Teradata Package for Python Function Reference on VantageCloud Lake - TDGenSeries - Teradata Package for Python - Look here for syntax, methods and examples for the functions included in the Teradata Package for Python.
Teradata® Package for Python Function Reference on VantageCloud Lake
- Deployment
- VantageCloud
- Edition
- Lake
- Product
- Teradata Package for Python
- Release Number
- 20.00.00.03
- Published
- December 2024
- ft:locale
- en-US
- ft:lastEdition
- 2024-12-19
- dita:id
- TeradataPython_FxRef_Lake_2000
- Product Category
- Teradata Vantage
- teradataml.dataframe.dataframe.TDGenSeries.__init__ = __init__(self, instances, data_types, start, offset, num_entries)
- Generate a series to be passed 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 an indexing mechanism which starts at integer 0 and increments by 1 for each
additional generated entry.
PARAMETERS:
instances:
Required Argument.
Specifies the columns and values for the generated series.
Types: dict
data_types:
Required Argument.
Specifies the data types of the identifying columns for the generated series.
Types: teradatasqlalchemy.types
start:
Required Argument.
Specifies Start value for the information about how the series payload, containing
successive real magnitude values.
Types: float, int
offset:
Required Argument.
Specifies offset value for the information about how the series payload, containing
successive real magnitude values.
Types: float, int
num_entries:
Required Argument.
Specifies number of entries for the information about how the series payload, containing
successive real magnitude values.
Types: int
RAISES:
None
RETURN:
None
EXAMPLES:
# 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)