speedyeda 0.1.1

🚀 One-line data exploration for developers & data scientists

🚀 SpeedyEDA - Lightning-Fast Data Exploration

Instant insights, beautiful visualizations, and comprehensive summaries from datasets with just one command.

Stop writing boilerplate! SpeedyEDA gives you complete exploratory data analysis in seconds. Perfect for data scientists, analysts, and developers who want instant insights without the setup.

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Your star helps others discover SpeedyEDA and motivates us to keep improving! 🙏

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✨ Features

• 📊 Automatic Statistics - Mean, median, mode, min/max, std, skewness, kurtosis
• 🔍 Missing Value Analysis - Highlights and actionable suggestions
• 📈 Auto Visualizations - Histograms, boxplots, correlation heatmaps, and more
• 🎨 Beautiful Terminal Output - Colorful, emoji-rich displays using rich
• 🎭 Fun Mode - Screenshot-worthy results with emojis and ASCII art
• 📄 Export Reports - Save as JSON or text with one flag
• 🔧 Presets - Pre-configured analysis (ecommerce, surveys, finance)
• 🔌 Plugin System - Extend with custom visualizations and metrics
• 🤝 Interactive Mode - Guided column and plot selection
• 📦 Batch Processing - Analyze multiple datasets at once

🚀 Quick Start

Installation

pip install speedyeda

Basic Usage

# Quick exploration with beautiful output
fasteda sales.csv --fun

# Use a preset for instant domain-specific insights
fasteda products.csv --preset ecommerce

# Generate plots automatically
fasteda data.csv --plots

# Interactive mode - let SpeedyEDA guide you
fasteda survey.xlsx --interactive

# Batch processing
fasteda file1.csv file2.csv file3.csv --batch

Python API

import pandas as pd
from fasteda import analyze, save_report

df = pd.read_csv("sales.csv")

# Generate comprehensive EDA
results = analyze(df, fun=True)

# Save detailed report
save_report(results, "sales_report.json")

📋 CLI Options

Flag	Description
--fun	🎉 Emojis and colorful output (highly recommended!)
--summary	📝 Plain text summary with insights
--plots	📊 Generate and save visualizations
--save <file>	💾 Export report (JSON/TXT)
--interactive	🤝 Interactive column/plot selection
--preset <name>	🎯 Use preset (ecommerce, survey, finance)
--columns <cols>	🎯 Analyze specific columns only
--batch	📦 Process multiple files
--quiet	🤫 Suppress terminal output

🎯 Smart Presets

SpeedyEDA includes built-in presets tailored for common scenarios:

• 📦 ecommerce - Product analysis, sales trends, customer behavior
• 📋 survey - Response distributions, sentiment analysis, demographics
• 💰 finance - Time series, correlations, risk metrics
• 🔧 general - Comprehensive all-purpose exploration

fasteda sales.csv --preset ecommerce --plots --fun

🔌 Extend with Plugins

Build custom analysis functions:

from fasteda.plugins import register_plugin

@register_plugin("outlier_detection")
def detect_outliers(df, threshold=1.5):
    # Your custom analysis
    return results

📦 Supported Formats

• 📄 CSV (.csv)
• 📊 Excel (.xlsx, .xls)
• 🗂️ JSON (.json)
• ⚡ Parquet (.parquet)

🌟 Why SpeedyEDA?

Before SpeedyEDA:

import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns

df = pd.read_csv("data.csv")
print(df.describe())
print(df.info())
print(df.isnull().sum())
plt.figure(figsize=(10,6))
# ... 20+ more lines of boilerplate ...

With SpeedyEDA:

fasteda data.csv --fun

✨ One command. Complete analysis. Beautiful output.

🤝 Contributing

We'd love your help making SpeedyEDA even better!

• 🐛 Found a bug? Open an issue
• 💡 Have an idea? Start a discussion
• 🎨 Want to contribute? Submit a PR
• ⭐ Love SpeedyEDA? Star the repo!

📄 License

MIT License - see LICENSE file for details.

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Made with ❤️ by Dawaman

If SpeedyEDA saves you time, ⭐ star the repo to show your support!

🐛 Report Bug · 💡 Request Feature · 📖 Documentation