Kalilur Rahman - Python Data Visualization Essentials Guide

My family and teachers

My wonderful spouse and the two angelic daughters who make me a complete human. A special dedication to all great mentors, teachers, professionals, and all the wonderful innovators, authors, and leaders who make this world a better place!

Kalilur Rahman has a Master's Degree in Business Administration, preceded by an Engineering Degree in Computer Science and over two decades of experience in software development, testing, program/ project management, and management consultancy. Kalilur has been a developer, designer, technical architect, test program manager, delivery unit head, IT services, and COE/factory services head of varying complexity across telecommunications, life sciences, retail, and healthcare industries. Kalilur has advised CXO-level leaders in market-leading firms for testing, business, and technology transformation programs. As a thought-leader, Kalilur is a regular invitee at many industry events across technology and domains.

Kalilur is a firm believer in "knowledge is power" and is passionate about writing and sharing his knowledge. Kalilur is an active member of various technical and professional forums and contributed to internal improvement initiatives in the organizations he worked for. Kalilur has varied interests includes technology, testing in the digital world, artificial intelligence, machine learning, DevOps, continuous delivery, agile, mobility, IoT, and analytics. He is a regular contributor at LinkedIn a site for professionals and has over 800,000+ followers at the time of publishing. He has published over 200 articles across LinkedIn, DevOps.Com, and other leading magazines.

Kalilur is also an active quizzing enthusiast who participates and contributes at corporate level quizzing at competitive and information levels.

First and foremost, I would like to thank my family for supporting me in this journey to write this book. I would like to thank everyone at BPB Publications for giving me this opportunity to publish this book and helping me keep focused on the goal, and supporting me along the way.

I would also like to thank my colleagues and extended professional community for giving me endless support and resources to write this book. My learning from all the teachers (upwards, peers, subordinates, and industry experts) has been phenomenal and helpful in quenching a little bit of my thirst for knowledge and sharing the same with extended readers.

I would like to thank all the life-long learners like me who have an insatiable thirst for knowledge that permits people like me to embark on a journey of knowledge sharing and wisdom searching and making ourselves better.

I would be missing my duty if I did not thank all the wonderful people at BPB publications who made this book a reality. This includes the management team (Nrip Jain and others), the acquisition Editor, who persistently reached out to me to get this book going, the content editor who was very methodical, meticulous, friendly, and strict to make sure that tasks were done on time and for brilliant inputs to chisel the book for the first draft. My wonderful technical editor's technical prowess and attention to detail made this a better book to read. The copyediting team did a fantastic job in building the final version of the book, and the entire marketing and management team from BPB made a wonderful effort to get the best out of this book.

Lastly, I would like to thank my critics, my mentors, and my guides. Without their criticism, feedback and inputs, I would never be able to write this book.

- Kalilur Rahman

Over the past Techade (a NASSCOM term for the decade 2011-20), data science has been very popular and has a key focus area for technologists. Leading technology giants, massively successful startups, and software product engineering companies have leveraged the power of data science to build great products and services. One of the key elements for the success of data science and big data analytics is the growth in the tools and features to make complex tasks simple and the growth in computing infrastructure. Data visualization is one key concept used for various core aspects of data science in a very intelligent and simple way.

Python has opened the doors for making data visualization simple by exponentiating resourceful libraries to automate various visualization needs. Complexities such as the need to visualize complex data sets and data types are addressed by various libraries efficiently using Python. With an easy-to-adapt framework and architecture, Python automation offers the capability to write good visualization with a few lines of code. Python offers several benefits when it comes to data visualization.