pyspark.sql.functions.array_insert

pyspark.sql.functions.array_insert(arr: ColumnOrName, pos: Union[ColumnOrName, int], value: Any) → pyspark.sql.column.Column[source]

Collection function: adds an item into a given array at a specified array index. Array indices start at 1, or start from the end if index is negative. Index above array size appends the array, or prepends the array if index is negative, with ‘null’ elements.

New in version 3.4.0.

Parameters
arrColumn or str

name of column containing an array

posColumn or str or int

name of Numeric type column indicating position of insertion (starting at index 1, negative position is a start from the back of the array)

value :

a literal value, or a Column expression.

Returns
Column

an array of values, including the new specified value

Notes

Supports Spark Connect.

Examples

>>> df = spark.createDataFrame(
...     [(['a', 'b', 'c'], 2, 'd'), (['c', 'b', 'a'], -2, 'd')],
...     ['data', 'pos', 'val']
... )
>>> df.select(array_insert(df.data, df.pos.cast('integer'), df.val).alias('data')).collect()
[Row(data=['a', 'd', 'b', 'c']), Row(data=['c', 'b', 'd', 'a'])]
>>> df.select(array_insert(df.data, 5, 'hello').alias('data')).collect()
[Row(data=['a', 'b', 'c', None, 'hello']), Row(data=['c', 'b', 'a', None, 'hello'])]