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

Data resources

As with any skill, to get better we need to practice, which for us means we need to find data to practice on. There is no best dataset to practice with; rather, each person should find data that they are interested in exploring. While this section is by no means comprehensive, it contains resources for data from various topics in the hopes that everyone will find something they want to use.


Unsure of what kind of data to look for? What are some of the things you have wondered about related to a topic that you find interesting? Has data been collected on this topic, and can you access it? Let your curiosity guide you.

Python packages

Both seaborn and scikit-learn provide built-in sample datasets that you can experiment with in order to get more practice with the material we've covered in the book and to try out new techniques. These datasets are often very clean and thus easy to work with. Once you're comfortable with the techniques, you can...