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.
For community support, please visit the Connectivity Forum.
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 08.00.00.00
Installation
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 = df.select(['id', 'masters'])
>>> filtered_df = df[(df.masters == 'yes') | (df.id > 10)]
>>> remove_context()
Documentation
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
License
Use of the Teradata Python Package is governed by the License Agreement for the teradataml version 16.20.00.00.
After installation, the LICENSE
and LICENSE-3RD-PARTY
files are located in the teradataml
directory of the Python installation directory.
Release Notes:
teradataml 16.20.00.00
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 16.20.00.00
Teradata Vantage Client Python Analytic library
Copyright 2018, Teradata. All Rights Reserved.
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