2.4 Data formats - Python for Scientific Computing 2023
Input/output bandwidth is just as much a consumable resource as CPU or memory. And data formats are important for both ease (human effort) and time taken to read data. Here, we will go over the basic concepts and some important data formats which you may need in your work.
The longer video from last year: • 2.3 Data formats - Python for Scienti...
https://aaltoscicomp.github.io/python...
01:00 What do we mean by data formats?
01:31 What's a data frame?
04:51 Numpy arrays arrangement?
06:29 Each file format has a purpose
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Python for Scientific Computing is a bridge between basic Python courses and scientific work with Python. This is a basic to intermediate course in Python tools such as NumPy, SciPy, Matplotlib, and Pandas. It also covers some more advanced tools, such as Binder, releasing software, data formats, etc. It is suitable for people who have a basic understanding of Python and want to know some internals and important libraries for science. We don't cover anything in too much depth, but we do introduce you to all of the main tools you will need.
This course was put on as a collaboration between partners in Finland, Norway, and Sweden, coordinated by Aalto Scientific Computing.
Links:
Playlist: • Python for Scientific Computing 2023
Course material: https://aaltoscicomp.github.io/python...
Workshop webpage: https://scicomp.aalto.fi/training/sci...
Aalto Scientific Computing: https://scicomp.aalto.fi/
CodeRefinery: https://coderefinery.org
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