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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
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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.
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Summary

In this chapter, we learned how to use pandas for the data collection portion of data analysis and to describe our data with statistics, which will be helpful when we get to the drawing conclusions phase. We learned the main data structures of the pandas library, along with some of the operations we can perform on them. Next, we learned how to create DataFrame objects from a variety of sources, including flat files and API requests. Using earthquake data, we discussed how to summarize our data and calculate statistics from it. Subsequently, we addressed how to take subsets of data via selection, slicing, indexing, and filtering. Finally, we practiced adding and removing both columns and rows from our dataframe.

These tasks also form the backbone of our pandas workflow and the foundation for the new topics we will cover in the next few chapters on data wrangling, aggregation, and data visualization. Be sure to complete the exercises provided in the next section before moving...

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Hands-On Data Analysis with Pandas - Second Edition
Published in: Apr 2021Publisher: PacktISBN-13: 9781800563452

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