Introduction to Teradata Package for Python - Introduction to Teradata Package for Python - Teradata Vantage

Teradata® VantageCloud Lake

Deployment
VantageCloud
Edition
Lake
Product
Teradata Vantage
Published
January 2023
Language
English (United States)
Last Update
2024-04-03
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Using the Teradata Package for Python (teradataml)

The Teradata Package for Python (teradataml) is an open-source Python library package that combines the benefits of open-source Python language environment with the massive parallel processing capabilities of Teradata Vantage.

The purpose of this document is to help data scientists:
  • Describe available features and functionalities of teradataml.
  • Install, uninstall, and upgrade the teradataml package.
  • Connect to Vantage.
  • Use teradataml for data management, exploration, and execution of analytic functions.
  • Understand limitations and considerations of teradataml.

Why Would I Use this Content?

The teradataml package is a Python library package like other open-source Python packages. The package interface makes available to Python users a collection of functions for analytics that reside on Vantage, so that Python users can perform in-database analytics with no SQL coding required. Also, the teradataml package provides functions for data manipulation and transformation, data filtering and sub-setting, and can be used in conjunction with open-source Python capabilities.

How Do I Use this Content?

Use this guide as a reference to find descriptions, usage notes, and examples of features and functions available in the teradataml package.

How Do I Get Started?

Then you can load data, manipulate and transform data for analysis, and execute analytic functions.

References to Other Relevant Content

On the Teradata documentation web site https://docs.teradata.com/:
  • Teradata Package for Python Function Reference on VantageCloud Lake, B700-4500
  • Teradata Vantage™ - Analytics Database Analytic Functions, B035-1206
  • Build Scalable Python Analytics with Open Analytics Framework