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You're reading from  Hands-On Data Analysis with Pandas - Second Edition

Product typeBook
Published inApr 2021
Reading LevelIntermediate
PublisherPackt
ISBN-139781800563452
Edition2nd Edition
Languages
Python
Tools
Pandas
Concepts
Databases
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Author (1)
Stefanie Molin
Stefanie Molin
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Stefanie Molin

Stefanie Molin is a data scientist and software engineer at Bloomberg LP in NYC, tackling tough problems in information security, particularly revolving around anomaly detection, building tools for gathering data, and knowledge sharing. She has extensive experience in data science, designing anomaly detection solutions, and utilizing machine learning in both R and Python in the AdTech and FinTech industries. She holds a B.S. in operations research from Columbia University's Fu Foundation School of Engineering and Applied Science, with minors in economics, and entrepreneurship and innovation. In her free time, she enjoys traveling the world, inventing new recipes, and learning new languages spoken among both people and computers.
Read more about Stefanie Molin

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Summary

Congratulations on making it through this chapter! Data wrangling may not be the most exciting part of the analytics workflow, but we will spend a lot of time on it, so it's best to be well versed in what pandas has to offer.

In this chapter, we learned more about what data wrangling is (aside from a data science buzzword) and got some firsthand experience with cleaning and reshaping our data. Utilizing the requests library, we once again practiced working with APIs to extract data of interest; then, we used pandas to begin our introduction to data wrangling, which we will continue in the next chapter. Finally, we learned how to deal with duplicate, missing, and invalid data points in various ways and discussed the ramifications of those decisions.

Building on these concepts, in the next chapter, we will learn how to aggregate dataframes and work with time series data. Be sure to complete the end-of-chapter exercises before moving on.

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Hands-On Data Analysis with Pandas - Second Edition
Published in: Apr 2021Publisher: PacktISBN-13: 9781800563452
© 2021 Packt Publishing Limited All Rights Reserved

Author (1)

author image
Stefanie Molin

Stefanie Molin is a data scientist and software engineer at Bloomberg LP in NYC, tackling tough problems in information security, particularly revolving around anomaly detection, building tools for gathering data, and knowledge sharing. She has extensive experience in data science, designing anomaly detection solutions, and utilizing machine learning in both R and Python in the AdTech and FinTech industries. She holds a B.S. in operations research from Columbia University's Fu Foundation School of Engineering and Applied Science, with minors in economics, and entrepreneurship and innovation. In her free time, she enjoys traveling the world, inventing new recipes, and learning new languages spoken among both people and computers.
Read more about Stefanie Molin

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