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Mastering pandas

Mastering pandas - Second Edition

By : Kumar
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Mastering pandas

Mastering pandas

By: 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)
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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

Installation of pandas and Supporting Software

Before we can start work on pandas for doing data analysis, we need to make sure that the software is installed and the environment is in proper working order. This chapter deals with the installation of Python (if necessary), the pandas library, and all necessary dependencies for the Windows, macOS/X, and Linux platforms. The topics we address include, among other things, selecting a version of Python, installing Python, and installing pandas.

The steps outlined in the following section should work for the most part, but your mileage may vary depending upon the setup. On different operating system versions, the scripts may not always work perfectly, and the third-party software packages already in the system may sometimes conflict with the instructions provided.

The following topics will be covered in this chapter:

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