Athena

Automated EDA, ML readiness scoring, and data diagnostics — locally in your browser.

pip install athena-eda
athena run

What it does

Athena analyzes tabular datasets and surfaces everything that matters before you start modeling. Upload a CSV, pick a mode, and get a structured diagnostic report in under two minutes — no code required.

It covers the full pre-modeling workflow: data quality, feature analysis, ML readiness scoring, leakage detection, time series diagnostics, and multi-model comparison. When you're done, download a ready-to-run Python preprocessing script tailored to your dataset.

Features

Core EDA

• Column classification — numeric, categorical, identifiers, free text, entity keys
• Missing value analysis with row-level and column-level breakdown
• Outlier and skew analysis — per-feature skewness, kurtosis, log-transform recommendations
• Feature redundancy detection — correlation matrix analysis for highly redundant pairs

ML Readiness

• ML Readiness Score — composite score across data health, trainability, and leakage risk
• Leakage Detection — flags identifier columns and suspiciously correlated features
• Baseline Probe — 3-fold cross-validated LightGBM baseline with learning curves and overfitting detection
• Stability Analysis — subsample stability checks across multiple runs
• Clustering Diagnostics — silhouette scoring across k=2 to 5 for unlabeled datasets
• Anomaly Detection — Isolation Forest with score distribution visualization

Model Arena

• Auto-trains Random Forest, LightGBM, Logistic Regression (classification) or Ridge, Lasso, Random Forest, LightGBM (regression)
• Ranks all models by balanced accuracy or RMSE with training time and variance
• Only runs on labeled datasets with a specified target column

Time Series

• Auto-detects datetime columns and forecast targets
• Stationarity testing — ADF and KPSS with differencing recommendations
• Seasonal decomposition with auto-detected period
• ACF and PACF with confidence bands
• Missing timestamp detection and coverage analysis
• Baseline models — Naive, Moving Average, Exponential Smoothing, Auto-ARIMA ranked by RMSE

NLP

• Free-text column detection with vocabulary and lexical diversity analysis
• Text quality metrics — empty ratio, duplicate ratio, URL ratio
• Vectorization recommendations — TF-IDF vs embeddings
• Per-class word analysis for labeled datasets

Drift Detection

• Upload train and test splits to get per-column KS-statistic drift scores
• New category detection and missing rate delta

Outputs

• Preprocessing script — one-click export of a production-ready Python script tailored to your EDA results
• HTML report — full diagnostic report with charts, tables, and recommendations
• Time series script — pipeline script with load, stationarity check, decomposition, train/test split, and all baseline models

Analysis Profiles

Installation

pip install athena-eda

Requires Python 3.9+. All dependencies including statsmodels and pmdarima for time series are included in the base install.

Running locally

athena run

Opens your browser at http://127.0.0.1:8000 automatically.

Other commands

athena info      # show system and package info
athena doctor    # check all dependencies
athena version   # show current version
athena update    # update to latest version

Stack

Frontend — React, TypeScript, Vite, Recharts

Backend — FastAPI, Python, LightGBM, scikit-learn, statsmodels, pmdarima, pandas

License

MIT