Practical Guide to Data Analysis and Preprocessing
Techniques for data cleaning, transformation, and validation to ensure quality data
In this project, we will utilize a dataset derived from a fictitious company that encompasses demographic data and results from a psychometric test administered to employees.
The key variables include age, gender, education_level, and salary, which are pivotal in a corporate context. The primary objective is to pre-process this data, ensuring both quality and consistency for subsequent analysis.
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