8 Best Books on Data Science with Python You Must Read in 2024

Best Books on Data Science with Python

Python is one of the most widely used programming languages in the data science field. Python has many packages and libraries that are specifically tailored for certain functions, including pandas, NumPy, scikit-learn, Matplotlib, and SciPy. So if you are looking for the Best Books on Data Science with Python, then you should check these books.

In this article, you will find 8 Best Books on Data Science with Python. These books will give you in-depth knowledge starting from basics to advanced level. Now without wasting your time, let’s start finding the Best Books on Data Science with Python

Best Books on Data Science with Python

1. Python Data Science Handbook

Python Data Science Book

Author- Jake VanderPlas

About Book-

For Data Science, a programming language is mandatory. Python is the most suitable programing language for Data Science. As a Data Scientist, most of the time, you have to work on Data manipulation and Data Cleaning. And you can perform these tasks with Pandas.

With this book, you’ll learn how to use:

  • IPython and Jupyter: provide computational environments for data scientists using Python
  • NumPy: includes the ndarrayfor efficient storage and manipulation of dense data arrays in Python
  • Pandas: features the DataFrame for efficient storage and manipulation of labeled/columnar data in Python
  • Matplotlib: includes capabilities for a flexible range of data visualizations in Python
  • Scikit-Learn: for efficient and clean Python implementations of the most important and established machine learning algorithms

You Should Read this Book, if-

  1. You want to learn Python Libraries for Data Science.

Where to Buy?

You can buy this book on Amazon- Python Data Science Handbook

2. Data Science from Scratch: First Principles with Python

Data Science from Scratch

Author– Joel Grus

About Book

As the book’s name sounds,” Data Science from Scratch”, this book is best for beginners. This book begins with very basics. And if you don’t have Python Knowledge, then also this is a good book for you.

In Data Science, knowledge of statistics, Linear Algebra, and Probability are mandatory. So this book will give you the basics of linear algebrastatistics, and probability. Along with that, you will understand how and when they’re used in data science.

The next skill for Data Science is Programming Language. So in this book, you will get a crash course in Python. And the next Skill for data science is Knowledge of Machine Learning. In this book, you will dive into the fundamentals of machine learning.

You will also learn how to implement models such as k nearest Neighbors, Naive Bayes, linear and logistic regression, decision trees, neural networks, and clustering.

Knowledge of Data Cleaning is also required for Data Science. In this book, you will learn how to collect, explore, clean, munge, and manipulate data.

In a nutshell, this book is an entry-level book for beginners.

You Should Read this Book, If-

  1. You are Beginner and don’t have any knowledge of Python or Statistics. Then you should definitely read this book.
  2. You want to learn the basics of Mathematics required for Data Science.

Where To Buy?

You can buy this book on Amazon- Data Science from Scratch or Download the Ebook here

3. Data Science Projects with Python

Data Science projects with python

Author–  Stephen Klosterman 

About Book

In this book, you will get practical guidance on industry-standard data analysis and machine learning tools by applying them to real data problems. This book covers pandas and Matplotlib concepts. And how to use them to critically examine datasets with summary statistics and graphs.

In this book, you will also learn how to use lasso and ridge regression to regularize your models. After reading this book, you will have a solid understanding of how to use machine learning algorithms to perform detailed data analysis and extract meaningful insights from unstructured data.

You Should Read this Book, If-

  1. You have some previous understanding of Python and you want a detailed walk-through of a Data Science project.
  2. And you are familiar with mathematical concepts such as algebra and basic statistics will also be useful.

Where To Buy?

You can buy this book on Amazon- Data Science Projects with Python

4. Python for Data Analysis

Python for Data Analysis

Author- Wes McKinney 

About Book-

This book is good for analysts, who are new to Python, and for Python programmers who are new to data science and scientific computing. This book will first teach you the basics of Python programming. Then it will cover Python’s role in data analysis and statistics. That’s why it is good for beginners in Python. After reading this book you can build real-world applications within a week.

Python for Data Analysis will also give you an idea of when you start working as a Data Analyst or scientist. You will learn basic and advanced features in NumPy (Numerical Python). Along with that, you will learn how to solve real-world data analysis problems with thorough, detailed examples.

You should read this book, if-

  1. You are analysts new to Python or Python programmers new to data science and scientific computing.

Where to Buy?

You can buy this book on Amazon-Python for Data Analysis

5. Python For Data Science

Author– Mr Ethan Williams 

About Book-

This is a comprehensive book for beginners to learn Python Programming for data science. In this book, you will learn Python libraries such as NumPy, Pandas, Matplotlib, and Seaborn for data analysis and visualization. This book has practical examples and applications for each lesson. In a nutshell, this book is good for data science beginners.

You should read this book, if-

  1. You are a Data Science Beginner.

Where to Buy?

You can buy this book on Amazon- Python For Data Science

6. Introduction to Machine Learning with Python

Author- Andreas C. Müller, Sarah Guido

About Book-

This book will start your Machine Learning Journey in Python. In this book, you will learn the fundamental concepts and applications of machine learning. Along with that, you will learn Advanced methods for model evaluation and parameter tuning.

This book also covers Methods for working with text data, including text-specific processing techniques.

You should read this book, if-

  1. You are a beginner in Machine Learning.
  2. Or you want to create a successful machine-learning application with Python and the scikit-learn library.

Where to Buy?

You can buy this book on Amazon- Introduction to Machine Learning with Python.

7. Python for Data Science For Dummies

This book is good for those who are new to data analysis. This book teaches the basics of Python data analysis programming and statistics. And you will also learn Google Colab and statistical concepts such as probability, random distributions, hypothesis testing, confidence intervals, and building regression models for prediction.

You should read this book, if-

  1. You have previous knowledge in Python and want to learn data analysis using Python.

Where to Buy?

You can buy this book on Amazon- Python for Data Science For Dummies

8. Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow

Author- Aurélien Géron

About Book-

This book gives you a hands-on approach to learning by doing. It starts with the more traditional ML approaches (the Scikit-learn part) giving you a great deal of context and practical tools for solving all kinds of problems. This book has an excellent balance between theory/background and implementation.

This practical book shows you how even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data.

This Book uses concrete examples, minimal theory, and two production-ready Python frameworks—Scikit-Learn and TensorFlow.

The first part of the book explains basic Machine Learning Algorithms. Support Vector Machine, Decision, Trees, Random Forests,  and many more. In this book, Scikit-learn examples for each of the algorithms are included.

In the second part, deep learning concepts through the TensorFlow library are explained.

You Should read this book, if-

  1. If you have basic programming knowledge.
  2. The one who is a beginner to Machine Learning and wants to start with the basics of coding.
  3. if you are interested in the popular scikit-learn machine learning library.

Where to Buy?

You can buy this book on Amazon- Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow

Conclusion

In this article, you have discovered the 8 Best Books on Data Science with Python. Have you Bought or Read anyone of these Books?. If yes then tell your experience in the comment section.

I hope these 8 Best Books on Data Science with Python will help you to begin and boost your Data Science Journey with Python.

Enjoy Learning!

All the Best!

Thank YOU!

Explore More about Data Science, Visit Here

Subscribe For More Updates!

[mc4wp_form id=”28437″]

Though of the Day…

It’s what you learn after you know it all that counts.’

John Wooden

Leave a Comment

Your email address will not be published. Required fields are marked *