try_avg
Returns the mean calculated from values of a group and the result is null on overflow.
Syntax
Python
from pyspark.sql import functions as sf
sf.try_avg(col)
Parameters
Parameter | Type | Description |
|---|---|---|
|
| Target column to compute on. |
Examples
Example 1: Calculating the average age
Python
import pyspark.sql.functions as sf
df = spark.createDataFrame([(1982, 15), (1990, 2)], ["birth", "age"])
df.select(sf.try_avg("age")).show()
Output
+------------+
|try_avg(age)|
+------------+
| 8.5|
+------------+
Example 2: Calculating the average age with None
Python
import pyspark.sql.functions as sf
df = spark.createDataFrame([(1982, None), (1990, 2), (2000, 4)], ["birth", "age"])
df.select(sf.try_avg("age")).show()
Output
+------------+
|try_avg(age)|
+------------+
| 3.0|
+------------+