AAVSO How to [Python! Finding Frequency Solutions for Variable Star Light Curves]

AAVSO webinar, originally broadcast Oct. 1, 2022.
This is the second session in a three-part series. Basic knowledge of Python is assumed. If you've never used Python before, we recommend installing it and watching AAVSO's recording of the first session ("The Basics" • AAVSO How to [Python! ... ) before watching this one.
Many stars vary in brightness at one or many frequencies. Measuring these frequencies reveals valuable information about the physical properties of the observed systems. This tutorial demonstrates how to measure the frequencies (or periods) of variation in light curve data with the interactive Python package Pyriod. The tutorial will introduce periodograms, significance testing, and the iterative prewhitening algorithm for fitting signals to the data. Attendees will benefit from previous experience with light curves and Python, but this is not required to follow the presentation.
Dr. Bell works with time series photometry from surveys like TESS, Kepler, and the Zwicky Transient Facility. Dr. Bell is the author of the Python package "Pyriod for prewhitening frequency analysis of time series astronomical data."

[@brandlc]

Is the Python jupyter notebook refered to by Dr Bell available to download?

[@komalchand3705]

What if light curve is not there for any particular star. How to extract light curve in that case?