xl0/lovely-numpy
NumPy arrays, ready for human consumption
When working with NumPy arrays in data science or machine learning, it can be hard to quickly understand what the data represents. This tool takes a raw NumPy array and transforms its output into a human-readable summary, including statistics, value ranges, and visualizations. Data scientists, machine learning engineers, and researchers can use this to quickly inspect and debug their numerical data.
Used by 3 other packages. Available on PyPI.
Use this if you frequently inspect NumPy arrays and want a concise, informative summary and visualization instead of raw numbers.
Not ideal if you primarily need to manipulate NumPy arrays programmatically without visual inspection or debugging.
Stars
72
Forks
5
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Mar 11, 2026
Commits (30d)
0
Dependencies
3
Reverse dependents
3
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/xl0/lovely-numpy"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Compare
Related frameworks
Emmanuel10701/Numpy
Numpy
somayajulukrishna020-lang/numpy-documentation
A structured, hands-on guide to NumPy — the foundation of numerical computing in Python.
DenshellDenejour/AI_with_Numpy
Numpy is a library of Python as Keras, Jupyter, Tkinter or Matpolib
Akash-9794/numpy-100-challenges
Learning NumPy for ML? This repo takes you from absolute basics to ML-level array operations...
25f2005869-glitch/NumPy-For-Data-Science
NumPy learning repository with step-by-step practice, array operations, indexing, slicing, and...