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Unified Python package for data science - pandas, numpy, matplotlib, and scikit-learn under one import.

Project description

npms 📦

PyPI version License: MIT Python 3.8+ Platform

Unified Python package for data science — pandas, numpy, matplotlib, and scikit-learn under one single import.


Install

pip install npms

Usage

import npms as ns

# Pandas
df = ns.DataFrame({'A': [1, 2, 3], 'B': [4, 5, 6]})
print(df)

# NumPy
arr = ns.array([1, 2, 3, 4, 5])
print(ns.mean(arr))

# Matplotlib
ns.plot([1, 2, 3], [1, 4, 9])
ns.xlabel('X')
ns.ylabel('Y')
ns.show()

# Scikit-learn
from npms import linear_model
model = linear_model.LinearRegression()

What's included

Library Purpose
pandas Data manipulation and analysis
numpy Numerical computing
matplotlib Data visualization
scikit-learn Machine learning

Features

  • ✅ Single import for all major data science libraries
  • ✅ Simplified namespace — use ns. for everything
  • ✅ Auto-installs all dependencies
  • ✅ Works on Windows, macOS, Linux

License

MIT © 2026 tokitahmidtoufa

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