pyspark.sql.DataFrame.withMetadata#

DataFrame.withMetadata(columnName, metadata)[source]#

Returns a new DataFrame by updating an existing column with metadata.

New in version 3.3.0.

Changed in version 3.4.0: Supports Spark Connect.

Parameters

columnNamestr: string, name of the existing column to update the metadata.
metadatadict: dict, new metadata to be assigned to df.schema[columnName].metadata

Returns

DataFrame: DataFrame with updated metadata column.

Examples

>>> df = spark.createDataFrame([(2, "Alice"), (5, "Bob")], schema=["age", "name"])
>>> df_meta = df.withMetadata('age', {'foo': 'bar'})
>>> df_meta.schema['age'].metadata
{'foo': 'bar'}