Data Model Classes
|
Declare the entity to be (or to contain) boolean (True or False) values. If not specified, the default value is False.
|
|
|
Represent a single column within a DataFrame entity. Outside the Python model (e.g. VDL, Tableau), the column will be represented as a separate entity whose name combines the names of the DataFrame and the Column, concatenated by an underscore, i.e. MyDataFrame_MyColumnName
|
|
|
Initializes Column.
|
|
|
The configuration of a DataFrame entity. Use the helper function xpressinsight.types.DataFrame to declare a DataFrame entity in an app, rather than instantiating xpressinsight.DataFrame directly.
|
|
|
Initializes DataFrame.
|
|
|
Abstract base class of all Insight entities, including composed entities like DataFrames.
|
|
|
Possible values of whether the UI should hide an entity where appropriate.
|
|
|
The configuration of an index entity. Use the helper function xpressinsight.types.Index to declare an index entity in an app, rather than instantiating xpressinsight.Index directly.
|
|
|
The constructor.
|
|
|
Declare the entity to be (or to contain) integer (whole number) values. Each value must fit into a signed 32-bit integer. If not specified, the default value is 0.
|
|
|
How and whether Insight handles an entity.
|
|
|
The configuration of a parameter entity. Parameters can be used to configure an Xpress Insight app. When parameters are declared, their name, data type, and default value must be specified. Parameters are typically read-only. Use the helper function xpressinsight.types.Param to declare a parameter entity in an app, rather than instantiating xpressinsight.Param directly.
|
|
|
Initializes Param with the data type or a default value (in which case data type is inferred).
|
|
|
Declare the entity to be (or to contain) floating-point (whole number) values. If not specified, the default value is 0.0.
|
|
|
The configuration of a scalar entity. Use the helper function xpressinsight.types.Scalar to declare a scalar entity in an app, rather than instantiating xpressinsight.Scalar directly.
|
|
|
The constructor.
|
|
|
The configuration of a Series entity, a declaration of a pandas Series data structure. Use the helper function xpressinsight.types.Series to declare a Series entity in an app, rather than instantiating xpressinsight.Series directly.
|
|
|
Initializes Series.
|
|
|
Declare the entity to be (or to contain) string (UTF-8 encoded) values. The length (in bytes) of a string scalar (Scalar or Param) must not exceed 1,000,000 bytes. The length of a string in a container (Index, Series, or DataFrame) must not exceed 250,000 characters. A string must not contain the null character. If not specified, the default value of a string scalar is the empty string "".
|
© 2001-2023 Fair Isaac Corporation. All rights reserved. This documentation is the property of Fair Isaac Corporation (“FICO”). Receipt or possession of this documentation does not convey rights to disclose, reproduce, make derivative works, use, or allow others to use it except solely for internal evaluation purposes to determine whether to purchase a license to the software described in this documentation, or as otherwise set forth in a written software license agreement between you and FICO (or a FICO affiliate). Use of this documentation and the software described in it must conform strictly to the foregoing permitted uses, and no other use is permitted.