data-exploration

What problem does it solve?

Data exploration enables systematic investigation of datasets to uncover patterns, validate quality, and surface insights that inform decision-making across ad-hoc investigations, data quality checks, and hypothesis generation.

Core Features & Use Cases

• Data Profiling and Quality Assessment: compute shape, missingness, dtypes, and duplicates to establish a reliability baseline for new datasets.
• Pattern Discovery and Visualization: generate distributions, correlations, and trend visuals to surface actionable insights for hypothesis testing.
• Intelligence Briefing: assemble findings into concise briefs for stakeholders to guide next steps.

Quick Start

Provide a path to a dataset and run the explore_dataset.py script to generate an exploration report and intelligence brief.