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Teradata Vantage Python package for Advanced Analytics

Project description

Teradata Python package for Advanced Analytics.

teradataml makes available to Python users a collection of analytic functions that reside on Teradata Vantage. This allows users to perform analytics with no SQL coding. In addition, teradataml library provides functions for scaling data manipulation and transformation, data filtering and sub-setting, and can be used in conjunction with other open-source python libraries.

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For Teradata customer support, please visit Teradata Access.

Table of Contents

Installation and Requirements

Package Requirements:

  • Python 3.4.3 or later

Note: 32-bit Python is not supported.

Minimum System Requirements:

  • Windows 7 (64Bit) or later
  • macOS 10.9 (64Bit) or later
  • Teradata Vantage:
    • Teradata Database 16.20 Feature Update 1
    • Teradata Machine Learning Engine


Use pip to install the Teradata Python Package for Advanced Analytics.

Platform Command
macOS pip install teradataml
Windows py -3 -m pip install teradataml

When upgrading to a new version of the Teradata Python Package, you may need to use pip install's --no-cache-dir option to force the download of the new version.

Platform Command
macOS pip install --no-cache-dir -U teradataml
Windows py -3 -m pip install --no-cache-dir -U teradataml

Using the Teradata Python Package

Your Python script must import the teradataml package in order to use the Teradata Python Package:

>>> import teradataml as tdml
>>> from teradataml import create_context, get_context, remove_context
>>> create_context(host = 'hostname', username = 'user', password = 'password')
>>> df = tdml.DataFrame('my_table')
>>> df
                id masters   gpa     stats programming  admitted
            0  34.0     yes  3.85  advanced    beginner       0.0
            1   6.0     yes  3.50  beginner    advanced       1.0
            2  36.0      no  3.00  advanced      novice       0.0
            3  15.0     yes  4.00  advanced    advanced       1.0
            4  18.0     yes  3.81  advanced    advanced       1.0
            5  13.0      no  4.00  advanced      novice       1.0
            6  38.0     yes  2.65  advanced    beginner       1.0
            7  19.0     yes  1.98  advanced    advanced       0.0
            8  17.0      no  3.83  advanced    advanced       1.0
            9  29.0     yes  4.00    novice    beginner       0.0

>>> select_df =['id', 'masters']) 

>>> filtered_df = df[(df.masters == 'yes') | ( > 10)]

>>> remove_context()


General product information, including installation instructions, is available in the Teradata Documentation website

  • Teradata Python Package User Guide – B700-4006
  • Teradata Python Package Function Reference – B700-4008


Use of the Teradata Python Package is governed by the License Agreement for the teradataml version After installation, the LICENSE and LICENSE-3RD-PARTY files are located in the teradataml directory of the Python installation directory.

Release Notes:

teradataml is the first release version. Please refer to the Teradata Python Package User Guide for a list of Limitations and Usage Considerations.

Teradata Python Package – teradataml
Teradata Vantage Client Python Analytic library

Copyright 2018, Teradata. All Rights Reserved.

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