Filtering with Boolean Column Requires a Comparison - Teradata Python Package

Teradata® Python Package User Guide

Product
Teradata Python Package
Release Number
16.20
Published
February 2020
Language
English (United States)
Last Update
2020-02-29
dita:mapPath
rkb1531260709148.ditamap
dita:ditavalPath
Generic_no_ie_no_tempfilter.ditaval
dita:id
B700-4006
lifecycle
previous
Product Category
Teradata Vantage

The Advanced SQL Engine does not support the Boolean data type. So the values '0' and '1' are used instead. To be consistent with pandas, '0' maps to 'False' and '1' maps to 'True'. This implies that the Boolean column in teradataml is numeric and behaves like a numeric column.

For example:
import teradataml
>>> df = df.assign(drop_columns = True,
                   Name= df.Name,
                   is_setosa = df.Name.str.contains('Setosa')
>>> df
              Name is_setosa
0  Iris-versicolor         0
1   Iris-virginica         0
2  Iris-versicolor         0
3   Iris-virginica         0
4   Iris-virginica         0
5      Iris-setosa         1
6   Iris-virginica         0
7  Iris-versicolor         0
8      Iris-setosa         1
9  Iris-versicolor         0
>>> df[df.is_setosa == 1]
          Name is_setosa
0  Iris-setosa         1
1  Iris-setosa         1
2  Iris-setosa         1
3  Iris-setosa         1
4  Iris-setosa         1
5  Iris-setosa         1
6  Iris-setosa         1
7  Iris-setosa         1
8  Iris-setosa         1
9  Iris-setosa         1

Using Boolean literals 'True' and 'False' when comparing is supported.

For example:

>>> df[df.is_setosa == True]
 
          Name is_setosa
0  Iris-setosa         1
1  Iris-setosa         1
2  Iris-setosa         1
3  Iris-setosa         1
4  Iris-setosa         1
5  Iris-setosa         1
6  Iris-setosa         1
7  Iris-setosa         1
8  Iris-setosa         1
9  Iris-setosa         1
>>> df[df.is_setosa == False]
 
              Name is_setosa
0  Iris-versicolor         0
1   Iris-virginica         0
2  Iris-versicolor         0
3   Iris-virginica         0
4   Iris-virginica         0
5   Iris-virginica         0
6  Iris-versicolor         0
7  Iris-versicolor         0
8   Iris-virginica         0
9  Iris-versicolor         0

A comparison operator is needed whenever using a Boolean column, or else an error is thrown.

For example:

>>> df[df.is_setosa]
 
 
OperationalError: [Version 16.20.0.38] [Session 1961] [Teradata Database] [Error 3707] Syntax error, expected something like a 'SUCCEEDS' keyword or a 'MEETS' keyword or a 'PRECEDES' keyword or an 'IN' keyword or a 'CONTAINS' keyword between the word 'is_setosa' and ';'.