pyspark.sql.functions.regr_avgx#
- pyspark.sql.functions.regr_avgx(y, x)[source]#
Aggregate function: returns the average of the independent variable for non-null pairs in a group, where y is the dependent variable and x is the independent variable.
New in version 3.5.0.
- Parameters
- Returns
Column
the average of the independent variable for non-null pairs in a group.
Examples
Example 1: All pairs are non-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_avgx("y", "x"), sf.avg("x")).show() +---------------+------+ |regr_avgx(y, x)|avg(x)| +---------------+------+ | 2.75| 2.75| +---------------+------+
Example 2: All pairs’ x values are null
>>> import pyspark.sql.functions as sf >>> df = spark.sql("SELECT * FROM VALUES (1, null) AS tab(y, x)") >>> df.select(sf.regr_avgx("y", "x"), sf.avg("x")).show() +---------------+------+ |regr_avgx(y, x)|avg(x)| +---------------+------+ | NULL| NULL| +---------------+------+
Example 3: All pairs’ y values are null
>>> import pyspark.sql.functions as sf >>> df = spark.sql("SELECT * FROM VALUES (null, 1) AS tab(y, x)") >>> df.select(sf.regr_avgx("y", "x"), sf.avg("x")).show() +---------------+------+ |regr_avgx(y, x)|avg(x)| +---------------+------+ | NULL| 1.0| +---------------+------+
Example 4: Some pairs’ x values are 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_avgx("y", "x"), sf.avg("x")).show() +---------------+------+ |regr_avgx(y, x)|avg(x)| +---------------+------+ | 3.0| 3.0| +---------------+------+
Example 5: Some pairs’ x or y values are 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_avgx("y", "x"), sf.avg("x")).show() +---------------+------+ |regr_avgx(y, x)|avg(x)| +---------------+------+ | 3.0| 3.0| +---------------+------+