Python Pandas for Beginners: Pandas Specialization for Data Scientist

Python Pandas for Beginners: Pandas Specialization for Data Scientist





Python Pandas for Beginners: Pandas Specialization for Data Scientist

by AI Publishing

  • Length: 268 pages
  • Edition: 1
  • Language: English
  • Publisher: AI Publishing LLC
  • Publication Date: 2022-01-17

Python NumPy & Pandas for Beginners

Python Libraries Textbook for Beginners with Codes Folder

Python is doubtless the most versatile programming language.
But are you serious enough about becoming proficient in Python?
If yes, then you need to become a master in the two essential Python libraries—NumPy and Pandas. You simply can’t overlook this truth.
In data science, NumPy and Pandas are by far the most widely used Python libraries. The main features of these libraries are powerful data analysis tools and easy-to-use structures.
Python NumPy & Pandas for Beginners presents you with a hands-on, simple approach to learning Python fast. This book is refreshingly different, as there’s a lot for you to do than mere reading. Each theoretical concept you cover is followed by practical examples, making it easier to master the concept.
The step-by-step layout of this book simplifies your learning. The author has gone to great lengths to ensure what you learn sticks. You have short exercises at the end of each one of the 11 chapters to test your knowledge of the theoretical concepts you have learned.
This book presents you with:

  • A strong foundation in Pandas.
  • A deep understanding of fundamental and intermediate topics.
  • The essentials of coding in Python.
  • Links to reference materials related to the topics you study.
  • Quick access to external files to practice and learn advanced concepts of Pandas.
  • Resources folder containing all the datasets used in the book.
The Focus of the Book Is on Learning by Doing

In this learning by doing book, you start with Python installation in the very first chapter. Then there’s a crash course in Python in the second half of the first chapter. In the second chapter, you jump straight to NumPy. Right through the book, you’ll use Jupyter Notebook to write code. You can also get fast access to the datasets used in this book.
The book is loaded with self-explanatory scripts, graphs, and images. They have been meticulously designed to help you understand new concepts easily. Hence, this book is the best choice for self-study, even if you are proficient in Python.


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