programmatic-eda

What problem does it solve?

Systematic exploratory data analysis following best practices helps analysts understand data structure, identify data quality issues (duplicates, missing values, inconsistencies, outliers), examine distributions, detect correlations, and generate visualizations.

Core Features & Use Cases

• Automated data profiling and sanity checks before analysis.
• Identification of data quality issues such as duplicates, missing values, and outliers.
• Generation of distributions, correlations, and visual summaries for quick decision support.
• Use Case: Apply to a new dataset to surface quality issues and initial insights, enabling rapid storytelling.

Quick Start

Load a dataset and generate an initial profiling report that includes distributions, relationships, and quality checks.