Live training with David Yerrington starts on January 7 at 1 PM (ET)
Training duration: 4 hours
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Instructor
Data Science Consultant | Yerrington Consulting
David Yerrington
10% discount ends in:
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By the end of the course, participants will be able to:
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Know how to configure Python environments
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Understand the fundamentals of Pandas
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Understand when to use Built-in vs. ".apply()" for data transformation
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Be familiar with common multi-index use cases
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Understand how to select data with multi-indexes
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Describe which aspects of a DataFrame can be customized
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Know how to write callback functions on DataFrame aesthetics
Course Abstract
Knowing just enough Pandas can mean the difference between exploring and understanding data from a fundamental. Knowing how to transform data, use multi-indexes, and customize Pandas' visual aspects in Jupyter Lab gives you the power to approach everyday problems confidently. In this session, you will build on fundamentals you already know to handle a more comprehensive array of data problems.
This session is for anyone who already has a solid foundation of Pandas fundamentals who wants to extend their knowledge with more advanced features, including aggregation, multi-indexing, designing transformations, and customizing DataFrame output.
Course Schedule
Module 1: Introductions, Configuration, and Review
- Configure your Python environments
- Review the fundamentals of Pandas
Module 2: Aggregations and ".apply()"
- Perform simple aggregations
- Review: DataFrame Axis
- Understand when to use Built-in vs. ".apply()" for data transformation
Module 3: Mult-indexing
- Describe when multi-indexing makes sense
- Be familiar with common multi-index use cases
- Understand how to select data with multi-indexes
Module 4: Customizing DataFrame Output
- Describe which aspects of a DataFrame can be customized
- How to write callback functions on DataFrame aesthetics
Who will be interested in this course?
This course is geared to data scientists, data engineers, machine learning engineers and software engineers of all levels who wish to gain a deep understanding of Pandas and how to apply it to real-world situations.
Which knowledge and skills you should have?
- Grouping
- Selecting rows or columns of DataFrames with .loc, iloc
- Boolean Indexing
- Git and Github
- Installing Python environments
- Jupyter Lab
Have questions?
What is included in your ticket?
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Access to live training and QA session with the Instructor
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Access to the on-demand recording
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Certificate of completion