pyspark.sql.functions.acosh#
- pyspark.sql.functions.acosh(col)[source]#
- Mathematical Function: Computes the inverse hyperbolic cosine (also known as arcosh) of the given column or expression. - New in version 3.1.0. - Changed in version 3.4.0: Supports Spark Connect. - Parameters
- colColumnor str
- The target column or expression to compute the inverse hyperbolic cosine on. 
 
- col
- Returns
- Column
- A new column object representing the inverse hyperbolic cosine of the input. 
 
 - Examples - Example 1: Compute the inverse hyperbolic cosine of a column of numbers - >>> from pyspark.sql import functions as sf >>> df = spark.createDataFrame([(1,), (2,)], ["value"]) >>> df.select("value", sf.acosh(df.value)).show() +-----+------------------+ |value| ACOSH(value)| +-----+------------------+ | 1| 0.0| | 2|1.3169578969248...| +-----+------------------+ - Example 2: Compute the inverse hyperbolic cosine of a column with null values - >>> from pyspark.sql import functions as sf >>> from pyspark.sql.types import StructType, StructField, IntegerType >>> schema = StructType([StructField("value", IntegerType(), True)]) >>> df = spark.createDataFrame([(None,)], schema=schema) >>> df.select(sf.acosh(df.value)).show() +------------+ |ACOSH(value)| +------------+ | NULL| +------------+ - Example 3: Compute the inverse hyperbolic cosine of a column with values less than 1 - >>> from pyspark.sql import functions as sf >>> df = spark.createDataFrame([(0.5,), (-0.5,)], ["value"]) >>> df.select(sf.acosh(df.value)).show() +------------+ |ACOSH(value)| +------------+ | NaN| | NaN| +------------+