df_type | Teradata Package for Python - df_type - Teradata Package for Python

Use the df_type property to return a type of DataFrame based on the underlying database object.

Example setup

Load the data.

>>> load_example_data("teradataml", "Employee_roles") # load valid time data.
>>> load_example_data("teradataml", "Employee_Address") # load transaction time data.
>>> load_example_data("teradataml", "Employee") # load bitemporal data.
>>> load_example_data("uaf", ["ocean_buoys2"]) # load data to create art table.
>>> load_example_data('dataframe', ['admissions_train']) # load data to create a regular table.

Example 1: DataFrame created on a Valid-Time dimension table

>>> df = DataFrame.from_table('Employee_roles')

>>> df.df_type

'VALID_TIME'

Example 2: DataFrame created on a Transaction-Time dimension table

>>> df = DataFrame.from_table('Employee_Address')

>>> df.df_type

'TRANSACTION_TIME'

Example 3: DataFrame created on a bi-temporal dimension table

>>> df = DataFrame.from_table('Employee')

>>> df.df_type

'BI_TEMPORAL'

Example 4: DataFrame created on an ART table

>>> data = DataFrame.from_table('ocean_buoys2')
>>> from teradataml import TDSeries,SInfo
>>> 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")
>>> uaf_out = SInfo(data=data_series_df, output_table_name='TSINFO_RESULTS')
>>> df = DataFrame.from_table('TSINFO_RESULTS')

>>> df.df_type

'ART'

Example 5: DataFrame created on a regular table

>>> df = DataFrame.from_table('admissions_train')

>>> df.df_type

'REGULAR_TABLE'

Example 6: DataFrame created on a volatile table

>>> df = DataFrame.from_table('admissions_train')
>>> df.to_sql(table_name='admissions_train_volatile', temporary=True)
>>> df = DataFrame.from_table('admissions_train_volatile')

>>> df.df_type

'VOLATILE_TABLE'

Example 7: DataFrame created on a Bi-temporal dimension view

>>> execute_sql('create view Employee_view AS SEQUENCED  VALIDTIME AND SEQUENCED TRANSACTIONTIME select * from Employee')
>>> df = DataFrame.from_table('Employee_view')

>>> df.df_type

'BI_TEMPORAL_VIEW'