patito.DataFrame.read_csv

classmethod DataFrame.read_csv(*args, **kwargs)

Read CSV and apply correct column name and types from model.

If any fields have derived_from specified, the given expression will be used to populate the given column(s).

Parameters:

• *args – All positional arguments are forwarded to polars.read_csv.

• **kwargs – All keyword arguments are forwarded to polars.read_csv.

Returns:

A dataframe representing the given CSV file data.

Return type:

DataFrame[Model]

Examples

The DataFrame.read_csv method can be used to automatically set the correct column names when reading CSV files without headers.

>>> import io
>>> import patito as pt
>>> class CSVModel(pt.Model):
...     a: float
...     b: str
...
>>> csv_file = io.StringIO("1,2")
>>> CSVModel.DataFrame.read_csv(csv_file, has_header=False)
shape: (1, 2)
┌─────┬─────┐
│ a   ┆ b   │
│ --- ┆ --- │
│ f64 ┆ str │
╞═════╪═════╡
│ 1.0 ┆ 2   │
└─────┴─────┘

The derived_from paramater of pt.Field allows you to specify the mapping between the CSV file’s column names, and the final column names you intend to construct.

>>> import io
>>> import patito as pt
>>> class CSVModel(pt.Model):
...     a: float
...     b: str = pt.Field(derived_from="source_of_b")
...
>>> csv_file = io.StringIO("a,source_of_b\n1,1")

# >>> CSVModel.DataFrame.read_csv(csv_file).drop() # shape: (1, 2) # ┌─────┬─────┐ # │ a ┆ b │ # │ — ┆ — │ # │ f64 ┆ str │ # ╞═════╪═════╡ # │ 1.0 ┆ 1 │ # └─────┴─────┘