Python for Data Analysis: The Guide to Learn How to Use Python for Data Analysis

Python is imposing itself in many fields as a language of reference programming. In the context of data science, it proves to be a leading tool for articulating complex projects with a "universal" language. Today, it is the ideal tool for setting up prototypes and a great ally for big data, machine learning, and deep learning.

This book will guide you through this simple language and deepen your use as a data scientist.

The aim is to give you the tools you need to understand and use Python's use of data science. If you are or want to become a data scientist, mastery of Python today is an important advantage and tends to become a prerequisite.

This book will allow you to take in hand this language and to understand all the subtleties in order to be able to develop in Python processes of data science.

Our goal here is not to present methods in a theoretical way but rather to illustrate the application of data science methods thanks to the Python language and all its specificities.

This book is for data scientists or future data scientists. In a broader way, it will interest all those who, on a daily basis, process data and attempt to implement data processing in concrete frameworks.

More specifically, it is intended for:

• Business Intelligence professionals who want to analyze their data more precisely thanks to a new language.
• Statisticians (especially those using SAS or R) who need to set up automated processes and who want to learn Python.
• Developers who want to acquire competence in data science with the use of Python.
• To master's degree students in computer science or statistics who wish to learn and improve their Python language by working on practical cases.
• Analysts and consultants who manage projects and data analysis in Python as part of their activities.
• Happy reading!

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