snowflake.snowpark.functions.explode_outer¶

snowflake.snowpark.functions.explode_outer(col: Union[Column, str]) → TableFunctionCall[source] (https://github.com/snowflakedb/snowpark-python/blob/v1.26.0/snowpark-python/src/snowflake/snowpark/functions.py#L1492-L1547)¶

Flattens a given array or map type column into individual rows. Unlike explode(), if array or map is empty, null or empty, then null values are produced. The default column name for the output column in case of array input column is VALUE, and is KEY and VALUE in case of map input column.

Parameters:: col – Column object or string name of the desired column

Examples::

>>> df = session.create_dataframe([[1, [1, 2, 3], {"Ashi Garami": "Single Leg X"}],
...                                [2, [11, 22], {"Sankaku": "Triangle"}],
...                                [3, [], {}]],
...                                schema=["idx", "lists", "maps"])
>>> df.select(df.idx, explode_outer(df.lists)).sort(col("idx")).show()
-------------------
|"IDX"  |"VALUE"  |
-------------------
|1      |1        |
|1      |2        |
|1      |3        |
|2      |11       |
|2      |22       |
|3      |NULL     |
-------------------

Copy

>>> df.select(df.idx, explode_outer(df.maps)).sort(col("idx")).show()
----------------------------------------
|"IDX"  |"KEY"        |"VALUE"         |
----------------------------------------
|1      |Ashi Garami  |"Single Leg X"  |
|2      |Sankaku      |"Triangle"      |
|3      |NULL         |NULL            |
----------------------------------------

Copy