What is Python data cleaning?

Python data cleaning is the process of using Python programming language and its libraries to identify, correct, or remove inaccurate, incomplete, or irrelevant data from datasets. This step is crucial in data analysis and machine learning, as clean data leads to more reliable and meaningful results. Tasks involved may include handling missing values, correcting data types, removing duplicates, and standardizing formats. Popular Python libraries for data cleaning include pandas and NumPy. Effective data cleaning ensures that analyses and models are built on high-quality, trustworthy data.