pandas backend adapter for PlanFrame.
Project description
planframe-pandas
pandas adapter package for PlanFrame. Import as planframe_pandas.
Documentation (ReadTheDocs):
- pandas track (end users):
https://planframe.readthedocs.io/en/latest/planframe_pandas/ - Light API reference:
https://planframe.readthedocs.io/en/latest/planframe_pandas/reference/api/
Install
pip install planframe-pandas
Usage
from planframe_pandas import PandasFrame
class User(PandasFrame):
id: int
age: int
pf = User([{"id": 1, "age": 10}, {"id": 2, "age": 20}])
rows = pf.select("id").to_dicts()
Notes
PandasFramesubclasses coreplanframe.pandas.PandasLikeFrame, so you get pandas-flavored helpers (assign,sort_values, boolean indexing, columnfilter,astype,eval,drop_duplicates, …) on top of the sharedFrameplan. See the pandas-like API guide.- PlanFrame is always lazy: chaining does not touch backend data; execution happens at
collect()boundaries. collect()returnslist[pydantic.BaseModel]. Usecollect_backend()for apandas.DataFrame, orstream_dicts()/stream()to iterate rows (see Streaming rows).
Common transforms
with_row_index(name="row_nr", offset=0): add a monotonically increasing row number column.clip(lower=..., upper=..., subset=...): clamp numeric columns (ifsubset=None, clamps all numeric schema fields).cast_many/cast_subset: multi-column cast helpers.fill_null_many/fill_null_subset: multi-column fill-null helpers.rename_upper/lower/title/strip(...): schema-driven rename helpers.pivot_longer(...)/pivot_wider(...): reshape convenience wrappers aroundmelt/pivot.
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