CSV Data Explorer - Column Analysis & Regression

CSV Data Explorer analyzes your CSV files to understand their structure, surface data quality issues, and fit statistical models. It auto-detects column types by sampling values and matching patterns — recognizing emails, URLs, timestamps, currencies, and numeric types. It highlights missing values and outliers, and can fit an OLS linear regression between two numeric columns to show correlations and make predictions.

The parser samples the first 100 rows to infer column types using regex patterns and value inspection. Missing values are counted per column. When you select X and Y columns, OLS linear regression is fitted using the normal equation (β = (XᵀX)⁻¹Xᵀy), and the R² score measures how well the line fits the data points.