Practical Python Data Visualization: A Fast Track Approach to Learning Data Visualization with Python - Paperback
$70.18
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Who This Book Is For
Data Science enthusiasts and professionals, Business analysts and managers, software engineers, data engineers.
Practical Python Data Visualization: A Fast Track Approach to Learning Data Visualization with Python - Paperback
$70.18
by Ashwin Pajankar (Author)
Quickly start programming with Python 3 for data visualization with this step-by-step, detailed guide. This book's programming-friendly approach using libraries such as leather, NumPy, Matplotlib, and Pandas will serve as a template for business and scientific visualizations.
You'll begin by installing Python 3, see how to work in Jupyter notebook, and explore Leather, Python's popular data visualization charting library. You'll also be introduced to the scientific Python 3 ecosystem and work with the basics of NumPy, an integral part of that ecosystem. Later chapters are focused on various NumPy routines along with getting started with Scientific Data visualization using matplotlib. You'll review the visualization of 3D data using graphs and networks and finish up by looking at data visualization with Pandas, including the visualization of COVID-19 data sets.
The code examples are tested on popular platforms like Ubuntu, Windows, and Raspberry Pi OS. WithPractical Python Data Visualization you'll master the core concepts of data visualization with Pandas and the Jupyter notebook interface.
What You'll Learn- Review practical aspects of Python Data Visualization with programming-friendly abstractions
- Install Python 3 and Jupyter on multiple platforms including Windows, Raspberry Pi, and Ubuntu
- Visualize COVID-19 data sets with Pandas
Who This Book Is For
Data Science enthusiasts and professionals, Business analysts and managers, software engineers, data engineers.
Back Jacket
Quickly start programming with Python 3 for data visualization with this step-by-step, detailed guide. This book's programming-friendly approach using libraries such as leather, NumPy, Matplotlib, and Pandas will serve as a template for business and scientific visualizations.
You'll begin by installing Python 3, see how to work in Jupyter notebook, and explore Leather, Python's popular data visualization charting library. You'll also be introduced to the scientific Python 3 ecosystem and work with the basics of NumPy, an integral part of that ecosystem. Later chapters are focused on various NumPy routines along with getting started with Scientific Data visualization using matplotlib. You'll review the visualization of 3D data using graphs and networks and finish up by looking at data visualization with Pandas, including the visualization of COVID-19 data sets.
The code examples are tested on popular platforms like Ubuntu, Windows, and Raspberry Pi OS. With Practical Python Data Visualization you'll master the core concepts of data visualization with Pandas and the Jupyter notebook interface.
You will:- Review practical aspects of Python Data Visualization with programming-friendly abstractions
- Install Python 3 and Jupyter on multiple platforms including Windows, Raspberry Pi, and Ubuntu
- Visualize COVID-19 data sets with Pandas
Author Biography
Ashwin Pajankar holds a Master of Technology from IIIT Hyderabad, and has over 25 years of programming experience. He started his journey in programming and electronics at the tender age of 7 with BASIC programming language and is now proficient in Assembly programming, C, C++, Java, Shell Scripting, and Python. Other technical experience includes single board computers such as Raspberry Pi and Banana Pro, and Arduino.
He is currently a freelance online instructor teaching programming bootcamps to more than 60,000 students from tech companies and colleges. His Youtube channel has an audience of 10000 subscribers and he has published more than 15 books on programming and electronics with many international publications.
Number of Pages: 160
Dimensions: 0.38 x 9.21 x 6.14 IN
Illustrated: Yes
Publication Date: October 25, 2020
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