FloatType#

class pyspark.sql.types.FloatType[source]#

Float data type, representing single precision floats.

Methods

`fromDDL`(ddl)	Creates `DataType` for a given DDL-formatted string.
`fromInternal`(obj)	Converts an internal SQL object into a native Python object.
`json`()
`jsonValue`()
`needConversion`()	Does this type needs conversion between Python object and internal SQL object.
`simpleString`()
`toInternal`(obj)	Converts a Python object into an internal SQL object.
`typeName`()

Methods Documentation

classmethod fromDDL(ddl)#

Creates DataType for a given DDL-formatted string.

New in version 4.0.0.

Parameters

ddlstr: DDL-formatted string representation of types, e.g. pyspark.sql.types.DataType.simpleString, except that top level struct type can omit the struct<> for the compatibility reason with spark.createDataFrame and Python UDFs.

Returns

DataType

Examples

Create a StructType by the corresponding DDL formatted string.

>>> from pyspark.sql.types import DataType
>>> DataType.fromDDL("b string, a int")
StructType([StructField('b', StringType(), True), StructField('a', IntegerType(), True)])

Create a single DataType by the corresponding DDL formatted string.

>>> DataType.fromDDL("decimal(10,10)")
DecimalType(10,10)

Create a StructType by the legacy string format.

>>> DataType.fromDDL("b: string, a: int")
StructType([StructField('b', StringType(), True), StructField('a', IntegerType(), True)])

fromInternal(obj)#: Converts an internal SQL object into a native Python object.

json()#

jsonValue()#

needConversion()#

Does this type needs conversion between Python object and internal SQL object.

This is used to avoid the unnecessary conversion for ArrayType/MapType/StructType.

simpleString()#

toInternal(obj)#: Converts a Python object into an internal SQL object.

classmethod typeName()#