regr_avgy

聚合函数：返回组中非 null 对的依赖变量的平均值，其中 y 依赖变量是 x 独立变量。

有关相应的 Databricks SQL 函数，请参阅 regr_avgy 聚合函数。

Syntax

import pyspark.sql.functions as sf

sf.regr_avgy(y=<y>, x=<x>)

参数

退货

pyspark.sql.Column：组中非 null 对的从属变量的平均值。

例子

示例 1：所有对均为非 null。

import pyspark.sql.functions as sf
df = spark.sql("SELECT * FROM VALUES (1, 2), (2, 2), (2, 3), (2, 4) AS tab(y, x)")
df.select(sf.regr_avgy("y", "x"), sf.avg("y")).show()

+---------------+------+
|regr_avgy(y, x)|avg(y)|
+---------------+------+
|           1.75|  1.75|
+---------------+------+

示例 2：所有对的 x 值均为 null。

import pyspark.sql.functions as sf
df = spark.sql("SELECT * FROM VALUES (1, null) AS tab(y, x)")
df.select(sf.regr_avgy("y", "x"), sf.avg("y")).show()

+---------------+------+
|regr_avgy(y, x)|avg(y)|
+---------------+------+
|           NULL|   1.0|
+---------------+------+

示例 3：所有对的 y 值为 null。

import pyspark.sql.functions as sf
df = spark.sql("SELECT * FROM VALUES (null, 1) AS tab(y, x)")
df.select(sf.regr_avgy("y", "x"), sf.avg("y")).show()

+---------------+------+
|regr_avgy(y, x)|avg(y)|
+---------------+------+
|           NULL|  NULL|
+---------------+------+

示例 4：某些对的 x 值为 null。

import pyspark.sql.functions as sf
df = spark.sql("SELECT * FROM VALUES (1, 2), (2, null), (2, 3), (2, 4) AS tab(y, x)")
df.select(sf.regr_avgy("y", "x"), sf.avg("y")).show()

+------------------+------+
|   regr_avgy(y, x)|avg(y)|
+------------------+------+
|1.6666666666666...|  1.75|
+------------------+------+

示例 5：某些对的 x 或 y 值为 null。

import pyspark.sql.functions as sf
df = spark.sql("SELECT * FROM VALUES (1, 2), (2, null), (null, 3), (2, 4) AS tab(y, x)")
df.select(sf.regr_avgy("y", "x"), sf.avg("y")).show()

+---------------+------------------+
|regr_avgy(y, x)|            avg(y)|
+---------------+------------------+
|            1.5|1.6666666666666...|
+---------------+------------------+