July 21, 2025

Python Data Cleaning Cookbook: Modern techniques and Python tools to detect and remove dirty data and extract key insights

29 minutes

Provides a comprehensive guide to data cleaning techniques using Python, specifically focusing on the pandas library. It covers essential steps from importing various data formats like CSV, Excel, SQL, SPSS, Stata, SAS, and R files, to addressing common data quality issues. The text details methods for identifying missing values and outliers through statistical analysis and visualizations, cleaning and transforming data series, and combining datasets through vertical concatenation and different types of merges. Ultimately, the book emphasizes automating data cleaning processes by developing reusable functions and classes to efficiently manage and prepare data for analysis.

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