Materials for Python short course for incoming Statistics grad students.
The workshop will be in Evans 332.
We’ll provide a few snacks, but given the somewhat late end time, feel free to bring your own and some lunch if you expect to be hungry.
The workshop content is in Markdown in python.qmd with a rendered HTML version in python.html and an Jupyter notebook version in python.ipynb. The mini-project material is in project.qmd/project.html/project.ipynb. The qmd files are the new-ish Quarto format, but are basically simple Markdown files with Python code chunks interspersed.
To download the materials on your computer, you have two options:
We’ll primarily be directly working with the Python code in the Markdown or notebook versions of the files, but you can see static HTML versions:
The only, but important, preparation in advance of the bootcamp is to make sure you have access to Python, with key packages (numpy, pandas, matplotlib, statsmodels) that we’ll use during the bootcamp.
Whether you run Python (or IPython) through the command line or via a Jupyter Notebook doesn’t matter.
In the workshop, I’ll primarily use both approaches.
Below are a couple options for having access to Python. Please make sure at least one of these works for you before you arrive at the short course. The last two options require a computing account with the department through the Statistical Computing Facility, which you request here: https://scf.berkeley.edu/account
(1) Download and install Anaconda (Python 3.11 distribution) on your laptop. Click “Download” and then click 64-bit “Graphical Installer” for your current operating system.
(2) Use the UC Berkeley DataHub to access Python via Jupyter notebooks. You can launch a Jupyter session that has access to the workshop materials here. Then just double-click on the python.ipynb file in the left pane and it should open in a notebook.
If you have an SCF account, you have a couple more options:
(3) SSH to any SCF Linux machine and run Python from the command line.
(4) Login to the SCF JupyterHub (using your SCF username and password) to access a Jupyter IPython notebook. Further instructions are here.
If you have questions about the workshop please don’t hesitate to email me.