teradatamlwidgets 20.0.0.4

Description:

teradatamlwidgets 20.0.0.4

Teradata Widgets
teradatamlwidgets makes available to Python users a user interface to a collection of analytic functions and plot functions that reside on Teradata Vantage. This package provides Data Scientists and Teradata users a simple UI experience within a Jupyter Notebook to perform analytics and visualization on Teradata Vantage with no SQL coding and limited python coding required.
For documentation and tutorial notebooks please visit Documentation.
For Teradata customer support, please visit Teradata Support.
Copyright 2024, Teradata. All Rights Reserved.
Table of Contents

Release Notes
Installation and Requirements
Using the Teradata Widgets Package
Documentation
License

Release Notes:
teradatamlwidgets 20.0.0.4


New Features/Functionality

None



New APIs:

None



Bug Fixes

Fixed list of SQLE functions



teradatamlwidgets 20.0.0.3


New Features/Functionality

None



New APIs:

None



Bug Fixes

Using native dialog boxes
Parameter name change for Plot (color)



teradatamlwidgets 20.0.0.2


New Features/Functionality

Updated documentation



New APIs:

None



Bug Fixes

Initialized default database



teradatamlwidgets 20.0.0.1


New Features/Functionality

Updated documentation



New APIs:

None



Bug Fixes

None



teradatamlwidgets 20.0.0.0


New Features/Functionality


New APIs:

Analytic functions

teradatamlwidgets.analytic_functions.Ui():
teradatamlwidgets.analytic_functions.get_output_dataframe():


Plotting

teradatamlwidgets.plot.ShowPlots():





Bug Fixes

None



Installation and Requirements
Package Requirements:

Python 3.5 or later

Note: 32-bit Python is not supported.
Minimum System Requirements:

Windows 7 (64Bit) or later
macOS 10.9 (64Bit) or later
Red Hat 7 or later versions
Ubuntu 16.04 or later versions
CentOS 7 or later versions
SLES 12 or later versions
Teradata Vantage Advanced SQL Engine:

Advanced SQL Engine 16.20 Feature Update 1 or later


For a Teradata Vantage system with the ML Engine:

Teradata Machine Learning Engine 08.00.03.01 or later



Installation
Use pip to install the Teradata Widgets Package for Advanced Analytics.



Platform
Command




macOS/Linux
pip install teradatamlwidgets


Windows
py -3 -m pip install teradatamlwidgets



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



Platform
Command




macOS/Linux
pip install --no-cache-dir -U teradatamlwidgets


Windows
py -3 -m pip install --no-cache-dir -U teradatamlwidgets



Using the Teradata Python Package
Your Python script must import the teradatamlwidgets package in order to use the Teradata Widgets Package:
>>> from teradataml import *
>>> Load the example data.
>>> load_example_data("movavg", ["ibm_stock"])
>>> load_example_data("teradataml", "titanic")
>>> inputs = ["ibm_stock"]
>>> outputs = ["Project_OutMovingAverageTest"]
>>> ui = Ui(function= 'MovingAverage',
outputs=outputs,
inputs=inputs)

>>> from teradataml import *
>>> from teradatamlwidgets.plot.Login import *
>>> from teradatamlwidgets.plot.Ui import *
>>> from teradatamlwidgets.plot.ShowPlots import *
>>> # Load the example data.
>>> load_example_data("movavg", "ibm_stock")
>>> load_example_data("teradataml", "iris_input")
>>> # Plot
>>> plot1 = Ui(
table_name="ibm_stock",
current_plot="Line",
x='period',
series='stockprice',
style='green')
>>> plot2 = Ui(
table_name="iris_input",
current_plot="Scatter",
x='sepal_length',
series='petal_length',
xlabel='sepal_length',
ylabel='petal_length',
grid_color='black',
grid_linewidth=1,
grid_linestyle="-",
style='red',
title='Scatter Plot of sepal_length vs petal_length',
heading= 'Scatter Plot Example')
>>> # Combine Plots
>>> ShowPlots([plot1, plot2], nrows=1, ncols=2)



Details


This package is useful to Data Scientists and Teradata users and provides following:


A simple UI experience within Jupyter Notebook.


Access to In-DB analytics


Visualizations


Integration with teradataml


Enable simple and easy integration with 3rd party workbenches




teradatamlwidgets.analytic_functions.Ui Class


Purpose

Opens the function UI dialog in the notebook for the analytic functions (subset of the Analytics Database analytic functions, Vantage Analytics Library (VAL) functions, Unbounded Array Framework (UAF) time series functions).



Syntax

teradatamlwidgets.analytic_functions.Ui(outputs=[], inputs=[], function = '', export_settings = '')



Arguments


outputs:

Optional Argument.
A list with output table(s) name. Specify it as a schema_name.table_name or just table_name. If not specified, a name will be generated at random.
Ex: outputs = [“dssDB.my_output”, “dssDB.my_test”]
Types: List String



inputs:


Required Argument.


Option 1: A list with whichever input table(s) is desired. The tables that are listed will be the options for you to choose from when you choose the function. It is written as schema_name.table_name


Ex: inputs = [“company1_stock”, “titanic”]


Option 2: A teradataml dataframe. It is written as DataFrame(“df_name”)


Ex: inputs = [DataFrame(“company1_stock”), DataFrame(”titanic”)]


Types: List String or List teradataml.DataFrame




function:

Optional Argument.
If a specific function is desired to be selected immediately when the UI shows up, then include the function name.
Ex: function = "Linear Regression VAL"
Types: String



export_settings:

Optional Argument.
In order to load and save your chosen parameters to a file, then set this filename.
Ex: filename="LinReg.json"
Types: String





Function Output

This function will return instance of notebook UI interface.



Usage Considerations

The first time this is called, the “Login” user interface will be displayed so the user can log into a Teradata instance which creates the internal instance.





teradatamlwidgets.analytic_functions.get_output_dataframe Method


Purpose

Gets the DataFrame of the executed function.



Syntax

ui.get_output_dataframe(output_index = 0)



Arguments

output_index:

Optional Argument.
Use this function to get the full output result table. Default is 0.
Types: Int





Function Output

Return Value: teradataml.DataFrame. Returns the output of the function as a teradataml DataFrame.



Usage Considerations

NA





teradatamlwidgets.plot.Ui Class


Purpose

Allows a user interface for plotting that allows the user to set plotting parameters and then visualize the plots. The internal implementation uses the functionality of TD_PLOT exposed in teradataml DataFrame.



Syntax

teradatamlwidgets.plot.Ui(table_name = '', df = None, current_plot = '', ...all other parameter arguments...)



Arguments


table_name:

Required Argument (IF df argument is not set).
An input table name to use for plotting.
Ex: teradatamlwidgets.plot.Ui(table_name = "titanic")
Types: String



df:

Required Argument (IF table_name argument is not set).
An input teradataml dataframe to use for plotting.
Ex: teradatamlwidgets.plot.Ui(df = DataFrame("titanic"))
Types: teradataml.DataFrame



current_plot:

Optional Argument.
If you want chart type pre-selected.
Ex: teradatamlwidgets.plot.Ui(table_name = "titanic", current_plot = "Bar")
Possible Values: Line, Bar, Scatter, Corr, Wiggle, Mesh, Geom
Types: String



..all other parameter arguments..:

Optional Argument(s).
If you want any other parameters pre-selected, see their argument name in description.
Ex: teradatamlwidgets.plot.Ui(table_name = "titanic", current_plot = "Bar", style='green')
Types: String



Refer to full list of parameter options in TD_PLOT teradataml documentation (https://docs.teradata.com/r/Enterprise_IntelliFlex_VMware/Teradata-Package-for-Python-User-Guide-17.20/Plotting-in-teradataml).




Function Output

This function will return instance of notebook UI interface for TD_PLOT.



Usage Considerations

The first time this is called, the “Login” user interface will be displayed so the user can log into a Teradata instance which creates the internal instance.





teradatamlwidgets.plot.ShowPlots Method

Purpose

ShowPlots combines multiple plots together into one figure.


Syntax

teradatamlwidgets.plot.ShowPlots(plots, nrows, ncols, grid=None)


Arguments


plots:

Required Argument.
List of UI Plot instances you want to combine into one figure.
Types: List of plot.Ui



nrows:

Required Argument (IF grid argument not supplied).
Number of rows.
Types: int



ncols:

Required Argument (IF grid argument not supplied).
Number of columns.
Types: int



grid:

Optional Argument.
Grid layout.
Types: map of tuples
Example: Generates a figure with 2 subplots in the first row and a first column and second colum respectively and 1 sublpot in the second row (refer to the teradataml subplot documentation)

grid={(1,1): (1, 1), (1,2): (1,1), (2, 1): (1, 2)}











Documentation
General product information, including installation instructions, is available in the Teradata Documentation website
License
Use of the Teradata Widgets Package is governed by the License Agreement for the Teradata Widgets Package for Advanced Analytics.
After installation, the LICENSE and LICENSE-3RD-PARTY files are located in the teradata_widget directory of the Python installation directory.