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

About the Author

Book Description

Transforming data into actionable insights using Python

Key Features

● Gain a comprehensive understanding of data visualization and exploratory data analysis (EDA) using Python.

● Discover valuable insights and patterns in data through visual analysis.

● Master the art of effectively communicating complex concepts by creating compelling and impactful data visualizations.

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).

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.

Table of Contents

1. Understanding Data

2. Data Visualization – Importance

3. Data Visualization Use Cases

4. Data Visualization Tools and Techniques

5. Data Visualization with Matplotlib

6. Data Visualization with Seaborn

7. Data Visualization with Bokeh

8. Exploratory Data Analysis

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