Add optional pandas helpers: `to_dataframe` / `from_dataframe` for flat dataclasses
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Nobody has claimed this yet.
data-science
enhancement
- Dominant language
- Python
- Stars
- 250
- Forks
- 36
- PR merge metrics
- No merged PRs in 30d
Description
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Goal: Easy DS integration without “pandas serialization”.
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API:
dataclass_wizard.integrations.pandas.to_dataframe(objs) -> pd.DataFrame...from_dataframe(cls, df) -> list[cls]
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Constraints (important):
- Start with flat fields only (nested objects -> error or stringify; decide explicitly).
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Acceptance criteria:
- Optional extra:
dataclass-wizard[pandas] - Docs + a minimal example in README or integrations page.
- Optional extra:
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
No files or tests are named in the issue. Start by reviewing the existing package structure and dependency extras, then define the pandas integration around to_dataframe and from_dataframe for flat dataclasses. Done means the optional pandas extra works, nested-field behavior is explicit, and documentation includes a minimal example.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- pandas, python
- Domain
- data
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100