to_csv

Converts a column containing a StructType into a CSV string. Throws an exception, in the case of an unsupported type.

Syntax

from pyspark.sql import functions as sf

sf.to_csv(col, options=None)

Parameters

Parameter	Type	Description
col	pyspark.sql.Column or str	Name of column containing a struct.
options	dict, optional	Options to control converting. Accepts the same options as the CSV datasource.

Returns

pyspark.sql.Column: A CSV string converted from the given StructType.

Examples

Example 1: Converting a simple StructType to a CSV string

from pyspark.sql import Row, functions as sf
data = [(1, Row(age=2, name='Alice'))]
df = spark.createDataFrame(data, ("key", "value"))
df.select(sf.to_csv(df.value)).show()

+-------------+
|to_csv(value)|
+-------------+
|      2,Alice|
+-------------+

Example 2: Converting a complex StructType to a CSV string

from pyspark.sql import Row, functions as sf
data = [(1, Row(age=2, name='Alice', scores=[100, 200, 300]))]
df = spark.createDataFrame(data, ("key", "value"))
df.select(sf.to_csv(df.value)).show(truncate=False)

+-------------------------+
|to_csv(value)            |
+-------------------------+
|2,Alice,"[100, 200, 300]"|
+-------------------------+

Example 3: Converting a StructType with null values to a CSV string

from pyspark.sql import Row, functions as sf
from pyspark.sql.types import StructType, StructField, IntegerType, StringType
data = [(1, Row(age=None, name='Alice'))]
schema = StructType([
  StructField("key", IntegerType(), True),
  StructField("value", StructType([
    StructField("age", IntegerType(), True),
    StructField("name", StringType(), True)
  ]), True)
])
df = spark.createDataFrame(data, schema)
df.select(sf.to_csv(df.value)).show()

+-------------+
|to_csv(value)|
+-------------+
|       ,Alice|
+-------------+

Example 4: Converting a StructType with different data types to a CSV string

from pyspark.sql import Row, functions as sf
data = [(1, Row(age=2, name='Alice', isStudent=True))]
df = spark.createDataFrame(data, ("key", "value"))
df.select(sf.to_csv(df.value)).show()

+-------------+
|to_csv(value)|
+-------------+
| 2,Alice,true|
+-------------+