Series - Pandas скачать в хорошем качестве

Series - Pandas

“There should be one—and preferably only one—obvious way to do it,” — Zen of Python. I certainly wish that were the case with pandas. In reading the docs it feels like there are a thousand ways to do each operation. And it is hard to tell if they do the exact same thing or which one you should use. That's why I made An Opinionated Guide to pandas—to present you one consistent (and a bit opinionated) way of doing data science with pandas and cut out all the confusion and cruft. I'll talk about which methods I use, why I use them and most importantly tell you the stuff that I've never touched in my years of data science practice. If this sounds helpful to you then please watch and provide feedback in your comments. This series is beginner-friendly​ but aimed most directly at intermediate users. Part 2 here:    • DataFrames - Pandas   “Intro to Data Structures p1” contents: NumPy broadcasting: https://docs.scipy.org/doc/numpy/user... pandas Series: https://pandas.pydata.org/pandas-docs... pandas Series indexing: https://pandas.pydata.org/pandas-docs... pandas Series vectorized operations: https://pandas.pydata.org/pandas-docs... NumPy Arrays: https://www.numpy.org/ pandas Series methods and attributes: https://pandas.pydata.org/pandas-docs... Virtualenv: https://virtualenv.pypa.io/en/latest/ Article on Dependency Managers:   / what-are-dependency-managers   Link that may be helpful w/PATH: https://unix.stackexchange.com/questi... Helpful links: Link to GitHub repo including environment setup for tutorials: https://github.com/knathanieltucker/p... Link to GitHub Intro To Data Structures Jupyter Notebook: https://github.com/knathanieltucker/p... PEP 20 – The Zen of Python link: https://www.python.org/dev/peps/pep-0...