Filtering with Boolean Column Requires a Comparison | Teradata Python Package - Filtering with Boolean Column Requires a Comparison - Teradata Vantage

Teradata® VantageCloud Lake

Deployment
VantageCloud
Edition
Lake
Product
Teradata Vantage
Published
January 2023
ft:locale
en-US
ft:lastEdition
2024-12-11
dita:mapPath
phg1621910019905.ditamap
dita:ditavalPath
pny1626732985837.ditaval
dita:id
phg1621910019905

The Analytics Database 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 ';'.