Advanced DataFrame Transformations
Venture into Pandas for exceptional operations
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Participants can interact with the instructor,
ask questions, seek clarification,
and receive immediate feedback. -
You can receive a full refund before
the second session. After attending
the second session, you will not be eligible
for a refund. -
Access to the session that was originally
conducted in real time. -
You can retake the same course you attended.
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We will provide you with the notes for the course.
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We will provide you with the homework
assignments for additional practice. -
You can always reach out to the instructor
between sessions or after the course on Slack.
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Discover the technique of executing logical operations on DataFrames using apply and lambda functions.
We'll execute intricate queries and apply logical conditions to the DataFrame.
Join us for an enriching workshop where you'll delve deep into the intricacies of DataFrames and master the art of employing complex logical statements. Uncover the power of NumPy functions to execute advanced logical operations. Navigate the realm of apply functions and harness the capabilities of anonymous lambda functions for precise logical manipulations.
In addition, we will focus on the 'query' function, equipping you with the skills to wield complex filtering with multiple conditions effortlessly. This workshop is your gateway to unraveling the secrets of effective data manipulation and logical analysis using Python's DataFrame.
What to expect
Led by expert instructors, our dynamic 3-hour live-online workshop offers real-time coding immersion. Dive into practical exercises and examples, experiencing live interaction as our skilled instructor guides you, reviews code, and corrects errors. Enhance your journey with comprehensive workshop materials, including notes and videos, solidifying your newfound skills. Elevate your coding prowess in this immersive experience, where theory meets practice and expert guidance fuels your success.
Prerequisites
Before enrolling in this workshop, it's recommended to have a grasp of Python's built-in data types and a foundational understanding of DataFrame structure in Pandas.