Processing and Visualization of Collected Data Based on Open-Source Tools and Principles

This paper demonstrates the use of opensource tools and libraries to process collected data and visualize analysis. These data were collected using a built-in assembly with a GPS receiver and an Arduino microcomputer, and in a second example with the help of a mobile device and a free Phyphox app. Using the Python programming language, the Matplotlib, NumPy and Pandas libraries analysis and visualization the collected data are made within the Jupyter notebook. In this paper, we demonstrate how it is possible to do a simple data analysis and apply it for learning purposes, but also in further research. Different graphical data representations are used in the paper to demonstrate the importance of the correct representations selected for different types of data. In an age when the amount of data collected is growing exponentially, it is important to be able to extract useful information from them, to make the data analysis results as accurate as possible. The complete software part of the work was created using an open-source tool and all the details and results of this work are freely available on GitHub
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