TO_BOOLEAN¶

TO_BOOLEAN(COLUMN_EXPRESSION)

Casts the input to a boolean value. If the input is a string, it will be cast to true if it is 'true', 't', 'yes', 'y', '1', cast to false if it is 'false', 'f', 'no', 'n', '0', and throw an error otherwise. If the input is an integer, it will be cast to true if it is non-zero and false if it is zero. If the input is a float, it will be cast to true if it is non-zero, false if it is zero, and throw an error on other inputs (e.g. inf) input. If the input is NULL, the output will be NULL.

Example:

We are given table1 with columns a and b and c

table1 = pd.DataFrame({
    'a': [1.1, 0, 2],
    'b': ['t', 'f', 'YES'],
    'c': [None, 1, 0]
})

upon query

SELECT
    TO_BOOLEAN(a) AS a,
    TO_BOOLEAN(b) AS b,
    TO_BOOLEAN(c) AS c
FROM table1;

we will get the following output:

       a      b      c
0   True   True   <NA>
1  False  False   True
2   True   True  False

Upon query

SELECT TO_BOOLEAN('other')

we see the following error:

ValueError: invalid value for boolean conversion: string must be one of {'true', 't', 'yes', 'y', 'on', '1'} or {'false', 'f', 'no', 'n', 'off', '0'}

Note

BodoSQL will read NaNs as NULL and thus will not produce errors on NaN input.