pandera.schema_components.Column¶

class pandera.schema_components.Column(pandas_dtype=None, checks=None, nullable=False, allow_duplicates=True, coerce=False, required=True, name=None, regex=False)[source]¶

Validate types and properties of DataFrame columns.

Create column validator object.

Parameters

pandas_dtype (Union[str, type, PandasDtype, ExtensionDtype, dtype, None]) – datatype of the column. A PandasDtype for type-checking dataframe. If a string is specified, then assumes one of the valid pandas string values: http://pandas.pydata.org/pandas-docs/stable/basics.html#dtypes
checks (Union[Check, Hypothesis, List[Union[Check, Hypothesis]], None]) – checks to verify validity of the column
nullable (bool) – Whether or not column can contain null values.
allow_duplicates (bool) – Whether or not column can contain duplicate values.
coerce (bool) – If True, when schema.validate is called the column will be coerced into the specified dtype.
required (bool) – Whether or not column is allowed to be missing
name (Optional[str]) – column name in dataframe to validate.
regex (bool) – whether the name attribute should be treated as a regex pattern to apply to multiple columns in a dataframe.

Raises

SchemaInitError – if impossible to build schema from parameters

Example

>>> import pandas as pd
>>> import pandera as pa
>>>
>>>
>>> schema = pa.DataFrameSchema({
...     "column": pa.Column(pa.String)
... })
>>>
>>> schema.validate(pd.DataFrame({"column": ["foo", "bar"]}))
  column
0    foo
1    bar

See here for more usage details.

Attributes

`allow_duplicates`	Whether to allow duplicate values.
`checks`	Return list of checks or hypotheses.
`coerce`	Whether to coerce series to specified type.
`dtype`	String representation of the dtype.
`has_subcomponents`
`name`	Get SeriesSchema name.
`nullable`	Whether the series is nullable.
`pandas_dtype`	Get the pandas dtype
`pdtype`	PandasDtype of the series.
`properties`	Get column properties.
`regex`	True if `name` attribute should be treated as a regex pattern.

Methods

`__init__`	Create column validator object.
`coerce_dtype`	Coerce dtype of a column, handling duplicate column names.
`example`	Generate an example of a particular size.
`get_regex_columns`	Get matching column names based on regex column name pattern.
`set_name`	Used to set or modify the name of a column object.
`strategy`	Create a `hypothesis` strategy for generating a Column.
`strategy_component`	Generate column data object for use by DataFrame strategy.
`validate`	Validate a Column in a DataFrame object.
`__call__`	Alias for `validate` method.