Data Visualization with Python: Exploring Matplotlib, Seaborn, and Bokeh for Interactive Visualizations

Transforming data into actionable insights using Python. Description: Python is a popular programming language for data visualization due to its rich ecosystem of libraries and tools. If you're interested in delving into data visualization in Python, this book is an excellent resource to begin your journey. With Matplotlib, you'll master the art of creating a wide range of charts, plots, and graphs. From basic line plots to complex 3D visualizations, you'll learn how to transform raw data into engaging visuals that tell compelling stories. Dive into Seaborn, a high-level library built on top of Matplotlib, and discover how to effortlessly create beautiful and informative statistical visualizations effortlessly. From heatmaps to distribution plots, you'll unleash the full potential of Seaborn in your data analysis endeavors. Lastly, you will learn how to unleash the true potential of Bokeh and create compelling data visualizations that allow users to explore and interact with data dynamically. By the end of the book, you will have acquired the knowledge and skills necessary to create a diverse range of visualizations proficiently. What you will learn: - Utilize Matplotlib, Seaborn, and Bokeh to produce visually captivating visualizations. - Gain expertise in various types of charts, plots, and graphs. - Craft visually appealing and informative statistical visualizations. - Construct interactive and adaptable plots using Bokeh. - Explore various techniques for conducting Exploratory Data Analysis (EDA). The main objective of this book is to provide knowledge on using python libraries for data visualization. Data visualization is the process of creating visual representations of data in order to gain insights and better understand the data. It is a powerful tool for exploring and analyzing data, as it allows us to quickly identify patterns and trends. Data visualization can be used to create charts, graphs, maps, and other visualizations that can help us better understand the data. Data visualization can also be used to communicate data-driven stories and insights to a wider audience. This chapter presents various functions available in the Matplotlib library of python which are used for presenting data in graphical representations. Matplotlib is a comprehensive library for creating static, animated, and interactive visualizations in Python. With this library you can create and design from basic plots to three dimension (3D) plots. However, before plotting you need to understand the dataset, we will work on exploratory data analysis in the last chapter of this book, wherein we will learn to find the insights of data for better understanding. Who this book is for: This book caters to a wide audience, including undergraduate and postgraduate students, researchers, data managers, and data analysts. It presents an all-encompassing exploration of data visualization, equipping you with the essential groundwork to progress as a data-driven professional.