Manage Large Datasets with Python and HDF5

Are you using Python to process large numerical datasets? Over the past few years, the Hierarchical Data Format (HDF5) has emerged as the mechanism of choice for processing, archiving and sharing scientific datasets ranging from gigabytes to terabytes and beyond. With a diverse user base spanning the range from NASA to the financial industry, HDF5 lets you create high-performance, portable, self-describing containers for your data. HDF5’s flexibility and speed make it particularly well-suited to analysis in Python.

This webcast provides a practical, Python-based introduction to the world of HDF5. This webcast covers:
* The basics of the format
* Performance
* Best practices for making sharable data files which can be read by colleagues on other platforms

Video producer: