DataFrames - 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.

“Intro to Data Structures p2” contents:
pandas DataFrames: https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.html
pandas indexing: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html
pandas loc: https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.loc.html
pandas iloc: https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.iloc.html
broadcasting

Helpful links:
An Opinionated Guide to pandas – Intro to Data Structures P2:
https://www.youtube.com/watch?v=KB-19V-cSs4&feature=youtu.be
Link to GitHub Intro To Data Structures Jupyter Notebook: https://github.com/knathanieltucker/pandas-tutorial/blob/master/notebooks/Pandas%20Intro%20to%20Data%20Structures.ipynb

Link to GitHub repo: https://github.com/knathanieltucker/pandas-tutorial

PEP 20 – The Zen of Python link: https://www.python.org/dev/peps/pep-0020/