Exploratory data analysis options – profiler versus manual
When performing exploratory data analysis (EDA), there are different approaches you can take to understand your data, including conducting manual analysis or using a profiler.
Manual EDA involves writing custom code or using general-purpose data analysis libraries (e.g., pandas in Python) to explore the data. It gives you more flexibility and control over the analysis process. You can customize the analysis based on your specific requirements and questions. Manual EDA allows for more in-depth exploration, including custom calculations, feature engineering, and advanced visualizations. It can be beneficial when dealing with complex data or when you have specific domain knowledge that you want to apply to the analysis.
A profiler is a tool or library specifically designed for analyzing and summarizing data. It automates many EDA tasks and provides quick insights into the data’s structure, summary statistics...
