This repository contains the materials for D-Lab’s Python Fundamentals workshop. No prior experience with Python is required to attend this workshop.
This four-part, interactive workshop series is your complete introduction to programming Python for people with little or no previous programming experience. By the end of the series, you will be able to apply your knowledge of basic principles of programming and data manipulation to a real-world social science application.
Each of the parts is divided into a lecture-style coding walkthrough interrupted by challenge problems, discussions of the solutions, and breaks. Instructors and TAs are dedicated to engaging you in the classroom and answering questions in plain language.
- Part 1: Introduction to Python and Jupyter Notebooks, variables, data types, and functions.
- Part 2: Data structures, loops, conditionals, and creating functions.
- Part 3: Libraries, File I/O, and scientific computing.
- Part 4: Error handling, style, and an applied, in-depth project.
Anaconda is a useful package management software that allows you to run Python and Jupyter notebooks easily. Installing Anaconda is the easiest way to make sure you have all the necessary software to run the materials for this workshop. If you would like to run Python on your own computer, complete the following steps prior to the workshop:
-
Download and install Anaconda (Python 3.9 distribution). Click the "Download" button.
-
Download the Python Fundamentals workshop materials:
- Click the green "Code" button in the top right of the repository information.
- Click "Download Zip".
- Extract this file to a folder on your computer where you can easily access it (we recommend Desktop).
-
Optional: if you're familiar with
git
, you can instead clone this repository by opening a terminal and entering the commandgit clone git@github.com:dlab-berkeley/Python-Fundamentals.git
.
If you do not have Anaconda installed and the materials loaded on your workshop by the time it starts, we strongly recommend using the D-Lab Datahub to run the materials for these lessons. You can access the DataHub by clicking the following button:
The DataHub downloads this repository, along with any necessary packages, and
allows you to run the materials in a Jupyter notebook that is stored on UC
Berkeley's servers. No installation is necessary from your end - you only need
an internet browser and a CalNet ID to log in. By using the DataHub, 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, 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:
Binder operates similarly to the D-Lab DataHub, but on a different set of servers. By using Binder, however, you cannot save your work.
Now that you have all the required software and materials, you need to run the code.
-
Open the Anaconda Navigator application. You should see the green snake logo appear on your screen. Note that this can take a few minutes to load up the first time.
-
Click the "Launch" button under "JupyterLab" and navigate through your file system on the left hand pane to the
Python-Fundamentals
folder you downloaded above. Note that, if you download the materials from GitHub, the folder name may instead bePython-Fundamentals-main
. -
Open
00_workshop_setup.ipynb
to begin. -
Press Shift + Enter (or Ctrl + Enter) to run a cell.
Note that all of the above steps can be run from the terminal, if you're familiar with how to interact with Anaconda in that fashion. However, using Anaconda Navigator is the easiest way to get started if this is your first time working with Anaconda.
Check out the following online resources to learn more about Python:
D-Lab works with Berkeley faculty, research staff, and students to advance data-intensive social science and humanities research. Our goal at D-Lab is to provide practical training, staff support, resources, and space to enable you to use R for your own research applications. Our services cater to all skill levels and no programming, statistical, or computer science backgrounds are necessary. We offer these services in the form of workshops, one-to-one consulting, and working groups that cover a variety of research topics, digital tools, and programming languages.
Visit the D-Lab homepage to learn more about us. You can view our calendar for upcoming events, learn about how to utilize our consulting and data services, and check out upcoming workshops. Subscribe to our newsletter to stay up to date on D-Lab events, services, and opportunities.
D-Lab offers a variety of Python workshops, catered toward different levels of expertise.
- Python Geospatial Fundamentals
- Python Web Scraping and APIs
- Python Machine Learning
- Python Text Analysis
- Python Deep Learning
- Emily Grabowski
- Pratik Sachdeva
- Christopher Hench
- Rochelle Terman