🌟 Data Cleaning and Processing 🌟 Handled missing values, removed duplicates, standardized salary formats, and treated outliers for consistency.Revealed trends in company performance, job roles, and salary distributions after refining the dataset. This project highlights the power of data preprocessing as the backbone of reliable analytics.
communication numpy conversion jupyter-notebook data-transformation eda pandas python-programming matplotlib vs-code transformation palettes data-cleaning cleaning data-interpretation analytical-thinking data-standardization aesthetic-design handling-missing-data
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Nov 15, 2025 - Jupyter Notebook