Lightning-fast DataFrame introspection with smart red-flag suggestions
Project description
edaio ⚡
Lightning-fast DataFrame introspection with smart red-flag suggestions.
🚀 Quick Start
import pandas as pd
from edaio import glance
df = pd.read_csv("your_data.csv")
report = glance(df, target='price')
✨ Features
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Instant insights – One line of code, zero configuration
-
Actionable suggestions – Tells you exactly what to fix
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Parallel computation – Lightning fast on large datasets
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Drift detection – Compare train/test datasets with PSI
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Programmable API – Query the report object for specific issues
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Lightweight – No heavy dependencies or bloated reports
📦 Installation
pip install edaio
With optional features:
pip install edaio[rich,plotly]
📊 Examples Basic Usage
from edaio import glance
import pandas as pd
df = pd.read_csv("sales.csv")
report = glance(df)
Target Analysis
report = glance(df, target='price')
print(report.null_cols) # Columns with >30% missing
print(report.high_corr_pairs) # Highly correlated features
Train/Test Comparison
report = glance(train_df, compare_to=test_df)
See drift detection in the suggestions
🔧 Command Line
edaio data.csv --target price --output-html report.html
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