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Introduction to Pandas for data science, 13 - 14 May 2024

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 the 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, hierarchical data structures, and some 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.


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. Pandas comes standard with the Anaconda3 distribution.   Any alternative Python installation with NumPy, Matplotlib and Pandas should work as well.  Further instructions will be shared with registered participants closer to the event.


Rebecca Pitts (application expert at LUNARC, PhD in Astronomy) will be the principal instructor.


The course is online.  Registered participants will be provided with a zoom-link before the event.

Date & Times

13 - 14 May 2024, with the same schedule on both days:


  • 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


Please use the registration page to register for the course.


For comments and questions, please contact LUNARC support

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