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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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Exercises

Complete the following exercises to practice the concepts covered in this chapter:

  1. Run the simulation for December 2018 into new log files without making the user base again. Be sure to run python3 simulate.py -h to review the command-line arguments. Set the seed to 27. This data will be used for the remaining exercises.
  2. Find the number of unique usernames, attempts, successes, and failures, as well as the success/failure rates per IP address, using the data simulated from exercise 1.
  3. Create two subplots with failures versus attempts on the left, and failure rate versus distinct usernames on the right. Draw decision boundaries for the resulting plots. Be sure to color each data point by whether or not it is a hacker IP address.
  4. Build a rule-based criteria using the percentage difference from the median that flags an IP address if the failures and attempts are both five times their respective medians, or if the distinct usernames count is five times its...
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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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