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Data Visualization with Python for Beginners: Visualize Your Data using Pandas, Matplotlib and Seaborn (Machine Learning & Data Science for Beginners)
Author(s): AI Publishing (Author)
- Publisher: AI Publishing LLC
- Publication Date: February 14, 2020
- Language: English
- Print length: 288 pages
- ISBN-10: 1733042687
- ISBN-13: 9781733042680
Book Description
Are you looking for a hands-on approach to learn Python for Data Visualization Fast?
Do you need to start learning Python for Data Visualization from Scratch?
This book is for you. This book works as a guide to present fundamental Python Libraries and a basis related to Data Visualization using Python. Data science and data visualization are two different but interrelated concepts. Data science refers to the science of extracting and exploring data in order to find patterns that can be used for decision making at different levels. Data visualization can be considered as a subdomain of data science where you visualize data with the help of graphs and tables in order to find out which data is most significant and can help in the identification of important patterns. This book is dedicated to data visualization and explains how to perform data visualization on a variety of datasets using various data visualization libraries written in the Python programming language. It is suggested that you use this book for data visualization purposes only and not for decision making. For decision making and pattern identification, read this book in conjunction with a dedicated book on machine learning and data science.We will start by digging into Python programming as all the projects are developed using it, and it is currently the most used programming language in the world. We will also explore the most-famous libraries for Data Visualization such as Pandas, Numpy, Matplotlib, Seaborn, etc .
What this book offers…
You will learn all about python in three modules, one for Plotting with Matplotlib, one for Plotting with Seaborn, and a final one Pandas for Data Visualization. All three modules will contain hands-on projects using real-world datasets and a lot of exercises.
Clear and Easy to Understand Solutions
All solutions in this book are extensively tested by a group of beta readers. The solutions provided are simplified as much as possible so that they can serve as examples for you to refer to when you are learning a new skill.
What this book aims to do…
This book is written with one goal in mind – to help beginners overcome their initial obstacles to learning Data Visualization using Python.A lot of times, newbies tend to feel intimidated by coding and data.The goal of this book is to isolate the different concepts so that beginners can gradually gain competency in the fundamentals of Python before working on a project.Beginners in Python coding and Data Science does not have to be scary or frustrating when you take one step at a time.
Ready to start practicing and visualizing your data using Python? Click the BUY button now to download this book
Topics Covered:
- Basic Plotting with Matplotlib
- Advanced Plotting with Matplotlib
- Introduction to the Python Seaborn Library
- Advanced Plotting with Seaborn
- Introduction to Pandas Library for Data Analysis
- Pandas for Data Visualization
- 3D Plotting with Matplotlib
- Interactive Data Visualization with Bokeh
Interactive Data Visualization with Plotly Hands-on Project Exercises
Click the BUY button and download the book now to start learning and coding Python for Data Visualization.
Editorial Reviews
Editorial Reviews
Review
Python has conspired to create a need for a new data and visual language. This book is expertly written to support the vast majority of us who have to present data before and without any Model. The book is organized into a series of chapters / use exercises and hands on project that enable you to zero in and get support for your processing challenge.
This Data Visualization book is Amazing, well written, and comprehensive in a way that’s very unusual for technical books
The world of data visualization has always been a bit bifurcated; you could look at wonderful pretty pictures of graphs and learn theory, or you could learn statistical software packages, but connecting the two was left as an exercise for the oft-confused reader. This book is beautiful, and full of exceptionally clear and practically useful graphs, but it also walks through all the steps of getting up and running with visual scientific communication, from installing Python through downloading data sets through plain-text manuscript generation. Every element of this book is an incredibly important component of what beginning researchers need to learn to communicate scientific ideas, and having them rolled into a single attractive and carefully composed package is a delight and fairly revelatory. I want — but realize I will not get — all technical books to find as elegant a balance as this one does.
Overall highly recommended for all beginners
**Reviewed By Bob Wilson a Data Scientist at Google (5 Stars)
What Usman provides in this book is an abundance of information, insights, and counsel that can help almost anyone to master the skills needed to visualize data using Python. in order to turn the data into information that can be used to drive better decision making and set up a great Machine Learning Model.
We need data visualization because a visual summary of information makes it easier to identify patterns and trends than looking through thousands of rows on a spreadsheet. It’s the way the human brain works. Since the purpose of data analysis is to gain insights, data is much more valuable when it is visualized. Even if a data analyst can pull insights from data without visualization, it will be more difficult to communicate the meaning without visualization. Charts and graphs make communicating data findings easier even if you can identify the patterns without them.
These are among the several subject of greatest interest and value to me:
- Plotting with Matplotlib
- Plotting with Seaborn
- Pandas for Data Visualization
- Interactive Data Visualization with Bokeh
At the end, I need only to let you know that Data visualization has become popular in recent years due to its power to display the results at the end of the machine learning process, but it is also increasingly being used as a tool for exploratory data analysis before applying machine learning models. At the beginning of the machine learning process, data visualization is a powerful tool (…)
**Reviewed by Jame Le Data Scientist (5 Stars)
Data Visualization with Python for Beginners is an “Excellent guide for beginners and experts alike”.
Its main goal is to introduce you to both the ideas and the methods of data visualization in a sensible, comprehensible, reproducible way.
Well, mission accomplished. The book is at once enormously readable, and sufficiently technically detailed as to make it easy to implement the principles introduced.
The book itself is also beautifully designed. The use of figures and margin notes give you a sense of being guided through the ideas rather than just being told what they are. I’ve had lots of fun going back to some of my own visualizations made with Pandas and improving them based on what I learned here.
I absolutely recommend this to beginners and experts alike. Healy gives you everything you’d need to know if you’re starting from scratch, but in such a way as to not slow things down for the more experienced reader.
