Teradata Package for Python Function Reference | 20.00 - array_size - 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_size = array_size(self, lower_bound=None, upper_bound=None)
- DESCRIPTION:
Get the size of the array.
Note:
* The function does not consider uninitialized elements in the array.
For example, if scope of the array is 5 and only 3 elements are initialized,
the size returns 3.
PARAMETERS:
lower_bound:
Optional Argument.
Specifies the lower bound value to start counting for the elements.
Note:
* If specified, both "lower_bound" and "upper_bound" arguments must be provided.
Types: int
upper_bound:
Optional Argument.
Specifies the upper bound value to end the counting for the elements.
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')
>>> df.tdtypes
id INTEGER()
arr1 ARRAY_INTEGER('[1:10]')
arr2 ARRAY_INTEGER('[1:10]')
arr3 ARRAY_VARCHAR('[1:10]', length=4)
# Example 1: Get the size of array column 'arr1'.
>>> res = df.assign(arr1_size = df.arr1.array_size())
>>> res
arr1 arr2 arr3 arr1_size
id
1 (10,20,30,40,50) (23,200,215,40,21) ('ab','bc','cd','ab','ef') 5
4 (180,28,38,48,58) (30,NULL,NULL,250,27) ('mn','no',NULL,'op','pq') 5
2 (150,25,35,45,55) (28,50,95,90,26) ('xy','yz','za','ab','xy') 5
6 (16,261,36,46,56) (29,170,160,46,25) ('uv','xy','ab','xy','yz') 5
3 (12,22,320,42,52) (25,22,140,200,23) ('pq','ab','ab','st','tu') 5
5 (14,24,34,44,54) (26,NULL,NULL,180,24) ('ij','jk',NULL,'kl','lm') 5
# Example 2: Get the size of the array column 'arr1' with initialized elements.
>>> sdf = df.assign(arr1=Array((23, df.id, 5), atype=ARRAY_INTEGER('[5]', default_null=True)))
>>> res = sdf.assign(arr1_size = sdf.arr1.array_size())
>>> res
arr1 arr2 arr3 arr1_size
id
1 (23,1,5,NULL,NULL) (23,200,215,40,21) ('ab','bc','cd','ab','ef') 5
4 (23,4,5,NULL,NULL) (30,NULL,NULL,250,27) ('mn','no',NULL,'op','pq') 5
2 (23,2,5,NULL,NULL) (28,50,95,90,26) ('xy','yz','za','ab','xy') 5
6 (23,6,5,NULL,NULL) (29,170,160,46,25) ('uv','xy','ab','xy','yz') 5
3 (23,3,5,NULL,NULL) (25,22,140,200,23) ('pq','ab','ab','st','tu') 5
5 (23,5,5,NULL,NULL) (26,NULL,NULL,180,24) ('ij','jk',NULL,'kl','lm') 5
# Example 3: Get the size of elements in array column 'arr2' from second position to fourth position.
>>> res = df.assign(arr1_size = df.arr1.array_size(lower_bound=2, upper_bound=4))
>>> res
arr1 arr2 arr3 arr1_size
id
1 (10,20,30,40,50) (23,200,215,40,21) ('ab','bc','cd','ab','ef') 3
4 (180,28,38,48,58) (30,NULL,NULL,250,27) ('mn','no',NULL,'op','pq') 3
2 (150,25,35,45,55) (28,50,95,90,26) ('xy','yz','za','ab','xy') 3
6 (16,261,36,46,56) (29,170,160,46,25) ('uv','xy','ab','xy','yz') 3
3 (12,22,320,42,52) (25,22,140,200,23) ('pq','ab','ab','st','tu') 3
5 (14,24,34,44,54) (26,NULL,NULL,180,24) ('ij','jk',NULL,'kl','lm') 3