Skip to main content

A one-line interactive EDA tool using Streamlit

Project description

Quick-EDA

📊 A powerful interactive Exploratory Data Analysis tool that launches a Streamlit interface for your pandas DataFrames with just one line of code.

Installation

pip install quick-eda

Quick Start

import pandas as pd
from quick_eda import analyze

# Load your data
df = pd.read_csv('your_data.csv')  # or any pandas DataFrame

# Launch the EDA interface
analyze(df)

That's it! The tool will automatically:

  1. Launch a Streamlit server
  2. Open your default web browser to the EDA interface
  3. Display interactive visualizations and analysis of your data

Features

  • 🚀 One-Line Setup: Just analyze(df) to start exploring
  • 📊 Interactive Visualizations: Dynamic charts and plots
  • 🔍 Data Quality Analysis:
    • Missing values detection
    • Outlier analysis
    • Data type validation
    • Consistency checks
  • 📈 Automated Insights:
    • Distribution analysis
    • Correlation detection
    • Time series patterns
    • Text analysis
  • 💡 Smart Suggestions: Get recommendations for data cleaning and transformation

Advanced Usage

from quick_eda import analyze

# Specify a custom port
analyze(df)

Requirements

  • Python 3.9+
  • pandas 2.0.0+
  • streamlit 1.44.0+

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

MIT License

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

explore_df-0.1.0.tar.gz (29.9 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

explore_df-0.1.0-py3-none-any.whl (42.1 kB view details)

Uploaded Python 3

File details

Details for the file explore_df-0.1.0.tar.gz.

File metadata

  • Download URL: explore_df-0.1.0.tar.gz
  • Upload date:
  • Size: 29.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.11.7

File hashes

Hashes for explore_df-0.1.0.tar.gz
Algorithm Hash digest
SHA256 2be7ba0f133221b3fb14d186ae71606975e66293a4e4e5588c14f93b6676ebb0
MD5 540c9620c60cfe3ce5cf1f3aedc5de21
BLAKE2b-256 a51201b0d314990562f2d824e316b2d5e08ca6d061616468a0baae3cf4b99f2c

See more details on using hashes here.

File details

Details for the file explore_df-0.1.0-py3-none-any.whl.

File metadata

  • Download URL: explore_df-0.1.0-py3-none-any.whl
  • Upload date:
  • Size: 42.1 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.11.7

File hashes

Hashes for explore_df-0.1.0-py3-none-any.whl
Algorithm Hash digest
SHA256 c0477fc022114d9b32d4469e406f8594126c6004f52760c99bee851f5282eb36
MD5 fcd177aa7dbef71d3de239d5aa882a3e
BLAKE2b-256 463478e1123e535f814bad33c0d158d8c7bb780fd8c0708ec54dec863c23c7de

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page