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.
- 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
- Teradata Package for Python Function Reference, B700-4008
- Teradata Vantage™ Machine Learning Engine Analytic Function Reference, B700-4003
- Teradata Vantage™ - Analytics Database Analytic Functions, B035-1206
- Teradata Package for R User Guide, B700-4005
- Teradata Package for R Function Reference, B700-4007
- Teradata Vantage™ Modules for Jupyter Installation Guide, B700-4010
- For VantageCloud Lake only: Build Scalable Python Analytics with Open Analytics Framework
- Teradata SQL Driver for Python (teradatasql)
- Teradata SQL Driver Dialect for SQLAlchemy (teradatasqlalchemy)