Difference between revisions of "Python resources"
From atmoschem
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*[https://www.datacamp.com/community/tutorials/python-statistics-data-science#hypothesistesting 40+ Python Statistics For Data Science Resources] | *[https://www.datacamp.com/community/tutorials/python-statistics-data-science#hypothesistesting 40+ Python Statistics For Data Science Resources] | ||
A list of Python resources for the eight statistics topics that you need to know to excel in data science | A list of Python resources for the eight statistics topics that you need to know to excel in data science | ||
| + | *[https://www.statsmodels.org/stable/index.html Documentation for the python package StatsModels] | ||
=Plotting= | =Plotting= | ||
*[https://realpython.com/python-matplotlib-guide/ A guide for python plotting with Matplotlib] | *[https://realpython.com/python-matplotlib-guide/ A guide for python plotting with Matplotlib] | ||
Revision as of 18:03, 9 November 2019
Contents
Getting started with Python
Jupyter notebook
Jupyter notebooks are interactive web-based applications that allow users to create and share documents containing live codes, equations, narrative texts, figures, interactive user interfaces, and other rich media. When combined with the Python kernel, Jupyter notebooks allow users to code in Python and display results in an interactive and convenient way. Jupyter notebooks are really wonderful tools for learning Python, data science, and coding in general.
We strongly recommend installing Python and Jupyter on your PC using the Anaconda distribution, which includes Python, the Jupyter Notebook, and other commonly used packages for scientific computing and data science.
Students enrolled in courses will also be provided with an account and access to a SUSTech server running Jupyter. However, this server can only be accessed from within the SUSTech network. You can use a SUSTech VPN from off-campus locations. Details will be given during the first lecture.
- Jupyter notebook: an introduction
- A tutorial for Jupyter run on mybinder It is a bit slow but worth it.
- 一个中文tutorial
Python tutorials for beginners
There are many, many good tutorials for Python. We encourage you to try out a few yourself. A few examples are listed here, but there are many more on the web. After learning the basics, you should seek out examples particular to your application on your own.
Python for atmospheric science
- A Hands-on Introduction to Using Python in the Atmospheric and Oceanic Sciences This is a Python textbook geared specifically for use in atmospheric and oceanic sciences. The writing is extremely clear and useful. Highly recommended. The PDFs can be downloaded for free.
- Research Computing in Earth Sciences is a Columbia University course designed to introduce incoming LDEO graduate students to modern computing software, programming tools and best practices that are broadly applicable to carrying out research in the Earth sciences. All materials are available online. Highly recommended.
- Unidata's online Python tutorial for atmospheric science.
- Dr McCray (McGill University) put together a few Python tutorials for atmospheric science.
- This course "Oceanographic Data Analysis With Open Source Tools" at University of Hawaii is a great resource. In particular, I highly recommend these Jupyter notebooks on climate data analyses.
- climlab is a python package for process-oriented climate modeling developed by Brian Rose (SUNY Albany)
Python for data science
- Get Data Off the Ground with Python An online MOOC course by Professor Lorena Barba at George Washington University.
- Take off with Stat in Python An online MOOC course by Professor Lorena Barba at George Washington University.
- A very simple tutorial of using python for data science.
- 40+ Python Statistics For Data Science Resources
A list of Python resources for the eight statistics topics that you need to know to excel in data science
