TDMatrix | Input Classes for UAF Functions | teradataml - TDMatrix - Teradata Vantage

Create a TDMatrix object from a teradataml DataFrame representing a MATRIX in time series which is used as input to Unbounded Array Framework time series functions.

A matrix is a two-dimensional array that has rows and columns. A matrix is identified by its matrix id, that is, the id argument, and is indexed by its row_index and column_index arguments.

Example 1: Create a TDMatrix object

>>> from teradataml import create_context, load_example_data, DataFrame, TDMatrix

>>> con = create_context(host = host, user=user, password=passw)

>>> load_example_data("dataframe", "admissions_train")

# Create a DataFrame to be passed as input to TDMatrix.
>>> data = DataFrame("admissions_train")

# Create a TDMatrix object to be passed as input to UAF functions.
>>> res = TDMatrix(data=data, 
                   id='admitted', 
                   row_index='id',
                   column_index = 'admitted',
                   row_index_style="TIMECODE",
                   payload_field='payload_field',
                   payload_content='REAL')

>>> res
          masters   gpa     stats programming  admitted
   id
   15     yes  4.00  Advanced    Advanced         1
   34     yes  3.85  Advanced    Beginner         0
   13      no  4.00  Advanced      Novice         1
   38     yes  2.65  Advanced    Beginner         1
    5      no  3.44    Novice      Novice         0
   40     yes  3.95    Novice    Beginner         0
   7      yes  2.33    Novice      Novice         1
   22     yes  3.46    Novice    Beginner         0
   26     yes  3.57  Advanced    Advanced         1
    17     no  3.83  Advanced    Advanced         1