Data visualization in python book

Data Visualization in Python — eBook Bundle

Data Visualization in Python with Matplotlib and Pandas is an eBook designed to take absolute beginners to Pandas and Matplotlib, with basic Python knowledge, and allow them to build a strong foundation for advanced work with these libraries — from simple plots to 3D plots and interactive buttons.

Through practical, hands-on, and straightforward examples, the eBook guides you through Data Visualization and Exploration using Python, Pandas, and Matplotlib. You’ll learn how to use the constituent elements of Pandas to load and manipulate datasets, as well as how to visualize them, gaining an understanding of the different styles of Matplotlib plotting and the anatomy of Matplotlib plots, before learning how to customize the elements to your liking. Furthermore, the eBook covers a great deal of different plot types, from simple Pie Charts and Bar Plots to 3D Surface Plots and Joint Plots. Each different plot type features a new dataset, containing different types of data you might want to visualize, guiding you through many unique aspects of Data Visualization.

It serves as an in-depth, guide that’ll teach you everything you need to know about Pandas and Matplotlib, including how to construct plot types that aren’t built into the library itself.

Data Visualization in Python, a eBook for beginner to intermediate Python developers, guides you through simple data manipulation with Pandas, cover core plotting libraries like Matplotlib and Seaborn, and show you how to take advantage of declarative and experimental libraries like Altair. More specifically, over the span of 11 chapters this eBook covers 9 Python libraries: Pandas, Matplotlib, Seaborn, Bokeh, Altair, Plotly, GGPlot, GeoPandas, and VisPy.

Each library has its own unique features and quirks, some related to each other, while some are based on completely different technologies and ideas. That being said, this eBook will act as a one-stop resource for learning the ins and outs of each, and getting acquainted with the landscape of visualization libraries in Python.

It serves as a unique, practical guide to Data Visualization, in a plethora of tools you might use in your career.

Bundled together, you’ll have solid knowledge of the landscape of Python’s visualization libraries, with practical experience in each, knowledge of when to use each one, and advanced knowledge of Pandas and Matplotlib — the de facto most popular Data Processing and Data Visualization libraries.

Free Updates and Additional Resources

At StackAbuse, we believe that learning is not a one-stop time investment. It’s life-long. Especially in the volatile and rapidly changing world of Computer Science and Software Engineering. So, we’ve pledged to update our eBook , guides, and other upcoming material to keep the pace of progress in the field. Software is updating — it’s only fitting that learning resources are updating as well. We’ll issue updates to both eBook as the libraries covered within them receive updates individually.

Additionally, we’ll issue resources, which aren’t long enough to warrant eBook of their own, through time in the form of detailed guides. One such guide — «Guide to Plotting Heatmaps in Seaborn», is included in the bundle for free, as other guides will be once released.

What Our Readers Think

«A very informative overview of many Python modules to visualize data!»

«This is the best all-in-one collection of data plotting techniques for Python, and a good Pandas reference as well. Great deskside reference. I highly recommend.»

«Great for beginners and hobbyists such as myself, who’d like to apply data visualization to their respective jobs, but also some intermediate folks. As a PM / PO, I routinely use various data visualization tools, but never did so programmatically. After recently picking up Python for a bit, the book was easy to follow and covered a lot of libraries, their distinctive features and advantages, as well as plot types.»

Money-Back Guarantee

We want to make sure you’re 100% happy with our books, so we’ll provide full refunds within 30 days of purchase, no questions asked. Simply reply to the download email with your refund request.

Additionally, if there is anything you dislike about the resources, please let us know, and we’ll do our best to improve the books in one of the frequent updates.

Who This Bundle is For

• Beginner to Advanced Python enthusiasts
• Aspiring Data Scientists, who are ready to jump into the world of Data Visualization
• Analysts, Product Managers, and Marketing Consultants who’d like to explore trends and adapt their strategies with empirical evidence
• The average Joe who’s interested in Data Visualization 😉

Prefer the Crinkle of the Paper?

If you prefer the crinkle of the paper, get our books on Amazon:

Book Bundle — Save 20%

A digital copy of «Data Visualization in Python», «Data Visualization in Python with Matplotlib and Pandas», and free «Guide to Plotting Heatmaps in Seaborn».

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README.md

Data Visualisation in Python

Authors: Sana Rasheed & Zeeshan-ul-hassan Usmani

Thank you for stepping into the domain of Data Analysis. This book will help you step in the field of Data Visualisation.

Code scripts are in Python programming language. The book images and code examples have shared in chapter-wise manner.

This book has been divided into 2 volumes:

1. Data Visualisation in Python — Plotly, Bokeh
2. Data Visualisation in Python — Altair, Select Right Chart Type

This repository consist of two folders based on defined volumes. The subsequent folder contains Python code scripts and images used in the book.

Pre-requisite: Python Programming Language

Happy Learning and Keep Practising!

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Data Visualization in Python

More specifically, over the span of 11 chapters this book will cover 9 Python libraries: Pandas, Matplotlib, Seaborn, Bokeh, Altair, Plotly, GGPlot, GeoPandas, and VisPy. Each library has its own unique features and quirks, some related to each other, while some are based on completely different technologies and ideas. That being said, this book will act as a for learning the ins and outs of each.

Whether you’re a student or a seasoned developer, this book aims to get you on board with the current landscape of Data Visualization libraries in Python and up to speed with some of the most popular and powerful tools out there.

Contents

• Introduction to Data Visualization
• Types of Plots
• Manipulating and Visualizing Data with Pandas
• Matplotlib
• Seaborn
• Bokeh
• Altair
• Plotly
• Ggplot
• GeoPandas
• VisPy

Over time we will continually update this book by fixing issues, updating information, adding new relevant content, etc. Have any feedback on what could be fixed/changed/added? Feel free to contact us!

Changelog

• Fixed image ordering issue in Chapter 9
• Fixed content rendering issue near end of Chapter 9 and start of Chapter 10
• Added ~50 pages through new in-depth examples, new datasets, and updates to existing examples
• Added new subsections «Change Tick Frequency», «Set Axis Range (xlim, ylim)», and «Bar Plots» to Chapter 4
• Updated «Histogram Plots» and «Scatter Plot» in Chapter 4
• Added new subsections «Violin Plots», «Bar Plots», and «Scatter Plots» to Chapter 5
• Updated «Distribution Plots» and «Pair Plots» in Chapter 5

FAQ

We want to make sure you’re 100% happy with the book, so we’ll provide full refunds within 30 days of purchase, no questions asked. Simply reply to the download email with your refund request.

Please reply to the download email with any issues you find with the book and we’ll correct it for the next update.

Purchasing this version gives you an individual license. If you’re interested in a group rate for a company, team, class, etc., please contact us.

You’ll get 2 PDFs and 2 EPUBs

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Data Analysis and Visualization Using Python

This is a preview of subscription content, access via your institution.

Table of contents (8 chapters)

Front Matter

Introduction to Data Science with Python

The Importance of Data Visualization in Business Intelligence

Data Collection Structures

File I/O Processing and Regular Expressions

Data Gathering and Cleaning

Data Exploring and Analysis

Data Visualization

Case Studies

Back Matter

About this book

Look at Python from a data science point of view and learn proven techniques for data visualization as used in making critical business decisions. Starting with an introduction to data science with Python, you will take a closer look at the Python environment and get acquainted with editors such as Jupyter Notebook and Spyder. After going through a primer on Python programming, you will grasp fundamental Python programming techniques used in data science. Moving on to data visualization, you will see how it caters to modern business needs and forms a key factor in decision-making. You will also take a look at some popular data visualization libraries in Python.

Shifting focus to data structures, you will learn the various aspects of data structures from a data science perspective. You will then work with file I/O and regular expressions in Python, followed by gathering and cleaning data. Moving on to exploring and analyzing data, you will look at advanced data structures in Python. Then, you will take a deep dive into data visualization techniques, going through a number of plotting systems in Python.

In conclusion, you will complete a detailed case study, where you’ll get a chance to revisit the concepts you’ve covered so far.

• Use Python programming techniques for data science
• Master data collections in Python
• Create engaging visualizations for BI systems
• Deploy effective strategies for gathering and cleaning data
• Integrate the Seaborn and Matplotlib plotting systems

Developers with basic Python programming knowledge looking to adopt key strategies for data analysis and visualizations using Python.

Keywords

• python
• data
• visualizations
• analysis
• bigdata
• datascience
• plotting
• collection

Authors and Affiliations

Higher Colleges of Technology, Abu Dhabi, United Arab Emirates

About the author

Dr. Ossama Embarak holds a Doctorate in Computer Science from the Heriot-Watt University in Scotland, UK. He has more than 2 decades of training and teaching experience with a number of programming languages including C++, Java, C#, R, and Python. He is presently the lead CIS Program Coordinator for Higher Colleges of Technology, UAE’s largest applied higher educational institution, with over 23,000 students attending campuses throughout the region.Recently, he got an interdisciplinary research grant of 199000 AED to implement a machine learning system for mining students’ knowledge and skills.

He has participated in many scholarly activities as a reviewer for journals in the field of computer and information sciences, artificial intelligence, mobile and web technologies. He has published numerous papers in datamining and knowledge discovery, and was also involved as a co-chair for the Technical Program Committee (TPC) for various regional and international conferences.

Bibliographic Information

• Book Title : Data Analysis and Visualization Using Python
• Book Subtitle : Analyze Data to Create Visualizations for BI Systems
• Authors : Dr. Ossama Embarak
• DOI : https://doi.org/10.1007/978-1-4842-4109-7
• Publisher : Apress Berkeley, CA
• eBook Packages : Professional and Applied Computing , Professional and Applied Computing (R0) , Apress Access Books
• Copyright Information : Dr. Ossama Embarak 2018
• Softcover ISBN : 978-1-4842-4108-0 Published: 20 November 2018
• eBook ISBN : 978-1-4842-4109-7 Published: 20 November 2018
• Edition Number : 1
• Number of Pages : XX, 374
• Number of Illustrations : 267 b/w illustrations
• Topics : Python , Open Source , Big Data

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