# codebasics/py

Repository to store sample python programs for python learning

Repository: https://github.com/codebasics/py
Canonical: https://ross.abutalabs.com/products/py
Language: Jupyter Notebook
License Family: other
Topics: python, pandas, pandas-dataframe, pandas-tutorial, numpy, numpy-arrays, numpy-tutorial, python-tutorial, python-tutorials, python-pandas, jupyter-notebook, jupyter, jupyter-notebooks, jupyter-tutorial
Last push: 2025-07-24T04:42:19+00:00

## Health v2 (maintenance only)
Score: 47/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 33, release rhythm 35, longevity 100
- inputs: {"age_days": 3931, "days_push": 405, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 7327, forks 16789 (observed 2026-08-28T04:09:58.246170+00:00)

## What it is
A collection of sample Python programs and Jupyter notebooks for learning Python, pandas, and numpy. It is aimed at beginners and accompanies the codebasics YouTube tutorials.

## Use cases
- learn python from scratch
- pandas dataframe tutorial examples
- numpy array practice notebooks
- beginner python sample programs
- jupyter notebook exercises for data science

## When to choose
- you are a beginner learning Python basics
- you want hands-on pandas and numpy examples
- you prefer learning via notebooks alongside video tutorials

## When to avoid
- you need production-ready code or libraries
- you need a licensed, maintained software package
- you want advanced or comprehensive data science coverage

## Facets
- artifact type: learning-resource
- maturity: active
- function: developer-tools
- domain: education, tutorials, data-science
- platform: python
- tags: python-tutorial, pandas, numpy, jupyter-notebook, beginner, sample-code

## Member repositories
- codebasics/py (main) score 47

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:09:58.246170+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T17:38:30.370918+00:00, confidence not recorded.
  - readme: https://github.com/codebasics/py (fetched 2026-08-28T04:09:58.246170+00:00, sha c8abe39c0adb)
- Data as of 2026-08-30T08:39:29.467469+00:00.