Create a TDAnalyticResult object from a teradataml Dataframe created on an Analytic Result Table (ART) which can be used as input to Unbounded Array Framework functions.
The primary use of an analytical result table (ART) is to associate function results with a name label, enabling users to easily retrieve the result data and pass the result to another UAF function.
An ART can have multiple layers. Each layer has its own dedicated row composition for the series or matrix.
Any operations like filter, select, sum, and so on, over TDAnalyticResult returns a teradataml DataFrame.
Required Arguments:
- data: Specifies the teradataml DataFrame.
Optional Arguments
- id_sequence: Specifies a sequence of series to plot.
- payload_field: Specifies the names of the fields for payload.
- payload_content: Specifies the payload content type.Permitted values:
- "REAL"
- "COMPLEX"
- "AMPL_PHASE"
- "AMPL_PHASE_RADIANS"
- "AMPL_PHASE_DEGREES"
- "MULTIVAR_REAL"
- "MULTIVAR_COMPLEX"
- "MULTIVAR_ANYTYPE"
- "MULTIVAR_AMPL_PHASE"
- "MULTIVAR_AMPL_PHASE_RADIANS "
- "MULTIVAR_AMPL_PHASE_DEGREES"
- layer: Specifies the layer name of the ART table, if dataframe is created on ART table.
Example 1: Prepare input for UAF function using an Analytic Result Table (ART)
>>> from teradataml import create_context >>> con = create_context(host=host, user= user, password=password)
# Create a Analytic Result Table(ART) by executing SInfo function. >>> from teradataml import load_example_data, SInfo >>> load_example_data("uaf", ["ocean_buoys2"])
# Create teradataml DataFrame object. >>> data = DataFrame.from_table("ocean_buoys2")
# Create teradataml TDSeries object. >>> data_series_df = TDSeries(data=data, id=["ocean_name","buoyid"], row_index="TD_TIMECODE", row_index_style="TIMECODE", payload_field="jsoncol.Measure.salinity", payload_content="REAL")
# Execute SInfo function and store the output in 'TSINFO_RESULTS'. >>> uaf_out = SInfo(data=data_series_df, output_table_name='TSINFO_RESULTS')
# Create a teradataml dataframe on 'TSINFO_RESULTS' ART. >>> art_df = DataFrame('TSINFO_RESULTS')
# Check if the DataFrame 'art_table' is created on an ART. >>> art_df.is_art True
# Create TDAnalyticResult object which can be used as input in UAF functions. >>> result = TDAnalyticResult(data=art_df)
# Check if 'result' is created on an ART. >>> result.is_art True
>>> result buoyid ROW_I INDEX_DT INDEX_BEGIN INDEX_END NUM_ENTRIES DISCRETE SAMPLE_INTERVAL CONTENT MIN_MAG_salinity MAX_MAG_salinity AVG_MAG_salinity RMS_MAG_salinity HAS_NULL_NAN_INF 0 44 1 TIMESTAMP(6) 2014-01-06 10:00:24.000000 2014-01-06 10:52:00.000009 13 0 MICROSECONDS(258000001) REAL 55.0 55.0 55.0 55.0 N 1 0 1 TIMESTAMP(6) 2014-01-06 08:00:00.000000 2014-01-06 08:10:00.000000 5 0 SECONDS(150) REAL 55.0 55.0 55.0 55.0 N 2 2 1 TIMESTAMP(6) 2014-01-06 21:01:25.122200 2014-01-06 21:03:25.122200 3 1 MINUTES(1) REAL 55.0 55.0 55.0 55.0 N 3 1 1 TIMESTAMP(6) 2014-01-06 09:01:25.122200 2014-01-06 09:03:25.122200 6 0 SECONDS(24) REAL 55.0 55.0 55.0 55.0 N