pandera.schemas.DataFrameSchema.remove_columns#

DataFrameSchema.remove_columns(cols_to_remove)[source]#

Removes columns from a DataFrameSchema and returns a new copy.

Parameters: cols_to_remove (List) – Columns to be removed from the DataFrameSchema
Return type: ForwardRef
Returns: a new DataFrameSchema without the cols_to_remove
Raises: SchemaInitError: if column not in schema.
Example

To remove a column or set of columns from a schema, pass a list of columns to be removed:

>>> import pandera as pa
>>>
>>> example_schema = pa.DataFrameSchema(
...     {
...         "category" : pa.Column(str),
...         "probability": pa.Column(float)
...     }
... )
>>>
>>> print(example_schema.remove_columns(["category"]))
<Schema DataFrameSchema(
    columns={
        'probability': <Schema Column(name=probability, type=DataType(float64))>
    },
    checks=[],
    coerce=False,
    dtype=None,
    index=None,
    strict=False
    name=None,
    ordered=False,
    unique_column_names=False
)>