Updated 2020-09-07

Python 101: Intro to Data Analysis with NumPy

PACE’s Python 101: Intro to Data Analysis with NumPy introduces PACE users to analyzing scientific and engineering data using Python in a Hands-On course.

Instruction focuses on basic Python skills and key features of the NumPy and Matplotlib libraries through a data analysis example. The course is taught through a Jupyter Notebook, and participants will have multiple opportunities for hands-on exercises throughout the session. The workshop will also cover the mechanics of setting up a Jupyter Notebook on the PACE cluster.

Those with no experience on the command line are encouraged to attend Linux 101 prior to taking this course. No prior knowledge of Python is expected or assumed.

This course is recommended for anyone new to Python and NumPy, especially if you are a PACE user.

Please contact PACE support (pace-support@oit.gatech.edu) if you have any questions or concerns.

Upcoming Course Offerings

Fall 2020 Sessions

  • Thursday, September 10, 10:30AM - 12:15PM via BlueJeans. Register in advance here. Registrants will be sent the BlueJeans link on the day prior to the workshop.

  • Tuesday, October 13, 2:00 - 3:45PM via BlueJeans. Register in advance here. Registrants will be sent the BlueJeans link on the day prior to the workshop.

  • Wednesday, December 9, 2:00 - 3:45PM via BlueJeans. Register in advance here. Registrants will be sent the BlueJeans link on the day prior to the workshop.

We can only offer 30 seats per session due to space limitations. If you have registered but cannot attend, please contact Wansley Dennis (via 404-894-2249 or wansley.dennis@orgdev.gatech.edu) to cancel your registration.

Course Info

Format: 105 minutes of presentation, with 4 hands-on exercises spread throughout the session.

This course is taught on PACE-ICE, PACE's Instructional Cluster Environment.

Download the hands-on content here if you do not have access to PACE or PACE-ICE: Hands-on.

Warning

This is a hands-on workshop, so you must bring a laptop with you. To fully benefit from this course, users should have an active PACE-ICE account created by registering for this course. It is possible to complete the hands-on exercises on your local machine with an Anaconda installation.

At the beginning of the class, connect to PACE-ICE and run Jupyter, using these instructions.

Running Python on your local machine

You may wish to run Python on your personal computer. To do so, we recommend that you install Anaconda on your laptop.

You can run the workshop materials and Python on your personal computer using Anaconda. Please visit Anaconda and download the software for Mac, Linux, or Windows. Choose the Python 3.7 version. After downloading, please follow the installation instructions. Once installation is complete, open the Anaconda Navigator and choose Jupyter notebook. A browser window should open and load a Jupyter home page.

If you already have Anaconda for Python 2, visit this site for instructions on adding Python 3 support.

Steps to take after class

Use page 2 of these instructions, which detail how to set up Anaconda on PACE, how to copy files from PACE-ICE to PACE, and how to copy files from PACE-ICE to your local machine.