Python for Data Analysis

Summary

Python for Data Analysis will explore many areas of Python and how different functions work and how it all correlates to Python.  In chapter one, we begin by giving you an overview of the different Python libraries. We also give a brief description, explain why they are popular, and what their functions are. In chapter two, we discuss the Panda library and give a rundown of its basics and why it is one of the more popular libraries and most commonly used today. In chapter three, we dive into the retrieving, processing, and storing of the data that is utilized in Python. Chapter four explores data visualizations and the use of charts and graphs to assist in visualizing the data that is generated through Python. With chapter five, you will become familiar with working with the databases that Python supports. A few examples of these include SQL, API, and SQLite.  Chapter six will cover predictive analytics and machine learning. It will describe the way machine learning and predictive analytics plays a role in Python and how Python can help to advance machine learning. Finally, in chapter seven, we see Python’s involvement with time series and signal processing.  As the chapters will show you, Python for Data Analysis is a great way to get a huge amount of information in a hurry. So no matter if you are just beginning in Python or need to learn it in a hurry, Python for Data Analysis is sure to provide you with what you need.

©2020 Jason Cannon (P)2020 Jason Cannon