# guipsamora/pandas_exercises

Practice your pandas skills!

Repository: https://github.com/guipsamora/pandas_exercises
Canonical: https://ross.abutalabs.com/products/pandas_exercises
Language: Jupyter Notebook
License: BSD-3-Clause
License Family: permissive
Topics: pandas, jupyter-notebooks, pandas-tutorial, python-pandas
Last push: 2025-10-17T13:45:08+00:00

## Health v2 (maintenance only)
Score: 53/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 47, release rhythm 35, longevity 100
- inputs: {"age_days": 3704, "days_push": 320, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 13053, forks 9033 (observed 2026-08-28T04:11:01.862898+00:00)

## What it is
A collection of hands-on exercises for practicing the pandas data analysis library in Python, organized by topic with instructions and solutions. Each lesson comes as Jupyter notebooks covering skills like filtering, grouping, merging, and time series.

## Use cases
- practice pandas skills with exercises
- learn pandas through hands-on problems
- find pandas practice problems with solutions
- improve dataframe manipulation skills
- supplement a pandas tutorial with exercises
- prepare for data analysis interviews

## When to choose
- you already know basic Python and want to practice pandas by doing
- you want topic-organized exercises with solutions to check against
- you prefer notebooks you can run and modify yourself

## When to avoid
- you need a structured tutorial that teaches pandas concepts from scratch
- you are looking for a pandas library or tool rather than learning material
- you need exercises for libraries other than pandas

## Facets
- artifact type: learning-resource
- maturity: active
- function: data-science
- domain: data-science, education, tutorials
- platform: python
- tags: pandas, jupyter-notebooks, exercises, practice-problems, dataframe

## Member repositories
- guipsamora/pandas_exercises (main) score 53

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:11:01.862898+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 2026-08-29T17:13:34.198399+00:00, confidence not recorded.
  - readme: https://github.com/guipsamora/pandas_exercises (fetched 2026-08-28T04:11:01.862898+00:00, sha 462281102fd4)
- Data as of 2026-08-30T08:39:29.467469+00:00.