Analyzing and Visualizing Data with Python

Advanced analytics and data science now play a major role in the majority of businesses. It supports organizations in tracking, managing, and gathering performance metrics to enhance organizational decision-making. Business managers can utilize innovative analysis and machine learning to help them decide how to best engage customers, enhance business performance, and increase sales. Data science and analytics can be utilized to create user-centric products and make wise choices. This can be achieved by comparing various product aspects and studying consumer feedback and market trends to develop goods and services that can draw clients and keep them around for an extended period.

This book is intended for everyone who wants to have an introduction to the techniques and methods of data science, advanced analytics, and machine learning for studying business cases that have been impacted by the use of these methods. The cases shown are heavily based on real use cases, with a demonstrated positive impact in various companies of different sectors. So, anyone who might be considering the application of data science in business operations, regardless of whether they are a seasoned business analyst seeking to enhance their list of skills, or a manager looking for methods that can be applied to maximize certain operations, can benefit from the examples discussed in this book.

In this chapter, we will lay down the initial components that will be used throughout this book to manage the data, manipulate it, and visualize it. Specifically, we will discuss the following:

• The use of data science in business and the main differences with roles such as business or data analysts
• The use of statistical programming libraries such as NumPy to apply matrix algebra and statical methods
• Storing the data in pandas, a library for data analysis and manipulation that is widely used in the context of data science
• Visualization with Seaborn and how the different types of charts can be used in different kinds of situations

Next, we will discuss the technical requirements that you will need to be able to follow the examples presented in this chapter.