Book Image

Mastering pandas - Second Edition

By : Ashish Kumar
Book Image

Mastering pandas - Second Edition

By: Ashish Kumar

Overview of this book

pandas is a popular Python library used by data scientists and analysts worldwide to manipulate and analyze their data. This book presents useful data manipulation techniques in pandas to perform complex data analysis in various domains. An update to our highly successful previous edition with new features, examples, updated code, and more, this book is an in-depth guide to get the most out of pandas for data analysis. Designed for both intermediate users as well as seasoned practitioners, you will learn advanced data manipulation techniques, such as multi-indexing, modifying data structures, and sampling your data, which allow for powerful analysis and help you gain accurate insights from it. With the help of this book, you will apply pandas to different domains, such as Bayesian statistics, predictive analytics, and time series analysis using an example-based approach. And not just that; you will also learn how to prepare powerful, interactive business reports in pandas using the Jupyter notebook. By the end of this book, you will learn how to perform efficient data analysis using pandas on complex data, and become an expert data analyst or data scientist in the process.
Table of Contents (21 chapters)
Free Chapter
1
Section 1: Overview of Data Analysis and pandas
4
Section 2: Data Structures and I/O in pandas
7
Section 3: Mastering Different Data Operations in pandas
12
Section 4: Going a Step Beyond with pandas

The pandas Library Architecture

In this chapter, we examine the various libraries that are available to pandas users. This chapter is intended to be a short guide to help the user to navigate and find their way around the various modules and libraries that pandas provides. It gives a breakdown of how the library code is organized, and it gives a brief description of the various modules. It will be most valuable to users who are interested in seeing the inner workings of pandas , as well as to those who wish to make contributions to the code base. We will also briefly demonstrate how you can improve performance using Python extensions. The various topics that will be discussed are as follows:

  • Introduction to the pandas library hierarchy
  • Description of pandas modules and files
  • Improving performance using Python extensions