7 Best Python Pandas Books for Data Analysis – 5th One Will Amaze You!
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Python Pandas are an essential resource when it comes to data science. One simply can’t think to start learning data analysis without having a grasp over pandas. But to have a good grasp over the pandas’ library, you need useful resources. And nothing beats a good old book when it comes to learning something. So in this tutorial, we have assembled for you “7 Best Pandas Books”.
Whether you are a beginner or an experienced programmer, we will provide you with a list of books suitable for both the categories. This article will surely help you in finding the perfect book for yourself.
So, are you ready to explore the list of Python Pandas Books? Let’s start.
Top Pandas Books for Data Science & Data Analysis
Below, you will find a list of the best books to learn Pandas which are easily available online.
1. Python for Data Science For Dummies
By Luca Massaron and John Paul Mueller
Almost every pedagogue has come across the “For Dummies” series while trying to teach themselves virtually anything. This series provides very comprehensive teaching and is mainly focussed towards novices who aren’t adept with the subject at all. The best part about “Python for Data Science For Dummies” is the fact that it not only helps readers understand the intricacies of Pandas, but also give them an in-depth guide to learn other libraries needed for Data Science too, like Numpy, SciPy, BeautifulSoup, and MatPlotLib. With the help of this Pandas book, you will not only master Pandas but also make yourself an expert in Data Science, which the book rightly terms as “The Sexiest Job of the Century.”
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2. Python for Data Analysis
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This Python Pandas book is the ultimate guide for anyone trying to become the ultimate user of Pandas. Why is that? Simply because it is written by the creator of the Pandas project, himself. This makes the book one of the best books to learn Pandas, but it comes at a certain price. The sheer amount of technical knowledge may be difficult for people to take in and understand. Therefore, it is not recommended for absolute beginners, but for people who are a little experienced.
3. Learning Pandas – Python Data Discovery and Analysis Made Easy
By Michael Heydt
Learning Pandas is another beginner-friendly book which spoon-feeds you the technical knowledge required to ace data analysis with the help of Pandas. One of the best attributes of this pandas book is the fact that it just focuses on Pandas and not a hundred other libraries, thus, keeping the reader out of confusion and proclaiming itself as one of the best books to learn Pandas. The book effectively guides you through installing the library, creating complex data structures, deriving data from the internet, and finally visualizing your results with the help of plots and graphs. The learning curve is not steep, and thus, it attracts a lot of beginners.
4. Learning the Pandas Library
By Matt Harrison
Simple, accurate and versatile are the best terms to describe this book. Hailed as one of the best books to learn Pandas, this book is comparatively lightweight when compared to the other books on the list. It is not a data-heavy book but provides the user with a glimpse of the real power vested by the Pandas library. While the fact that it’s a relatively lightweight book may disinterest many, they will all be missing out on a lot since the book while being lightweight is very to-the-point. Meaning that it is perfect for people who want to get the basics of Pandas clear as soon as possible without wasting time beating about the bush. The book has thorough coverage of Pandas DataFrame and the various activities one can perform with the help of DataFrames.
5. Pandas Cookbook
By Theodore Petrou
This book can be termed as the perfect reference book. While all other Pandas books are competing to be considered ‘the best book for learning Pandas’ try to give you comprehensive knowledge of the library, this book acts as a compulsory companion to all those books. With more than 95 recipes to showcase the power of the library, readers will be able to analyze data like never before. The book empowers you with the knowledge of solving huge computing problems, create complex data structures, get more meaning out of your data, and much more.
6. Pandas for Everyone: Python Data Analysis
By Daniel Y. Chen
Do you want to get into Data Analysis, but you don’t even have background knowledge of Python? Worry not, this pandas book will solve everything. Why waste money on another book for python, when you can have the knowledge required to code in python and Pandas on the same book? This book is aimed at absolute beginners who have zero programming knowledge. It picks you up, guides you and channels your mind to know exactly what needs to start Data Analysis with Python and Pandas. As the title of the book states, it is for everyone. This makes it a definite pick to be one of the best books to learn Pandas.
7. Hands-On Data Analysis with NumPy and Pandas
By Curtis Miller
This pandas book is a slightly tougher book to get your mind around, and it’s recommended that one has a slight knowledge of Pandas and NumPy before starting on the book. Setting that aside, this book is very comprehensive and provides its readers with the experience of not only Pandas but also NumPy. While imparting the basic knowledge of Pandas, it also gives readers the knowledge of creating hierarchical indexes with DataFrames and plot that too. This book might not be beginner friendly, but that doesn’t keep it from being one of the best books to learn Pandas.
Summary
From the above Python Pandas books, now you can select, which one is best suitable for you. The list aims at saving your time and bringing you the list of best books to learn Pandas so that you don’t have to waste time elsewhere. So what are you waiting for, take up the book you like the most and start your journey into the land of Data Analysis with Pandas!
Hope, you liked the explanation. You may also like to know about different types of Python libraries.
Also, if you have any queries, feel free to comment.
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