What is the main feature of exploratory data analysis?

The main feature of exploratory data analysis (EDA) is to summarize the main characteristics of data. EDA involves using various techniques to visually and quantitatively explore datasets, aiming to uncover patterns, spot anomalies, test assumptions, and check the overall data quality. By summarizing the data, analysts can better understand its structure, relationships among variables, and distribution, which are all crucial for informing further analysis or modeling.

This approach emphasizes visualizations, such as histograms, box plots, and scatter plots, alongside summary statistics like mean, median, mode, and standard deviation. It allows data analysts to generate insights without predefined hypotheses, making it an essential preliminary step before applying more advanced analytics, such as predictive modeling or statistical significance testing.