snowflake.snowpark.DataFrame.unpivot¶
- DataFrame.unpivot(value_column: str, name_column: str, column_list: List[ColumnOrName]) DataFrame [source]¶
Rotates a table by transforming columns into rows. UNPIVOT is a relational operator that accepts two columns (from a table or subquery), along with a list of columns, and generates a row for each column specified in the list. In a query, it is specified in the FROM clause after the table name or subquery. Note that UNPIVOT is not exactly the reverse of PIVOT as it cannot undo aggregations made by PIVOT.
- Parameters:
value_column – The name to assign to the generated column that will be populated with the values from the columns in the column list.
name_column – The name to assign to the generated column that will be populated with the names of the columns in the column list.
column_list – The names of the columns in the source table or subequery that will be narrowed into a single pivot column. The column names will populate
name_column
, and the column values will populatevalue_column
.
Example:
>>> df = session.create_dataframe([ ... (1, 'electronics', 100, 200), ... (2, 'clothes', 100, 300) ... ], schema=["empid", "dept", "jan", "feb"]) >>> df = df.unpivot("sales", "month", ["jan", "feb"]).sort("empid") >>> df.show() --------------------------------------------- |"EMPID" |"DEPT" |"MONTH" |"SALES" | --------------------------------------------- |1 |electronics |JAN |100 | |1 |electronics |FEB |200 | |2 |clothes |JAN |100 | |2 |clothes |FEB |300 | ---------------------------------------------