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Exploratory Data Analysis: Radiation Monitoring with Python and Geiger Counter
Collecting and Processing of the Geiger–Müller Tube Data
Most people probably never thought about it, but the background radiation always surrounds us. Its sources may vary, from natural components like uranium, thorium, or radon to nuclear accidents or cosmic rays from space. The radiation level is never zero, and charged particles fly through your body even now when you’re reading this text.
How large is the background radiation level, and are there any fluctuations in it? Can we find any patterns using exploratory data analysis and data science tools like anomaly detection? Are there any changes in the radiation level caused by the sun or atmospheric events such as wind or rain? There are many questions, and the best way to figure them out is to try! In this article, I will show how to collect the radiation data using the Geiger counter and a Raspberry Pi and how to process this data using Python and Pandas. For those who would like to use the same data, a link to a Kaggle dataset is at the end of the article.
Let’s get started!
1. Hardware
Many data processing applications nowadays run in the cloud. However, if we want to work with sensors and IoT, we need to…
