try_avg

Returns the mean calculated from values of a group and the result is null on overflow.

Syntax

from pyspark.sql import functions as sf

sf.try_avg(col)

Parameters

Parameter	Type	Description
col	pyspark.sql.Column or column name	Target column to compute on.

Examples

Example 1: Calculating the average age

import pyspark.sql.functions as sf
df = spark.createDataFrame([(1982, 15), (1990, 2)], ["birth", "age"])
df.select(sf.try_avg("age")).show()

+------------+
|try_avg(age)|
+------------+
|         8.5|
+------------+

Example 2: Calculating the average age with None

import pyspark.sql.functions as sf
df = spark.createDataFrame([(1982, None), (1990, 2), (2000, 4)], ["birth", "age"])
df.select(sf.try_avg("age")).show()

+------------+
|try_avg(age)|
+------------+
|         3.0|
+------------+