To sign up for the Python series and other workshops, please visit the D-Lab's website.

If you have a Berkeley CalNet ID, you can run these lessons on Berkeley's DataHub by clicking this link. By using this link, you can save your work and come back to it at any time. When you want to return to your saved work, just go straight to DataHub (https://datahub.berkeley.edu), sign in, and you click on the python-fundamentals folder.

If you don't have a Berkeley CalNet ID, you can still run these lessons in the cloud, by clicking this button: By using this button, you cannot save your work unfortunately.

To run these lessons on your laptop:

• Click the green "Clone or Download" button
• Click "Download Zip"
• Extract this file someplace familiar (we recommend Desktop)

If you are a Git user, clone the repo on your laptop command line:

git clone https://github.com/dlab-berkeley/python-fundamentals.git

The D-Lab introductory series consists of four parts:

Part 1:

• Running Python
• Jupyter notebooks
• Variables assignment
• Types conversion
• Strings
• Built-ins

Part 2:

• Lists
• Loops
• Conditionals
• Functions
• Scope

Part 3:

• Dictionaries
• Files
• Libraries
• Errors
• Comprehensions

Part 4:

• Python in Application

Parts 1-3 focus on learning the basics of programming in Python. This includes variables, data types, conditionals, functions, scope, debugging, and style. All of the materials aim to use examples from the social sciences and humanities in order to better relate to our target audience. In support of this, Part 4 is a day of application. Learners will work with a real-world text data set of UN documents, extracting targeted information and generating tabular data, ultimately writing to a .csv file suitable for subsequent statistical analysis. Everything needed to complete Part 4 is covered in parts 1-3.

Much of these materials were adapted from those produced by Software Carpentry. Thank you!