td_except | Teradata Python Package - 17.00 - td_except - Teradata Package for Python

Teradata® Package for Python User Guide

Product
Teradata Package for Python
Release Number
17.00
Release Date
November 2021
Content Type
User Guide
Publication ID
B700-4006-070K
Language
English (United States)
Use the td_except() function to return the rows that appear in the first teradataml DataFrame and not in other teradataml DataFrame(s) along the index axis.

Example Prerequisites

>>> from teradataml import load_example_data
>>> load_example_data("dataframe", "setop_test1")
>>> load_example_data("dataframe", "setop_test2")
>>> from teradataml.dataframe import dataframe
>>> from teradataml.dataframe.setop import td_except

Example 1: Run td_except() on rows from two DataFrames, using default signature

This example applies the except operation on rows from two teradataml DataFrames when using default signature of the function.

>>> df1 = DataFrame('setop_test1')
>>> df1
   masters   gpa     stats programming  admitted
id                                             
62      no  3.70  Advanced    Advanced         1
53     yes  3.50  Beginner      Novice         1
69      no  3.96  Advanced    Advanced         1
61     yes  4.00  Advanced    Advanced         1
58      no  3.13  Advanced    Advanced         1
51     yes  3.76  Beginner    Beginner         0
68      no  1.87  Advanced      Novice         1
66      no  3.87    Novice    Beginner         1
60      no  4.00  Advanced      Novice         1
59      no  3.65    Novice      Novice         1
>>> df2 = DataFrame('setop_test2')
>>> df2
   masters   gpa     stats programming  admitted
id                                             
12      no  3.65    Novice      Novice         1
15     yes  4.00  Advanced    Advanced         1
14     yes  3.45  Advanced    Advanced         0
20     yes  3.90  Advanced    Advanced         1
18     yes  3.81  Advanced    Advanced         1
17      no  3.83  Advanced    Advanced         1
13      no  4.00  Advanced      Novice         1
11      no  3.13  Advanced    Advanced         1
60      no  4.00  Advanced      Novice         1
19     yes  1.98  Advanced    Advanced         0
>>> idf = td_except([df1[df1.id<55] , df2])
>>> idf
   masters   gpa     stats programming  admitted
id                                             
51     yes  3.76  Beginner    Beginner         0
50     yes  3.95  Beginner    Beginner         0
54     yes  3.50  Beginner    Advanced         1
52      no  3.70    Novice    Beginner         1
53     yes  3.50  Beginner      Novice         1
53     yes  3.50  Beginner      Novice         1

Example 2: Run td_except() on rows from two DataFrames, discarding duplicate rows

This examples applies the except operation on rows from the two teradataml DataFrames from previous example, discarding duplicate rows from the result by passing allow_duplicates = False.

>>> idf = td_except([df1[df1.id<55] , df2], allow_duplicates=False)
>>> idf
   masters   gpa     stats programming  admitted
id                                             
54     yes  3.50  Beginner    Advanced         1
51     yes  3.76  Beginner    Beginner         0
53     yes  3.50  Beginner      Novice         1
50     yes  3.95  Beginner    Beginner         0
52      no  3.70    Novice    Beginner         1

Example 3: Run td_except() on more than two DataFrames

This example shows what happens when td_except is used on more than two teradataml DataFrames. In this example, you have three teradataml DataFrames as df1, df2 & df3, the operation is applied on df1 and df2 first, and then the operation is applied again on the result and df3.

>>> df3 = df1[df1.gpa <= 3.9]
>>> # Effective operation here would be, (df1-df2)-df3
>>> idf = td_except([df1, df2, df3])
>>> idf
   masters   gpa     stats programming  admitted
id                                             
61     yes  4.00  Advanced    Advanced         1
50     yes  3.95  Beginner    Beginner         0
69      no  3.96  Advanced    Advanced         1