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

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.

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 ';'.