TDGenSeries | Input Classes for UAF Functions | teradataml - TDGenSeries - Teradata Package for Python

Teradata® Package for Python User Guide

Deployment
VantageCloud
VantageCore
Edition
Enterprise
IntelliFlex
VMware
Product
Teradata Package for Python
Release Number
20.00
Published
March 2024
Language
English (United States)
Last Update
2024-04-09
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Product Category
Teradata Vantage

Generate a series to a UAF function rather than using a pre-existing series instance. It contains all the information that would have been derivable from a TDSeries as well as the information required to generate the series.

The TDGenSeries can only be passed to a function that accepts a single series as input.

Generated series have a indexing mechanism which starts at integer 0 and increments by 1 for each additional generated entry.

Required Arguments:
  • instances: Specifies the columns and values for the generated series.
  • data_types: Specifies the data types of the identifying columns for the generated series.
  • start: Specifies the start value for the information about how the series payload, containing successive real magnitude values.
  • offset: Specifies the offset value for the information about how the series payload, containing successive real magnitude values.
  • num_entries: Specifies the number of entries for the information about how the series payload, containing successive real magnitude values.

Example 1: Create a TDGenSeries object

# Import TDGenSeries.
>>> from teradataml import TDGenSeries
# Import INTEGER type from teradatasqlalchemy.
>>> from teradatasqlalchemy.types import INTEGER
# Create a TDGenSeries object to be passed as input to UAF functions.
>>> series = TDGenSeries(instances = {"BuoyID": 3}, data_types = INTEGER(), start=0, offset=1, num_entries=5)