DataSource stores all details of a Data Source. Data Source can refer to either teradataml DataFrame or SQL query as a source. The following example explains creating a Data Source for sales data.
>>> df = DataFrame("sales")
>>> df
Feb Jan Mar Apr datetime accounts Orange Inc 210.0 NaN NaN 250.0 04/01/2017 Jones LLC 200.0 150.0 140.0 180.0 04/01/2017 Blue Inc 90.0 50.0 95.0 101.0 04/01/2017 Alpha Co 210.0 200.0 215.0 250.0 04/01/2017 Yellow Inc 90.0 NaN NaN NaN 04/01/2017
>>> from teradataml import DataSource
>>> ds = DataSource('Sales_Data', df, timestamp_col_name='datetime', description="Montly sales source")
>>> ds DataSource(Sales_Data) >>>
Properties
- name
- Specifies unique name of the Data Source in the Feature Store.
Example:
>>> ds.name 'Sales_Data'
- timestamp_col_name
- Specifies the name of the column containing the record created time in the dataset.
Example:
>>> ds.timestamp_col_name 'datetime'
- source
- Specifies the source details of the dataset.
Example:
>>> ds.source 'select * from "sales"'
- description
- Specifies the description of DataSource.
Example:
>>> ds.description 'Monthly sales source'