databricks.koalas.DataFrame.koalas.attach_id_column¶
-
koalas.attach_id_column(id_type: str, column: Union[Any, Tuple]) → DataFrame¶ Attach a column to be used as identifier of rows similar to the default index.
See also Default Index type.
- Parameters
- id_typestring
The id type.
‘sequence’ : a sequence that increases one by one.
Note
this uses Spark’s Window without specifying partition specification. This leads to move all data into single partition in single machine and could cause serious performance degradation. Avoid this method against very large dataset.
‘distributed-sequence’ : a sequence that increases one by one, by group-by and group-map approach in a distributed manner.
‘distributed’ : a monotonically increasing sequence simply by using PySpark’s monotonically_increasing_id function in a fully distributed manner.
- columnstring or tuple of string
The column name.
- Returns
- DataFrame
The DataFrame attached the column.
Examples
>>> df = ks.DataFrame({"x": ['a', 'b', 'c']}) >>> df.koalas.attach_id_column(id_type="sequence", column="id") x id 0 a 0 1 b 1 2 c 2
>>> df.koalas.attach_id_column(id_type="distributed-sequence", column=0) x 0 0 a 0 1 b 1 2 c 2
>>> df.koalas.attach_id_column(id_type="distributed", column=0.0) ... x 0.0 0 a ... 1 b ... 2 c ...
For multi-index columns:
>>> df = ks.DataFrame({("x", "y"): ['a', 'b', 'c']}) >>> df.koalas.attach_id_column(id_type="sequence", column=("id-x", "id-y")) x id-x y id-y 0 a 0 1 b 1 2 c 2
>>> df.koalas.attach_id_column(id_type="distributed-sequence", column=(0, 1.0)) x 0 y 1.0 0 a 0 1 b 1 2 c 2