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Community repository of bamboolib - a GUI for pandas DataFrames 🐼🐍

This is the community repository of bamboolib. There are no source files because bamboolib is closed source. However, you can use bamboolib for free on Open Data via Binder and Kaggle. If you have any issues or feature requests, please open an issue.

bamboolib is a GUI for pandas DataFrames that enables anyone to work with Python in Jupyter Notebook or JupyterLab.

Features

  • Intuitive GUI that exports Python code
  • Supports all common transformations and visualizations
  • Provides best-practice analyses for data exploration
  • Can be arbitrarily customized via simple Python plugins
  • Integrate any internal or external Python library

Main benefits of bamboolib

  • Enables data analysts to work with Python without having to write code
  • Reduces the on-boarding time and training costs for data analysts
  • Removes the organizational divide between GUI and coding tools and creates a single platform & point of truth
  • Enables data analysts to collaborate with data scientists within Jupyter and to share the working results as reproducible code
  • Compared to other enterprise AI platforms, bamboolib creates no technical lock-in and provides the greatest flexibility via leveraging Python
  • Even people who can code use bamboolib because it is faster and easier than writing the code themselves
  • Reduces cognitive load: Focus on what's important instead of spending your time on StackOverflow.

🔍Try bamboolib live on Binder

Installation

Install bamboolib for Jupyter Notebook or Jupyter Lab by running the code below in your terminal (or Anaconda Prompt for Windows):

pip install bamboolib

# Jupyter Notebook extensions
python -m bamboolib install_nbextensions

# JupyterLab extensions
python -m bamboolib install_labextensions

After you have installed bamboolib, you can go here to test bamboolib.

Documentation

You find out how to get started along with tutorials and an API reference on our docs.

Further links

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  • Jupyter Notebook 65.8%
  • Python 34.0%
  • Shell 0.2%