Reusing Open Data with ERDDAP and Python

Key Points

Open Data & ERDDAP

  • Open data is documentation and sharing research data openly for re-use:

  • Reusing data from another source can be challenging

  • ERDDAP provides the ability to download data in common file formats :
Finding data in the ERDDAP data catalog

  • Searching an ERDDAP data catalog can be done using a web page

  • Data can be downloaded in different file formats

  • Constraints can be added to a dataset search
Data requests using an ERDDAP URL

  • Tabledap request URLs are in the form: server/protocol/datasetID.fileType{?query}

  • urllib library works with https protocols
Online data to your Python environment

  • There are keypackages necessary to import data from ERDDAP into Python: pandas

  • Data can be downloaded locally or be interacted with directly using erddapy

  • You can asses your data package in Python
Aggregating multiple datasets

  • There are keypackages necessary to import data from ERDDAP into Python: pandas, urllib

  • Data can be downloaded locally or be interacted with directly using erddapy

  • You can asses your data package in Python
Gridded dataset

  • There are key packages necessary to import data from ERDDAP into Python: xarray

  • xarray works similar to Pandas

  • xarray has a build in plotter for gridded datasets

Inspiration, modified examples and content has been used from the following sources:

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