Data in JSON or CSV Format | Native Object Store | Teradata Python Package - Data in JSON or CSV Format - 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
dita:mapPath
nvi1706202040305.ditamap
dita:ditavalPath
plt1683835213376.ditaval
dita:id
rkb1531260709148
Product Category
Teradata Vantage
Foreign table created in JSON or comma-separated values (CSV) format typically contains two columns:
  • Location
  • Payload
You can create a teradataml DataFrame on a foreign table using "DataFrame()" or "DataFrame.from_table()", the same way to create a teradataml DataFrame on a regular table. With the created DataFrame, you can easily access the data in these columns and process the data using teradataml DataFrame API or other Python packages.
Though teradataml provides direct access to the data in foreign tables, actual data that resides in 'Payload' column and path variables for the foreign table can be accessed in one of the following ways: