Teradata Package for Python Function Reference | 20.00 - array_sum - Teradata Package for Python - Look here for syntax, methods and examples for the functions included in the Teradata Package for Python.

Teradata® Package for Python Function Reference - 20.00

Deployment
VantageCloud
VantageCore
Edition
VMware
Enterprise
IntelliFlex
Product
Teradata Package for Python
Release Number
20.00.00.11
Published
August 2026
ft:locale
en-US
ft:lastEdition
2026-08-13
dita:id
TeradataPython_FxRef_Enterprise_2000
Product Category
Teradata Vantage
teradataml.dataframe.sql.DataFrameColumn.array_sum = array_sum(self, lower_bound=None, upper_bound=None)
DESCRIPTION:
    Compute the sum of all elements in the array.
 
PARAMETERS:
    lower_bound:
        Optional Argument.
        Specifies the starting index for sum calculation (inclusive).
        Note:
            * If specified, both "lower_bound" and "upper_bound" arguments must be provided.
        Types: int
 
    upper_bound:
        Optional Argument.
        Specifies the ending index for sum calculation (inclusive).
        Note:
            * If specified, both "lower_bound" and "upper_bound" arguments must be provided.
        Types: int
 
RETURNS:
    ColumnExpression
 
EXAMPLES:
    >>> from teradataml import *
    >>> load_example_data("array", "array_table")
 
    # Create a DataFrame on 'array_table'.
    >>> df = DataFrame("array_table")
    >>> df
                     arr1                   arr2                        arr3
    id                                                                      
    1    (10,20,30,40,50)     (23,200,215,40,21)  ('ab','bc','cd','ab','ef')
    4   (180,28,38,48,58)  (30,NULL,NULL,250,27)  ('mn','no',NULL,'op','pq')
    2   (150,25,35,45,55)       (28,50,95,90,26)  ('xy','yz','za','ab','xy')
    6   (16,261,36,46,56)     (29,170,160,46,25)  ('uv','xy','ab','xy','yz')
    3   (12,22,320,42,52)     (25,22,140,200,23)  ('pq','ab','ab','st','tu')
    5    (14,24,34,44,54)  (26,NULL,NULL,180,24)  ('ij','jk',NULL,'kl','lm')
 
    # Example 1: Calculate sum of all elements in array column 'arr1'.
    >>> res = df.assign(sum_res = df.arr1.array_sum())
    >>> res
                     arr1                   arr2                        arr3    sum_res
    id                                                                              
    1    (10,20,30,40,50)     (23,200,215,40,21)  ('ab','bc','cd','ab','ef')      150.0
    4   (180,28,38,48,58)  (30,NULL,NULL,250,27)  ('mn','no',NULL,'op','pq')      352.0
    2   (150,25,35,45,55)       (28,50,95,90,26)  ('xy','yz','za','ab','xy')      310.0
    6   (16,261,36,46,56)     (29,170,160,46,25)  ('uv','xy','ab','xy','yz')      415.0
    3   (12,22,320,42,52)     (25,22,140,200,23)  ('pq','ab','ab','st','tu')      448.0
    5    (14,24,34,44,54)  (26,NULL,NULL,180,24)  ('ij','jk',NULL,'kl','ab')      170.0
 
    # Example 2: Calculate sum of elements in array column 'arr1' from first position
    #            to third position.
    >>> res = df.assign(sum_res = df.arr1.array_sum(lower_bound=1, upper_bound=3))
    >>> res
                     arr1                   arr2                        arr3    sum_res
    id                                                                              
    1    (10,20,30,40,50)     (23,200,215,40,21)  ('ab','bc','cd','ab','ef')       60.0
    4   (180,28,38,48,58)  (30,NULL,NULL,250,27)  ('mn','no',NULL,'op','pq')      246.0
    2   (150,25,35,45,55)       (28,50,95,90,26)  ('xy','yz','za','ab','xy')      210.0
    6   (16,261,36,46,56)     (29,170,160,46,25)  ('uv','xy','ab','xy','yz')      313.0
    3   (12,22,320,42,52)     (25,22,140,200,23)  ('pq','ab','ab','st','tu')      354.0
    5    (14,24,34,44,54)  (26,NULL,NULL,180,24)  ('ij','jk',NULL,'kl','ab')       72.0