13.2. Python

13.2.1. Useful Links

There are a lot of excellent tutorials and web pages for helping with Python coding:

• The gist of Python: a quick introductory blog that covers Python basics for data analysis.

• Jupyter Notebook: Jupyter Notebook provides a powerful notebook-based data analysis environment that SuPy users are strongly encouraged to use. Jupyter notebooks can run in browsers (desktop, mobile) either by easy local configuration or on remote servers with pre-set environments (e.g., Google Colaboratory, Microsoft Azure Notebooks). In addition, Jupyter notebooks allow great shareability by incorporating source code and detailed notes in one place, which helps users to organise their computation work.

  • Installation

    Jupyter notebooks can be installed with pip on any desktop/server system and open .ipynb notebook files locally:

    python3 -m pip install jupyter -U
    

  • Extensions: To empower your Jupyter Notebook environment with better productivity, please check out the Unofficial Jupyter Notebook Extensions. Quick introductory blogs can be found here and here.

• pandas: pandas is an essential tool for data analysis in Python.

  • Introductory blogs:

    • Quick dive into Pandas for Data Science: introduction to pandas.

    • Basic Time Series Manipulation with Pandas: pandas-based time series manipulation.

    • Introduction to Data Visualization in Python: plotting using pandas and related libraries.

  • A detailed tutorial in Jupyter Notebooks:

    • Introduction to pandas

    • pandas fundamentals

    • Data Wrangling with pandas

Tip

1. Stuck? the help and FAQ pages are useful places to start.

2. Please report workshop manual issues at GitHub Issues. Go from the page with the problem - an automatical link will be inserted. Thanks.