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Data Cleaning in Python Module

ISBN #978-1-959142-31-7

Data Cleaning in Python Module

This module will help students understand the primary data cleaning steps necessary to prepare for predictive modeling. This includes outlier detection and management, handling missing data of all types (random, completely at random, and not at random), and making mathematical transformations. In addition, several basic and common modifications of Pandas DataFrames are covered, including iterating over records, recoding values, and converting dates to integers.

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Course Objective

This module teaches key data cleaning steps for predictive modeling, including outlier detection, handling missing data, mathematical transformations, and common Pandas DataFrame modifications such as iterating, recoding, and converting dates.

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