Python Data Visualization Essentials Guide: Become a Data Visualization expert by building strong proficiency in Pandas, Matplot,Used

Build your data science skills. Start data visualization Using Python. Right away. Become a good data analyst by creating quality data visualizations using Python.Key Features? Exciting coverage on loads of Python libraries, including Matplotlib, Seaborn, Pandas, and Plotly.? Tons of examples, illustrations, and usecases to demonstrate visual storytelling of varied datasets.? Covers a strong fundamental understanding of exploratory data analysis (EDA), statistical modeling, and data mining.DescriptionData visualization plays a major role in solving data science challenges with various capabilities it offers. This book aims to equip you with a sound knowledge of Python in conjunction with the concepts you need to master to succeed as a data visualization expert.The book starts with a brief introduction to the world of data visualization and talks about why it is important, the history of visualization, and the capabilities it offers. You will learn how to do simple Pythonbased visualization with examples with progressive complexity of key features. The book starts with Matplotlib and explores the power of data visualization with over 50 examples. It then explores the power of data visualization using one of the popular exploratory data analysisoriented libraries, Pandas.The book talks about statistically inclined data visualization libraries such as Seaborn. The book also teaches how we can leverage bokeh and Plotly for interactive data visualization. Each chapter is enriched and loaded with 30+ examples that will guide you in learning everything about data visualization and storytelling of mixed datasets.What you will learn? Learn to work with popular Python libraries and frameworks, including Seaborn, Bokeh, and Plotly.? Practice your data visualization understanding across numerous datasets and real examples.? Learn to visualize geospatial and timeseries datasets.? Perform correlation and EDA analysis using Pandas and Matplotlib.Who this book is forThis book is for all data analytics professionals, data scientists, and data mining hobbyists who want to be strong data visualizers by learning all the popular Python data visualization libraries. Prior working knowledge of Python is assumed.Table of Contents1. Introduction to Data Visualization2. Why Data Visualization3. Various Data Visualization Elements and Tools4. Using Matplotlib with Python5. Using NumPy and Pandas for Plotting6. Using Seaborn for Visualization7. Using Bokeh with Python8. Using Plotly, Folium, and Other Tools for Data Visualization9. Handson Examples and Exercises, Case Studies, and Further ResourcesAbout the AuthorsKallur Rahman is an IT industry leader with over 2 decades of experience in software development, testing, program/ project management, and management consultancy. He has been a developer, designer, technical architect, test program manager, delivery unit head, IT Services, and COE/Factory Services leader of various complexity spanning telecommunications, Life Sciences, Retail, and Healthcare Industries. He has a masters degree in Business Administration preceded by an Engineering degree in Computer Science. He has counseled CxO level executives in marketleading corporations for testing, business and technology transformation programs. As a thoughtleader, he is a frequent invitee at several industry events spanning technical and domainfocused themes.LinkedIn Bio: https://www.linkedin.com/in/kalilurrahman/