Sign In Start Free Trial
Account

Add to playlist

Create a Playlist

Modal Close icon
You need to login to use this feature.
  • Book Overview & Buying Mastering pandas
  • Table Of Contents Toc
  • Feedback & Rating feedback
Mastering pandas

Mastering pandas

By : Kumar
close
close
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)
close
close
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

Time Series and Plotting Using Matplotlib

Time series data is generated by a variety of processes, including the Internet of Things (IoT) sensors, machine/server logs, and monthly sales data from Customer Relationship Management (CRM) system. Some common characteristics of time series data is that the data points are generated at a fixed frequency and that there is an inherent trend and seasonality associated with the data.

In this chapter, we will take a tour of some topics that are necessary to develop expertise in using pandas. Knowledge of these topics is very useful for the preparation of data as input to programs for data analysis, prediction, or visualization.

The topics that we'll discuss in this chapter are as follows:

  • Handling time series data and dates
  • Manipulation of time series data—rolling, resampling, shifting, lagging, and time element separation
  • Formatting...

Unlock full access

Continue reading for free

A Packt free trial gives you instant online access to our library of over 7000 practical eBooks and videos, constantly updated with the latest in tech
bookmark search playlist download font-size

Change the font size

margin-width

Change margin width

day-mode

Change background colour

Close icon Search
Country selected

Close icon Your notes and bookmarks

Delete Bookmark

Modal Close icon
Are you sure you want to delete it?
Cancel
Yes, Delete

Confirmation

Modal Close icon
claim successful

Buy this book with your credits?

Modal Close icon
Are you sure you want to buy this book with one of your credits?
Close
YES, BUY