Book Image

Mastering Python Data Visualization

Book Image

Mastering Python Data Visualization

Overview of this book

Table of Contents (16 chapters)
Mastering Python Data Visualization
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
Index

Summary


The examples shown so far are just to give you an idea of how one should think and plan before making a presentation. The most important stage is the data familiarization and preparation process for visualization. Whether one can get the data first or shape the desired story is mainly influenced by exactly what outcome is attempted. It is like the "chicken and the egg" situation—does data come first or the focus? Initially, it may not be clear what data one may need, but in most cases, after a few iterations, things will be clear as long as there are no errors in the data.

Transform the quality of data by doing some cleanup or reducing the dimensions (if required), and fill gaps if any. Unless the data is good, the efforts that one may put into presenting it visually will be wasted. After a reasonable understanding of the data is achieved, it makes sense to determine what kind of visualization may be appropriate. In some cases, it would be better to display it in several different ways to see the story clearly.