The analysis and interpretion of data that originates from our surroundings and environment is a topic of increasing interest. Such data is now an established part of our everyday lives, ranging from that collected about our climate to data acquired during smart manufacturing processes. The quantity of data allows us, in theory, to characterize any phenomenon. However, dealing with it requires the mastery of many skills, both theoretical and practical. Here we examine some of these techniques and make use of Python for the analysis of this real-world data.