dataset-inspector 0.0.1

Lightweight CLI tool to analyze CSV datasets and detect common ML data issues.

dataset-inspector

A lightweight CLI tool to quickly analyze CSV datasets and detect common issues before training ML models.

Features

• Basic statistics – mean, std, min, max, median, quartiles for every numeric column
• Missing values – per-column count and percentage
• Duplicate rows – exact duplicate detection
• Class imbalance – minority/majority ratio check for categorical columns
• Anomaly detection – IQR or z-score based outlier flagging
• Terminal report – clean, colour-coded output
• JSON export – optional machine-readable report

Installation

pip install -r requirements.txt

Quick start

# Analyse the included example dataset
python -m dataset_inspector --input examples/sample.csv

# Specify a target column for class-imbalance check
python -m dataset_inspector --input data.csv --target label

# Use z-score anomaly detection and export JSON
python -m dataset_inspector --input data.csv --anomaly-method zscore --json report.json

# Enable verbose / debug logging
python -m dataset_inspector --input data.csv -v

Project structure

dataset_inspector/
├── __init__.py      # package metadata
├── __main__.py      # python -m entry point
├── cli.py           # argument parsing (argparse)
├── analyzer.py      # core analysis logic
├── report.py        # terminal + JSON report formatting
└── utils.py         # logging helpers
examples/
└── sample.csv       # small demo dataset