patito.DataFrame.get

DataFrame.get(predicate=None)

Fetch the single row that matches the given polars predicate.

If you expect a data frame to already consist of one single row, you can use .get() without any arguments to return that row.

Raises

RowDoesNotExist – If zero rows evaluate to true for the given predicate.
MultipleRowsReturned – If more than one row evaluates to true for the given predicate.
RuntimeError – The superclass of both RowDoesNotExist and MultipleRowsReturned if you want to catch both exceptions with the same class.

Parameters

predicate (Optional[Expr]) – A polars expression defining the criteria of the filter.

Returns

A pydantic-derived base model representing the given row.

Return type

Model

Example

>>> import patito as pt
>>> import polars as pl
>>> df = pt.DataFrame({"product_id": [1, 2, 3], "price": [10, 10, 20]})

The .get() will by default return a dynamically constructed pydantic model if no model has been associated with the given dataframe:

>>> df.get(pl.col("product_id") == 1)
UntypedRow(product_id=1, price=10)

If a Patito model has been associated with the dataframe, by the use of DataFrame.set_model(), then the given model will be used to represent the return type:

>>> class Product(pt.Model):
...     product_id: int = pt.Field(unique=True)
...     price: float
...
>>> df.set_model(Product).get(pl.col("product_id") == 1)
Product(product_id=1, price=10.0)

You can invoke .get() without any arguments on dataframes containing exactly one row:

>>> df.filter(pl.col("product_id") == 1).get()
UntypedRow(product_id=1, price=10)

If the given predicate matches multiple rows a MultipleRowsReturned will be raised:

>>> try:
...     df.get(pl.col("price") == 10)
... except pt.exceptions.MultipleRowsReturned as e:
...     print(e)
...
DataFrame.get() yielded 2 rows.

If the given predicate matches zero rows a RowDoesNotExist will be raised:

>>> try:
...     df.get(pl.col("price") == 0)
... except pt.exceptions.RowDoesNotExist as e:
...     print(e)
...
DataFrame.get() yielded 0 rows.