Resources

General

• Office hours

• Stack Overflow

• RealPython

• FreeCodeCamp

• GitHub Student Developer Pack

  • Includes learning resources and various tools

NYU

• Wagner Quantitative Support

  • Tutoring

  • Math Review

• NYU Library Data Services

  • Consultation

  • Classes

• The Coding Lab

Pandas

• Documentation

• Cheat sheets

  • Official

  • DataCamp

  • DataQuest

• Python for Data Analysis book

• NYU’s Quantitative Analysis Guide: Python

There are countless other blog posts, videos, books, etc. out there. There is no “best” resource, as individuals prefer different formats, come in with different experience, and learn at different speeds. Anything that comes up near the top of a Google search will likely be fine.

Learning more

Want to keep going after this class?

Python fundamentals

Recommended focusing on fundamentals of Python 3. Many “learn Python” resources will be web development-oriented (they will probably mention Django/Flask), so you might want to look for ones that focus on data science or Python 3 on its own. Some that are data-oriented:

• freeCodeCamp’s Scientific Computing with Python class

• DataCamp’s Python Fundamentals or Python Programmer tracks

Countless other “learn Python” resources/courses/videos/books out there; there isn’t one right choice for everyone.

Machine learning

• Kaggle’s Intro to Machine Learning

• DataCamp’s Natural Language Processing in Python track

NYU

• Wagner Data Science and Data Management

• Center for Urban Science + Progress (CUSP)

  • Applied Data Science

  • Machine Learning for Cities

Jupyter outside this course

We use a cloud-based Jupyter environment (JupyterHub) for this course to avoid installation issues across student computers. This is the only environment that’s supported for course work.

After this class, however, you’ll no longer have access. Some options for running Jupyter on your own:

• Google Colab

• Anaconda

• Visual Studio Code

Matching the class environment

Advanced

Note these instructions won’t work in Colab.

1. Install Mamba.

2. Clone the repository.

3. Check out the nyu branch.

4. Create the environment. From this directory, run:

   mamba env create --file extras/environment.lock.yml
   

5. Activate the environment:

   conda activate python-public-policy
   

6. Start the Jupyter server:

   jupyter notebook
   

See also

• 14 Principles of Open Government Data

• Blog post about GitHub for non-developers

• DataJournalism.com