During COVID-19, Research Commons' services continue.
SFU graduate students are encouraged to book consultations with the Research Commons staff and partners. Consultations are available by phone, via email, or through online video-conference.
Not finding what you're looking for? Please get in touch with us at firstname.lastname@example.org so we can discuss your research support needs.
This workshop is currently full and you will be placed on a waitlist.
All times are Pacific Time Zone (Vancouver, BC, Canada).
Python is a popular language for scientific computing, and great for general-purpose programming as well. This hands-on workshop will cover basic concepts and tools, including data structures, and popular data science libraries such as pandas and numpy. This workshop uses curricula from Software Carpentry, whose mission is to help researchers get more work done in less time and with less pain by teaching them basic lab skills for scientific computing.
Setup & Software Installation
Participants will need to install Python on their device.
We will be using Python 3.7 and Jupyter notebooks throughout the workshop. The easiest way to install is via Anaconda https://docs.anaconda.com/anaconda/install/. We will also explore incorporating an IDE such as PyCharm https://www.jetbrains.com/pycharm/, please ensure you install this.
In addition to this, please make sure you install the following Python dependencies:
Matplotlib (Instructions https://matplotlib.org/3.1.1/users/installing.html )
Numpy (Instructions https://scipy.org/install.html )
Pandas (Instructions https://pandas.pydata.org/pandas-docs/stable/install.html)
Plotly (Instructions https://pypi.org/project/plotly/)
This workshop is designed for people with no background in Python.
You need to attend all 3 days. Different topics are covered each day and it builds on materials covered on the previous day, so if you miss a day, we won't have the resources to help you catch up in this online environment. To give you an idea of what's being covered each day, here is a very rough draft of the topics being covered each day. They will be refined each day as required.
Day 1 (June 28): Introduction and basic programming / Q & A
Day 2 (June 29): Data structures / Q & A
Day 3 (June 30): Python and data science: numpy, pandas and plotly / Discussion / Q & A