In this post, we have prepared a curated top list of reading recommendations for beginners and experienced. This hand-picked list of the best Pandas books and tutorials can help fill your brain this July and ensure you’re getting smarter. We have also mentioned the brief introduction of each book based on the relevant Amazon or Reddit descriptions.
- Python for Data Analysis (2012)
- Pandas Cookbook (2017)
- Learning Pandas – Python Data Discovery and Analysis Made Easy (2015)
- Pandas for Everyone: Python Data Analysis (Addison-Wesley Data & Analytics Series) (2018)
- Python Data Science Handbook: Essential Tools for Working with Data (2016)
- Python for Data Science For Dummies (For Dummies (Computer/Tech)) (2015)
- EJB 3 in Action (2014)
- Cython (2015)
Python for Data Analysis (2012)
Python for Data Analysis is concerned with the nuts and bolts of manipulating, processing, cleaning, and crunching data in Python. It is also a practical, modern introduction to scientific computing in Python, tailored for data-intensive applications. This is a book about the parts of the Python language and libraries you’ll need to effectively solve a broad set of data analysis problems. This book is not an exposition on analytical methods using Python as the implementation language.
Author(s): Wes McKinney
Pandas Cookbook (2017)
Pandas is one of the most powerful, flexible, and efficient scientific computing packages in Python. With this book, you will explore data in pandas through dozens of practice problems with detailed solutions in iPython notebooks. This book will provide you with clean, clear recipes, and solutions that explain how to handle common data manipulation and scientific computing tasks with pandas. You will work with different types of datasets, and perform data manipulation
Author(s): Theodore Petrou
This learner’s guide will help you understand how to use the features of pandas for interactive data manipulation and analysis.
Author(s): Michael Heydt
The Hands-On, Example-Rich Introduction to Pandas Data Analysis in Python. Today, analysts must manage data characterized by extraordinary variety, velocity, and volume. Using the open source Pandas library, you can use Python to rapidly automate and perform virtually any data analysis task, no matter how large or complex.
Author(s): Daniel Y. Chen
For many researchers, Python is a first-class tool mainly because of its libraries for storing, manipulating, and gaining insight from data. Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them all—IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other related tools.
Author(s): Jake VanderPlas
Unleash the power of Python for your data analysis projects with For Dummies! Python is the preferred programming language for data scientists and combines the best features of Matlab, Mathematica, and R into libraries specific to data analysis and visualization. Python for Data Science For Dummies shows you how to take advantage of Python programming to acquire, organize, process, and analyze large amounts of information and use basic statistics concepts to identify trends and patterns.
Author(s): John Paul Mueller, Luca Massaron
Author(s): Kyran Dale
EJB 3 in Action (2014)
Building on the bestselling first edition, EJB 3 in Action, Second Edition tackles EJB 3.2 head-on, through numerous code samples, real-life scenarios, and illustrations. This book is a fast-paced tutorial for Java EE 6 business component development using EJB 3.2, JPA 2, and CDI. Besides covering the basics of EJB 3.2, this book includes in-depth EJB 3.2 internal implementation details, best practices, design patterns, and performance tuning tips. The EJB 3 framework provides a standard way
Author(s): Debu Panda, Reza Rahman
Build software that combines Python’s expressivity with the performance and control of C (and C++). It’s possible with Cython, the compiler and hybrid programming language used by foundational packages such as NumPy, and prominent in projects including Pandas, h5py, and scikits-learn.
Author(s): Kurt W. Smith
Best Pandas Books You Must Read
We highly recommend you to buy all paper or e-books in a legal way, for example, on Amazon. But sometimes it might be a need to dig deeper beyond the shiny book cover. Before making a purchase, you can visit resources like Library Genesis and download some Pandas books mentioned below at your own risk. Once again, we do not host any illegal or copyrighted files, but simply give our visitors a choice and hope they will make a wise decision.
Pandas 1.x Cookbook: Practical recipes for scientific computing, time series analysis, and exploratory data analysis using Python
Author(s): Matt Harrison, Theodore Petrou
ID: 2479051, Publisher: Packt Publishing, Year: 2020, Size: 5 Mb, Format: pdf
Pandas 1.x Cookbook: Practical recipes for scientific computing, time series analysis, and exploratory data analysis using Python, 2nd Edition
Author(s): Matt Harrison, Theodore Petrou
ID: 2534258, Publisher: Packt Publishing, Year: 2020, Size: 6 Mb, Format: epub
Thinking in Pandas: How to Use the Python Data Analysis Library the Right Way
Author(s): Hannah Stepanek
ID: 2534409, Publisher: Apress, Year: 2020, Size: 2 Mb, Format: pdf
Please note that this booklist is not definite. Some books are absolutely record-breakers according to The New York Times, others are drafted by unknown writers. On top of that, you can always find additional tutorials and courses on Coursera, Udemy or edX, for example. Are there any other relevant links you could recommend? Drop a comment if you have any feedback on the list.