Know how to configure Python environments
Understand the fundamentals of Pandas
Understand when to use Built-in vs. ".apply()" for data transformation
Be familiar with common multi-index use cases
Understand how to select data with multi-indexes
Describe which aspects of a DataFrame can be customized
Know how to write callback functions on DataFrame aesthetics
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.
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
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.
- Selecting rows or columns of DataFrames with .loc, iloc
- Boolean Indexing
- Git and Github
- Installing Python environments
- Jupyter Lab
Access to live training and QA session with the Instructor
Access to the on-demand recording
Certificate of completion