This is a public repository of resources, designed and developed by Dr. Eugenio Tufino (Uni Trento, www.unitn.it) and Micol Alemani for the Physics Lab Course taught by Dr. Micol Alemani at University of Potsdam (www.physik.uni-potsdam.de/) in November 2022.

Reference: E Tufino, S Oss and M Alemani , Integrating Python data analysis in an existing introductory laboratory course, European Journal of Physics, 2023, https://iopscience.iop.org/article/10.1088/1361-6404/ad4fcc/meta

Python Data Analysis curriculum

This curriculum has been integrated into the introductory laboratory course at the University of Potsdam, focusing on Python for data analysis.

Repository Structure

Note: All files are provided with an English version, denoted by the suffix _EN. Files available in German are marked with the _DE suffix.

Getting_Started

This folder contains four Jupyter Notebooks that introduce the fundamental lab computational concepts within the course:

First Laboratory Session: Explore various Jupyter Notebook platforms and their setup procedures. Gain an understanding of basic calculations, text formatting, LaTeX usage, and simple plot creation.

Second Laboratory Session: This session focuses on scientific libraries, manipulate Pandas dataframes, conduct linear fits, and investigate statistical measures such as χ² and r². Introduction to creating histograms.

Application_Examples

This folder contains five Jupyter Notebooks, to use Use Python to investigate real-world physics phenomena:

Analyze sunspot time-series data using the moving average. Examine the relationship between light source illuminance and distance. Create histograms to explore the oscillation period of a pendulum. Simulate parabolic motion. Visualize atmospheric CO2 data from online sources.

Additional_Techniques

Two Jupyter Notebooks to improve the skills on importing and manipulating data files across diverse platforms, including Jupyter Lab-Anaconda, Google Colab, and direct internet sources.

Exercises_Start_Second_Semester

This folder contains exercises and data files used in the assessment at the beginning of the second semester.

License

This work is distributed under the Creative Commons Attribution 4.0 International. You are free to copy and redistribute the material in any medium or format, remix, transform, and build upon the material for any purpose, even commercially.

The above rights are are granted if you give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.