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Extra resources for Mastering Python Data Visualization
It is something that allows us to drill down and find more about the change in data. pdf by Ben Shneiderman. Sometimes, it is much harder to display everything on a single display and on a single scale, and only by experience, one can better understand these visualization methods. Summarizing further, visualization is useful in both organizing and making sense out of data, particularly when it is in abundance. Interactive visualization is emerging as a new form of communication, which allows users to analyze the information in order to construct their own, new understanding of the data.
One of the challenges is to ensure that the data is clean and subsequently, to reduce the dimensions so that unnecessary information is discarded. Visualization can be used wherever we see increased knowledge or value of data. That can be determined by doing more data analysis and running through algorithms. The data analysis might vary from the simplest form to a more complicated one. Sometimes, there is value in looking at data beyond the mean, median, or total, because these measurements only measure things that may seem obvious.
An artist paints a picture using tools and materials like brushes, and colors. Similarly, another artist tries to create data visualization with the help of computing tools. Visualization can be aesthetically pleasing and helps in making things clear; sometimes, it may lack one or both of those qualities depending on the users who create it. Today, there are over thirty different visual representations of data, each having a reason to represent data in that specific way. As the visualization methods progress, we have much more than just bar graphs and pie charts.