Pandas is a powerful, popular Python package for cleaning, manipulating, and statistically analyzing large tabular data sets. It is particularly useful in preparation for AI/ML applications and publication-ready visualization. Originally developed for financial panel data, it is now used by data scientists in a huge variety of fields, from marketing to medicine to astronomy. Pandas is capable of handling data sets of several Gigabytes.
This course will introduce:
- core Pandas data types
- basic input/output routines
- data selection and filtering
- data inspection and cleaning methods
- built-in and user-defined functions for data manipulation
- memory saving datatypes
- multithreading methods
- built-in visualization methods
There will be a mix of static examples and live demonstrations via Jupyter notebook, and exercises will be provided to complement the lecture materials.
This course is part of NAISS training: https://www.naiss.se/training/
Prerequisites
Participants should be comfortable with Python, in particular NumPy and string methods. A very basic grasp of Matplotlib is also expected. Familiarity with the Python datetime module will be a plus in the time series section, but is not required.
For the hands-on exercises, access to a laptop or desktop computer with a working Python 3.6 or better installation is required. Any Python installation with NumPy, Matplotlib and Pandas should work as well. Further instructions will be shared with registered participants closer to the event.
Instructor
Rebecca Pitts (NAISS and LUNARC application expert, PhD in Astronomy) will be the principal instructor.
Location
The course is online. Registered participants will be provided with a zoom-link before the event.
Date & Times
10 - 11 March 2026, with the same schedule on both days:
Schedule
- Morning lecture block – 10:00-10:45
- Morning exercise block – 11:00-12:00
- Afternoon lecture block – 13:00-13:45
- Afternoon exercise block – 14:00-15:00
Registration
Registration will close on 27th February 2026.
Please use the registration form: https://survey.mailing.lu.se/Survey/62542 to register for the event.
Comments/Questions
For comments and questions, please Comments and questions on these training events should be sent to NAISS using the support form in SUPR: https://supr.naiss.se/support/.