pandas.api.extensions.ExtensionDtype

class pandas.api.extensions.ExtensionDtype[source]

A custom data type, to be paired with an ExtensionArray.

New in version 0.23.0.

Notes

The interface includes the following abstract methods that must be implemented by subclasses:

  • type
  • name
  • construct_from_string

The following attributes influence the behavior of the dtype in pandas operations

  • _is_numeric
  • _is_boolean

Optionally one can override construct_array_type for construction with the name of this dtype via the Registry. See pandas.api.extensions.register_extension_dtype().

  • construct_array_type

The na_value class attribute can be used to set the default NA value for this type. numpy.nan is used by default.

ExtensionDtypes are required to be hashable. The base class provides a default implementation, which relies on the _metadata class attribute. _metadata should be a tuple containing the strings that define your data type. For example, with PeriodDtype that’s the freq attribute.

If you have a parametrized dtype you should set the ``_metadata`` class property.

Ideally, the attributes in _metadata will match the parameters to your ExtensionDtype.__init__ (if any). If any of the attributes in _metadata don’t implement the standard __eq__ or __hash__, the default implementations here will not work.

Changed in version 0.24.0: Added _metadata, __hash__, and changed the default definition of __eq__.

This class does not inherit from ‘abc.ABCMeta’ for performance reasons. Methods and properties required by the interface raise pandas.errors.AbstractMethodError and no register method is provided for registering virtual subclasses.

Attributes

kind A character code (one of ‘biufcmMOSUV’), default ‘O’
name A string identifying the data type.
names Ordered list of field names, or None if there are no fields.
type The scalar type for the array, e.g.

Methods

construct_array_type() Return the array type associated with this dtype
construct_from_string(string) Attempt to construct this type from a string.
is_dtype(dtype) Check if we match ‘dtype’.
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