Intro
This section present several use cases to give ideas how each function may be used.
Each time a method is used in a use cases, it's full documentation will be available in a collapsible
section. For instance, if a use-case uses the method spark_frame.functions.nullable
you will see this
section at the end of the section:
nullable
nullable(col: Column) -> Column
Make a pyspark.sql.Column
nullable.
This is especially useful for literal which are always non-nullable by default.
Examples:
>>> from pyspark.sql import SparkSession
>>> spark = SparkSession.builder.appName("doctest").getOrCreate()
>>> from pyspark.sql import functions as f
>>> df = spark.sql('''SELECT 1 as a''').withColumn("b", f.lit("2"))
>>> df.printSchema()
root
|-- a: integer (nullable = false)
|-- b: string (nullable = false)
>>> res = df.withColumn('a', nullable(f.col('a'))).withColumn('b', nullable(f.col('b')))
>>> res.printSchema()
root
|-- a: integer (nullable = true)
|-- b: string (nullable = true)
Source code in spark_frame/functions.py
You can also find a comprehensive list of all methods in the reference.