pandera.api.pandas.components.MultiIndex#
- class pandera.api.pandas.components.MultiIndex(indexes, coerce=False, strict=False, name=None, ordered=True, unique=None)[source]#
Validate types and properties of a DataFrame MultiIndex.
This class inherits from
DataFrameSchema
to leverage its validation logic.Create MultiIndex validator.
- Parameters
indexes (
List
[Index
]) – list of Index validators for each level of the MultiIndex index.coerce (
bool
) – Whether or not to coerce the MultiIndex to the specified dtypes before validationstrict (
bool
) – whether or not to accept columns in the MultiIndex that aren’t defined in theindexes
argument.ordered (
bool
) – whether or not to validate the indexes order.unique (
Union
[str
,List
[str
],None
]) – a list of index names that should be jointly unique.
- Example
>>> import pandas as pd >>> import pandera as pa >>> >>> >>> schema = pa.DataFrameSchema( ... columns={"column": pa.Column(int)}, ... index=pa.MultiIndex([ ... pa.Index(str, ... pa.Check(lambda s: s.isin(["foo", "bar"])), ... name="index0"), ... pa.Index(int, name="index1"), ... ]) ... ) >>> >>> df = pd.DataFrame( ... data={"column": [1, 2, 3]}, ... index=pd.MultiIndex.from_arrays( ... [["foo", "bar", "foo"], [0, 1, 2]], ... names=["index0", "index1"], ... ) ... ) >>> >>> schema.validate(df) column index0 index1 foo 0 1 bar 1 2 foo 2 3
See here for more usage details.
Attributes
BACKEND
coerce
Whether or not to coerce data types.
dtype
Get the dtype property.
dtypes
A dict where the keys are column names and values are
DataType
s for the column.names
Get index names in the MultiIndex schema component.
properties
Get the properties of the schema for serialization purposes.
unique
List of columns that should be jointly unique.
Methods