Teradata Package for Python Function Reference on VantageCloud Lake - array_insert - 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 on VantageCloud Lake

Deployment
VantageCloud
Edition
Lake
Product
Teradata Package for Python
Release Number
20.00.00.11
Publication Date
August 2026
Content Type
Programming Reference
Publication ID
B700-4500-200K
ft:locale
en-US
ft:lastEdition
2026-08-13
ft:sourceId
FTML
dita:id
TeradataPython_FxRef_Lake_2000
Product Category
Teradata Vantage
teradataml.dataframe.sql.DataFrameColumn.array_insert = array_insert(self, index, element)
DESCRIPTION:
    Insert an element at the specified index in the array.
 
PARAMETERS:
    index:
        Required Argument.
        Specifies the index (1-based) where to insert the element.
        Types: int OR ColumnExpression
        
    element:
        Required Argument.
        Specifies the element to insert.
        Types: ColumnExpression OR Python literal
 
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: Insert element 'txt' at index 3 in array column 'arr3'.
    >>> res = df.assign(modified_arr = df.arr3.array_insert(index=3, element="txt"))
    >>> res
                     arr1                   arr2                        arr3                      modified_arr
    id                                                                                                        
    3   (12,22,320,42,52)     (25,22,140,200,23)  ('pq','ab','ab','st','tu')  ('pq','ab','txt','ab','st','tu')
    1    (10,20,30,40,50)     (23,200,215,40,21)  ('ab','bc','cd','ab','ef')  ('ab','bc','txt','cd','ab','ef')
    2   (150,25,35,45,55)       (28,50,95,90,26)  ('xy','yz','za','ab','xy')  ('xy','yz','txt','za','ab','xy')
    5    (14,24,34,44,54)  (26,NULL,NULL,180,24)  ('ij','jk',NULL,'kl','lm')  ('ij','jk','txt',NULL,'kl','lm')
    6   (16,261,36,46,56)     (29,170,160,46,25)  ('uv','xy','ab','xy','yz')  ('uv','xy','txt','ab','xy','yz')
    4   (180,28,38,48,58)  (30,NULL,NULL,250,27)  ('mn','no',NULL,'op','pq')  ('mn','no','txt',NULL,'op','pq')
 
    # Example 2: Insert element from column 'id' at index specified in column 'idx' in array column 'arr3'.
    >>> tdf = df.assign(idx=4)
    >>> res = tdf.assign(modified_arr = tdf.arr2.array_insert(tdf.idx, tdf.id))
    >>> res
                     arr1                   arr2                        arr3  idx             modified_arr
    id                                                                                                    
    2   (150,25,35,45,55)       (28,50,95,90,26)  ('xy','yz','za','ab','xy')    4       (28,50,95,2,90,26)
    3   (12,22,320,42,52)     (25,22,140,200,23)  ('pq','ab','ab','st','tu')    4     (25,22,140,3,200,23)
    6   (16,261,36,46,56)     (29,170,160,46,25)  ('uv','xy','ab','xy','yz')    4     (29,170,160,6,46,25)
    4   (180,28,38,48,58)  (30,NULL,NULL,250,27)  ('mn','no',NULL,'op','pq')    4  (30,NULL,NULL,4,250,27)
    1    (10,20,30,40,50)     (23,200,215,40,21)  ('ab','bc','cd','ab','ef')    4     (23,200,215,1,40,21)
    5    (14,24,34,44,54)  (26,NULL,NULL,180,24)  ('ij','jk',NULL,'kl','lm')    4  (26,NULL,NULL,5,180,24)
 
    # Example 3: Insert element at index 10 greater than array size in array column 'arr1'.
    >>> res = df.assign(modified_arr = df.arr1.array_insert(index=10, element=999))
    >>> res
                     arr1                   arr2                        arr3                               modified_arr
    id                                                                                                                 
    5    (14,24,34,44,54)  (26,NULL,NULL,180,24)  ('ij','jk',NULL,'kl','lm')   (14,24,34,44,54,NULL,NULL,NULL,NULL,999)
    2   (150,25,35,45,55)       (28,50,95,90,26)  ('xy','yz','za','ab','xy')  (150,25,35,45,55,NULL,NULL,NULL,NULL,999)
    6   (16,261,36,46,56)     (29,170,160,46,25)  ('uv','xy','ab','xy','yz')  (16,261,36,46,56,NULL,NULL,NULL,NULL,999)
    1    (10,20,30,40,50)     (23,200,215,40,21)  ('ab','bc','cd','ab','ef')   (10,20,30,40,50,NULL,NULL,NULL,NULL,999)
    3   (12,22,320,42,52)     (25,22,140,200,23)  ('pq','ab','ab','st','tu')  (12,22,320,42,52,NULL,NULL,NULL,NULL,999)
    4   (180,28,38,48,58)  (30,NULL,NULL,250,27)  ('mn','no',NULL,'op','pq')  (180,28,38,48,58,NULL,NULL,NULL,NULL,999)