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

Where does pandas fit in the pipeline?

As discussed in the previous section, pandas can be used to perform Step 4 to Step 6 in the pipeline. And Step 4 to Step 6 are the backbone of any data science process, application, or product:

Where does pandas fit in the data analytics pipeline?

The Step 1 to Step 6 can be performed in pandas by some methods. Those in the Step 4 to Step 6 are the primary tasks while the Step 1 to Step 3 can also be done in some way or other in pandas.

pandas is an indispensable library if you're working with data, and it would be near impossible to find code for data modeling that doesn't import pandas into the working environment. Easy-to-use syntax in Python and the availability of a spreadsheet-like data structure called a dataframe make it amenable even to users who are too comfortable and too unwilling to move away from Excel. At the same...