What are the best practices for data cleaning in Python?
An example of an AI chatbot conversation about best practices for data cleaning in Python.
What are the best practices for data cleaning in Python?
Some best practices include using libraries like Pandas, handling missing values, and ensuring data consistency.
Can you explain how to handle missing values?
You can handle missing values by using methods like imputation, dropping rows, or filling with default values.
What libraries should I use for data cleaning?
Pandas is the most popular library for data cleaning, along with NumPy for numerical operations and Matplotlib for visualization.
How do I ensure data consistency?
Data consistency can be ensured by validating data types, standardizing formats, and removing duplicates.
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