#1 About the book

This book comes from my experience teaching Python in a variety of settings and through different stages of its (and my) development. Much of the material has been taken from multiple drafts that I wrote on machine learning and data science as well as the Python Programming drafts too that I wrote through my blog. I’m looking forward to teaching Python to people as long as people will let me, and I’m interested in seeing how the next generation of students will approach it (and how my approach to them will change). Overall, it’s been just an amazing experience to see the widespread adoption of Python over the past decade. I’m sure the next decade will be just as amazing.

#2 How this book is Organized?

This book is not a part-based structured, it is an Iteration-based structured. Each Iteration is meant to teach you a specific thing in Data Science, for example:

1. Iteration One: Introduction to Data Science.
2. Iteration Two: Python.
3. Iteration Three: Jupyter.
4. Iteration Four: Numpy.
5. Iteration Five: Pandas.
6. Iteration Six: Matplotlib.
7. Iteration Seven: SKLearn.
8. Iteration Eight: Finals.

#3 Iterations Done So Far...

The book is on going progress, so we have done the first seven iterations out of eight, and soon will publish the third. Stay tuned for the sheets coming with the book and the updates with the latest tech...

#4 Updated Regularly???

If you bought one of my books, you will find that those books are updated monthly, based on calendar schedule, we do set the next book that will be updated. So, you should subscribe to the readers mail to get info about the next updated book.

You will learn that NumPy has very efficient arrays that are easy to use due to the powerful indexing mechanism. This book describes some of the more advanced and tricky indexing techniques.

Also we will try to make an attempt to document the most essential methods that every user should know. NumPy has many methods to even mention in this book!

The Goal.

The goal this weekend is to introduce a foundation of pandas by thoroughly inspecting the Series and DataFrame data structures. It is vital for pandas users to know each component of the Series and the DataFrame, and to understand that each column of data in pandas holds precisely one data type.

Also, you will learn how to select a single column of data from a DataFrame, which is returned as a Series. Working with this one-dimensional object makes it easy to show how different methods and operators work. Many Series methods return another Series as output. This leads to the possibility of calling further methods in succession, which is known as method chaining.

Welcome to the first book in this Week End Series, this series helped me a lot before, and I hope it helps you now.

And this book is about the techniques that you should learn Python, any data scientist, and not only data scientists, but every one that faces data problems, and dealing with data is on his/her job description should know how to explore data. I hope you find what you need in this book.

This book is written to help you learn Python programming FAST and learn it WELL. If you are an absolute beginner in Programming, you'll find that this book explains complex concepts in an easy to understand manner. Examples are carefully chosen to demonstrate each concept so that you can gain a deeper understanding of the language. If you are an experienced coder, this book gives you a good base from which to explore Python. The appendices at the end of the book will also provide you with a convenient reference for some of the commonly used functions in Python.

At the end of the series, you'll be guided through a project that gives you a chance to put what you've learned to use.

We will provide with this magazine all the codes, so you can download the source code of the sections and project too.

You can get the online version freely here

Welcome to the one of the middle books in this Week End Series, this series helped me a lot before, and I hope it helps you now.

And this book is about the techniques that you should learn Python, any data scientist, and not only data scientists, but every one that faces data problems, and dealing with data is on his/her job description should know how to explore data. I hope you find what you need in this book.