Resources#
There are countless 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.
Questions#
pandas cheat sheets#
Tutorials#
Books#
Python for MBAs “and those in business roles that include coding or working with coding teams”
Courses#
Pre-approved courses outside of Wagner (for Wagner students)
Free trials for online courses through the GitHub Student Developer Pack
Python fundamentals#
DataCamp’s Python Fundamentals or Python Programmer tracks
Data analysis/science#
Center for Urban Science + Progress (CUSP)
Applied Data Science
Machine Learning for Cities
freeCodeCamp’s Scientific Computing with Python class
IBM Data Analyst Course - can jump to specific parts
Machine learning#
Workshops#
Learning more#
Want to keep going with Python after this class? See Developer Roadmaps for directions you can go. This course doesn’t spend a lot of time on Python fundamentals, so it’s recommended that you do that first.
Many “learn Python” resources will be web development-oriented — they will probably mention Django/Flask. If you want to stay focused on data, you might want to look for ones that focus on data science or Python 3 generally.
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. To download the files:
Open a notebook
In a code cell, run
!tar -czvf ~/python_files.tar.gz ~
From the file browser, check the box next to
python_files.tar.gz
, then clickDownload
On your computer, unzip the file.
On Windows, you may need to install 7-Zip to do so.
A non-exhaustive list of alternatives:
Local#
Cloud-based#
Matching the class environment#
Advanced
Note these instructions won’t work in Colab.
Install Mamba.
Check out the
nyu
branch.-
conda config --set channel_priority strict
Create the environment. From this directory, run:
mamba env create --file extras/environment.lock.yml
Activate the environment:
conda activate python-public-policy
Start the Jupyter server:
make notebook