1.3 Numpy - Python for Scientific Computing 2021 смотреть онлайн

Numpy is the standard Python array package. It provides not only the basic data structure, but also plenty of operations on this data. By using built-in functions, many operations can be vectorized and made much faster (just like they are done in any other high-level numerical language). Many other scientific and numerical packages are build using Numpy, so it is very important to learn to use it well.

https://aaltoscicomp.github.io/python-for-scicomp/numpy/


00:41 What is the array object?
03:01 Python vs Numpy speed test
06:06 Ways to create arrays
11:51 Array math
13:46 Exercises 1, 2
15:24 Indexing and slicing
21:35 Universal functions
25:07 Exercises 3, 4, (5)
26:01 Q&A
31:56 wrap-up and conclusions

-----

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: https://www.youtube.com/playlist?list=PLZLVmS9rf3nOS7bHNmbcDoyTnMYaz_TJW
- Course material: https://aaltoscicomp.github.io/python-for-scicomp/
- Workshop webpage: https://scicomp.aalto.fi/training/scip/python-for-scicomp/
- Aalto Scientific Computing: https://scicomp.aalto.fi/
- CodeRefinery: https://coderefinery.org