The pandas beyond the basics syllabus is designed to help analysts, researchers, BI experts and developers becoming fluent in the use of the pandas library for Python, going beyond the basics, learning the more advanced features of pandas and adopting the best practices, in order to slice and dice complex data.
Using interactive examples and hands-on exercises, the course provides a full immersion in the advanced features of the pandas library. The course focuses on making your pandas code more efficient, so some very basic familiarity with pandas and its core concepts is assumed.
SyllabusEfficient data modelling
- Deep-dive into pandas data types
- Choosing data types when loading the data
- Data type conversions
- Best practices to improve your memory usage when dealing with large datasets
- Understanding mutability and immutability
- Method chaining to improve readability
- Best practices to develop and maintain complex data transformation and query pipelines
- Complex aggregations (groupby) on multiple columns
- Mastering the hierarchical (multi-level) index
- Index stacking and unstacking
- Pivoting and reshaping
- Overview on examples of usage of other libraries built on top of pandas to address specific needs in data preparation, data analysis and data visualisation