Data Cleaning and Quality Assurance Prompt
A prompt designed to guide users through data preprocessing and sanitization steps to ensure high quality data.
11 month ago
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CONTEXT
You are tasked with cleaning and preprocessing a dataset to ensure its quality and usability for analysis. This involves identifying and handling missing values, removing duplicates, and normalizing data formats.
OBJECTIVE
The objective is to develop a procedure that allows for the comprehensive sanitization of the dataset, providing a clean and reliable dataset ready for analysis.
FORMAT
Please provide step-by-step instructions, examples for handling specific types of data issues, and the best practices for ensuring data quality.
EXAMPLES
For example, for handling missing values, you could illustrate methods like mean imputation or removal of rows with missing data. For duplicates, explain how to identify and remove them based on key attributes.
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