Data Scientists all around the world are loving the wonders Python can do. It is a universal programming language that can systematize all the tiring jobs that they do. To make it even better, Python has essential data scientist elements such as analytics, algorithms, and data visualization libraries. If you are looking to learn Python from scratch or as an expert, consulting books should be your first choice for a quick go-to resource on nearly any topic. We have gathered the best five Python books for Data Scientists and Data Analysts – primarily from the O’Reilly book collection.
This book for Data Scientists is a complete guide on collecting, processing, cleaning, and manipulating the data. Python for Data Analysis covers the domain of applications requiring lots of data. Also, it brilliantly introduces the problems related to data analysis. Gathering the reviews globally, this Python book for Data Scientists has proved to be the best Python book for understanding various tools.
The book covers the fundamental concepts such as time series and data aggregations that every Data Scientist should know. For analyzing the data successfully, it has mentioned some excellent way outs. Moreover, this Python book for Data Scientists is written in easy and understandable English.
Researchers and professional programmers may also opt for this book for learning purposes and reference material – particularly for simple usage of the Pandas Python library. And, even if you consider yourself already well-versed with Pandas, you may also find something new in this book as new editions are regularly published. Also, Data Scientists will be able to apply Pandas in the real world through basic Python exercises. This is the best part of this Python book for Data Scientists. In a nutshell, it teaches you to use your skills and solve real work with Pandas too.
You should opt for this Python book for Data Scientists if you are planning to solve critical data questions. It will improve your Python expertise both as an expert or an amateur. Python Machine Learning is a combination of theory and practice with lots of well-explained coding examples. The book has codes that revolve around various algorithms and machine learning techniques as well as guides on improving your code.
This one of the five Python books for Data Scientists covers all the basic concepts of machine learning that they should know. For instance, it explains how to train Artificial Neural Networks (ANN) for various applications. You will know how to use regression analysis to forecast continuous response values. Also, you will learn to discover the patterns in your data through data clustering and pre-process the data before training.
Python Machine Learning is one of the first books to devote a whole chapter to Theano library of Python. Theano is particularly good if you are utilizing GPU computing. Furthermore, the book also briefly discusses Keras, the latest library of Python, for quickly prototyping and building ANN. We are positive that this Python book for Data Scientists will surely advance your knowledge. The corresponding book codes can be found on the author’s GitHub repository.
Data Scientists and developers across the globe have found this to be quite helpful in understanding the core Python library when getting started. The book has step-by-step directions on basic programming techniques that build on each other throughout the book. Further, you will find practice questions and challenges that ask you to improve the efficiency of your code. Data analysts can flawlessly systematize their algorithms once they have gone through this book.
Automate the boring stuff with Python delivers easy automatic hints that can assist Data Scientists with their daily work. It also provides an opportunity for Data Analysts who have to handle lots of data and do their analysis. This Python book for Data Scientists makes you develop real-world useful tools that you may use daily. The author doesn’t skip any crucial points and perfectly bridges your skills and the concepts for real examples.
All Data Scientists would agree that this is a must-have reference Python book for them. It is a precise and crystal-clear Python book for Data Scientists to understand the applications of many different approaches to common data problems. Moreover, it covers how Python can do data processing, analysis, and visualization. This is a big plus as a lot of work in Data Science is about data processing, preprocessing, data transformation, and data interpretation. However, you may feel that the book doesn’t go into detail about each topic.
This Python book for Data Scientists has everything from IPython, Pandas, Numpy, Scikit-Learn, and Matpotlib. The book has code written for Jupyter Notebooks, so you can easily test them. We would recommend this book for anyone who is a beginner in the field of Data Science or Python.
This is the last Python book for Data Scientists that we recommend. It revolves around more advanced concepts of machine learning, data science, and deep learning. In the beginning, this Python book for data scientists introduces basic subjects such as k-nearest neighbors and Linear regression. Then, it takes you deeper into the world of deep neural networks.
Again, this book has well-explained perfect real-world examples which would help you master your Python skills. We would recommend you to go for this book if you already have some concepts related to Machine Learning covered in the Python Machine Learning book covered earlier
These are the Best must have five Python books for Data Scientists and Analysts. Even if you are taking some online courses to build up your skills, you should consult these books as holistic and portable reference guides. They may also help you in solving the exercises of your online courses. You can master Python if you know the right book to read. Tell us in the comments below if these are the books that you have been looking for all along.