Book Image

Hands-On Data Analysis with Pandas - Second Edition

By : Stefanie Molin
5 (1)
Book Image

Hands-On Data Analysis with Pandas - Second Edition

5 (1)
By: Stefanie Molin

Overview of this book

Extracting valuable business insights is no longer a ‘nice-to-have’, but an essential skill for anyone who handles data in their enterprise. Hands-On Data Analysis with Pandas is here to help beginners and those who are migrating their skills into data science get up to speed in no time. This book will show you how to analyze your data, get started with machine learning, and work effectively with the Python libraries often used for data science, such as pandas, NumPy, matplotlib, seaborn, and scikit-learn. Using real-world datasets, you will learn how to use the pandas library to perform data wrangling to reshape, clean, and aggregate your data. Then, you will learn how to conduct exploratory data analysis by calculating summary statistics and visualizing the data to find patterns. In the concluding chapters, you will explore some applications of anomaly detection, regression, clustering, and classification using scikit-learn to make predictions based on past data. This updated edition will equip you with the skills you need to use pandas 1.x to efficiently perform various data manipulation tasks, reliably reproduce analyses, and visualize your data for effective decision making – valuable knowledge that can be applied across multiple domains.
Table of Contents (21 chapters)
Section 1: Getting Started with Pandas
Section 2: Using Pandas for Data Analysis
Section 3: Applications – Real-World Analyses Using Pandas
Section 4: Introduction to Machine Learning with Scikit-Learn
Section 5: Additional Resources

Chapter 2: Working with Pandas DataFrames

The time has come for us to begin our journey into the pandas universe. This chapter will get us comfortable working with some of the basic, yet powerful, operations we will be performing when conducting our data analyses with pandas.

We will begin with an introduction to the main data structures we will encounter when working with pandas. Data structures provide us with a format for organizing, managing, and storing data. Knowledge of pandas data structures will prove infinitely helpful when it comes to troubleshooting or looking up how to perform an operation on the data. Keep in mind that these data structures are different from the standard Python data structures for a reason: they were created for specific analysis tasks. We must remember that a given method may only work on a certain data structure, so we need to be able to identify the best structure for the problem we are looking to solve.

Next, we will bring our first dataset...