generic data analysis projects
  • describe why virtual environments are useful
  • create and activate a virtual environment from a file
  • describe the use cases of key oceanographic analysis libraries
  • describe the relationship between the key oceanographic analysis libraries
  • integrate a test dataset into your pipeline
  • aggregate your data using groupby operations
  • know how to find the bottlenecks in your code
  • identify your next learning objective and how you will acheive it

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