agro-data-intelligence 0.1.1

Agricultural data auditing, visualization and explainable machine learning framework

Data Audit

data_audit is a powerful Pandas accessor that makes auditing, cleaning, and training ML models on tabular data seamless and intuitive.

Features

• Data Auditing: Rapidly scan dataframes for missing values, duplicates, and outliers (via IQR/Z-score/Custom Bounds).
• Auto-Fixing: Heal data in-place or generate suggestions.
• Anomaly Detection: Out-of-the-box anomaly detection via Isolation Forest.
• Embedded ML: Instantly train Regression or Classification models (Random Forest) directly on your dataframe.
• Explainability: SHAP integration for global feature importance and local predictions.

Installation

pip install data_audit

Quickstart

import pandas as pd
import data_audit

# Load your dataframe
df = pd.read_csv("data.csv")

# 1. Scan for issues
issues = df.audit.scan()

# 2. Fix issues automatically
df.audit.fix(mode='auto')

# 3. Train a Machine Learning Model on a target column
df.audit.ml.train(target="SalePrice")

# 4. Explain the model's global and local features
print(df.audit.ml.explain())