pyspark.sql.functions.log¶

pyspark.sql.functions.log(arg1: Union[ColumnOrName, float], arg2: Optional[ColumnOrName] = None) → pyspark.sql.column.Column[source]¶

Returns the first argument-based logarithm of the second argument.

If there is only one argument, then this takes the natural logarithm of the argument.

New in version 1.5.0.

Changed in version 3.4.0: Supports Spark Connect.

Parameters

arg1Column, str or float: base number or actual number (in this case base is e)
arg2Column, str or float: number to calculate logariphm for.

Returns

Column: logariphm of given value.

Examples

>>> df = spark.createDataFrame([10, 100, 1000], "INT")
>>> df.select(log(10.0, df.value).alias('ten')).show() 
+---+
|ten|
+---+
|1.0|
|2.0|
|3.0|
+---+

And Natural logarithm

>>> df.select(log(df.value)).show() 
+-----------------+
|        ln(value)|
+-----------------+
|2.302585092994046|
|4.605170185988092|
|4.605170185988092|
+-----------------+

pyspark.sql.functions.hypot pyspark.sql.functions.log10