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

A summary of time series-related objects

There are many time series-related objects in pandas that are used for manipulating, creating, and processing timestamp data. The following table gives a summary of time series-related objects:

Object

Summary

datetime.datetime

This is a standard Python datetime class.

Timestamp

This is a pandas class derived from. datetime.datetime.

DatetimeIndex

This is a pandas class and is implemented as an immutable numpy.ndarray of the Timestamp/datetime object type.

Period

This is a pandas class representing a time period.

PeriodIndex

This is a pandas class and is implemented as an immutable numpy.ndarray of the Period object type.

DateOffset

DataOffset is used to move forward a date by a given number of valid dates (days, weeks, months, and so on).

timedelta

Timedelta calculates the difference in time...